Wikiversity enwikiversity https://en.wikiversity.org/wiki/Wikiversity:Main_Page MediaWiki 1.47.0-wmf.22 first-letter Media Special Talk User User talk Wikiversity Wikiversity talk File File talk MediaWiki MediaWiki talk Template Template talk Help Help talk Category Category talk School School talk Portal Portal talk Topic Topic talk Collection Collection talk Draft Draft talk TimedText TimedText talk Module Module talk Event Event talk 4 1558 2835220 2834402 2026-09-30T18:59:57Z ~2026-52639-89 3111893 2835220 wikitext text/x-wiki {{Please leave this line alone (sandbox heading)}} What <quiz> 1111111-000000=1111111 90+10=100 </quiz> final work <quiz> 10-2=8 212+8+220 DIE DIE ALL OF YOU DIDE DIE DIEA A A G AG A KAGA KG:AS LAG SGSA"ASG G GSA AGSA GS AG GA GS GSAG AS <quiz> 22-1=21 23+21(11)=354 i6r6pmad139ywz8hrodgoj4hl92uap4 2835282 2835220 2026-10-01T08:06:06Z ~2026-52726-18 3111929 2835282 wikitext text/x-wiki {{Please leave this line alone (sandbox heading)}} What <quiz> 1111111-000000=1111111 90+10=100 </quiz> final work <quiz> 10-2=8 212+8+220 scotland forever A A G AG A KAGA KG:AS LAG SGSA"ASG G GSA AGSA GS AG GA GS GSAG AS <quiz> 22-1=21 23+21(11)=354 ian5i7il0ucgq7zirqdgzfjz2qqgnim 0 60198 2835286 2829923 2026-10-01T08:31:52Z Abid Educator 3111930 Relaxad posture and best sitting area while learning typing, further added a website link to learn typing while playing typing games, so that the leaning process is not looks bored. 2835286 wikitext text/x-wiki {{:{{BASEPAGENAME}}/Sidebar}} '''Typing''' is the process of entering or inputting text by pressing keys on a typewriter, computer keyboard, mobile phone, or calculator.<ref>[[Wikipedia: Typing]]</ref> Learners should practice typing for fifteen minutes each day until their typing speed is at least 30 words per minute. Learners can benefit from a comfortable, ergonomically suitable seating area that helps them maintain a supported, relaxed posture while learning typing. == Multimedia == * [https://www.typing.com/student/lessons Typing.com: Learn to Type] * [https://monkeytype.com/ Monkeytype] * [https://www.typetap.io TypeTap] * [https://www.typingbattles.com/ Typingbattle] == Activities == * Complete the [https://www.typing.com/student/lessons Typing.com lessons.] * Use [https://monkeytype.com/ Monkeytype.com] , and practice typing daily until you can reach 30 words per minute consistently. * Use [https://www.typetap.io TypeTap] and AI practice typing daily until you can reach 30 words per minute consistently. * Typing games such as [https://www.typingbattles.com/ TypingBattle] can make keyboarding practice more engaging, helping learners improve their typing speed and accuracy without getting bored. == See Also == * [[Elementary Typing]] * [[Introduction_to_Computers/Input_Devices |Input Devices]] * [[Wikipedia: Typing]] == References == {{reflist}} {{subpage navbar}} {{CourseCat}} [[Category:Computer Skills]] [[Category:Typing]] [[Category:Completed resources]] fy18lyowb2lfxj5y0a18enzmua1kuip 2835287 2835286 2026-10-01T08:33:34Z Abid Educator 3111930 rectified the typing mistake 2835287 wikitext text/x-wiki {{:{{BASEPAGENAME}}/Sidebar}} '''Typing''' is the process of entering or inputting text by pressing keys on a typewriter, computer keyboard, mobile phone, or calculator.<ref>[[Wikipedia: Typing]]</ref> Learners should practice typing for fifteen minutes each day until their typing speed is at least 30 words per minute. Learners can benefit from a comfortable, ergonomically suitable seating area that helps them maintain a supported, relaxed posture while learn typing. == Multimedia == * [https://www.typing.com/student/lessons Typing.com: Learn to Type] * [https://monkeytype.com/ Monkeytype] * [https://www.typetap.io TypeTap] * [https://www.typingbattles.com/ Typingbattle] == Activities == * Complete the [https://www.typing.com/student/lessons Typing.com lessons.] * Use [https://monkeytype.com/ Monkeytype.com] , and practice typing daily until you can reach 30 words per minute consistently. * Use [https://www.typetap.io TypeTap] and AI practice typing daily until you can reach 30 words per minute consistently. * Typing games such as [https://www.typingbattles.com/ TypingBattle] can make keyboarding practice more engaging, helping learners improve their typing speed and accuracy without getting bored. == See Also == * [[Elementary Typing]] * [[Introduction_to_Computers/Input_Devices |Input Devices]] * [[Wikipedia: Typing]] == References == {{reflist}} {{subpage navbar}} {{CourseCat}} [[Category:Computer Skills]] [[Category:Typing]] [[Category:Completed resources]] 64alnhx9xsvk75vst5lifzszx9n29fo 14 61682 2835279 2699367 2026-10-01T06:53:24Z Wolverène 1345688 incorrect interwiki 2835279 wikitext text/x-wiki This category is for articles listed under "Web Development" [[Category:Software]] [[Category:Computing]] 998l5rkozfl36du5eiq0069ik0k1ojx 0 75666 2835201 2831767 2026-09-30T15:26:36Z Jeanne Noiraud 1366702 /* Examples of scholarly wikis */ 2835201 wikitext text/x-wiki __TOC__ ==Purpose== This page is meant to support some brain storming on the relative merits of paper-based and wiki-based scholarly communication, as discussed in a [http://ways.org/en/blogs/2008/dec/28/the_journal_scope_in_focus_putting_scholarly_communication_in_context blog post] that was later [http://ways.org/en/blogs/2009/sep/29/what_would_science_look_like_if_it_were_invented_today_part_ii_knowledge_structuring updated and expanded]. Feel free to add to it, here or there, and to [http://en.citizendium.org/wiki/User:Daniel_Mietchen/Talks/LSWT_2010/Integrating_wikis_with_scientific_workflows reuse] [http://en.citizendium.org/wiki/User:Daniel_Mietchen/Talks/COASP_2010/Start it]. ==Comparison between paper-based and wiki-based scholarly communication systems== {| |style="text-align:center;background:#f0f0f0;{{text color default}};"|'''Feature of science communication''' |style="text-align:center;background:#f0f0f0;{{text color default}};"|'''Paper-based practice''' |style="text-align:center;background:#f0f0f0;{{text color default}};"|'''Comment''' |style="text-align:center;background:#f0f0f0;{{text color default}};"|'''Wiki-based practice''' |style="text-align:center;background:#f0f0f0;{{text color default}};"|'''Comment''' |- | ideas|| || no timestemp system that is universal and transparent || || universal and transparent timestemp system |- | research design|| || version control is tedious in collaborative studies || || version control is standard |- | research proposal|| || version control is tedious in collaborative studies || || version control is standard |- | research funding|| || || || |- | data acquisition|| || || || |- | data analysis|| || || || |- | manuscript writing|| || version control is tedious in collaborative studies || || version control is standard |- | manuscript formatting||already largely standardized with LaTeX templates, less so with MS Word, OpenOffice and others || ||standardized to some extent by the wiki syntax but not as much as a typical TeX style file allows || |- | reference formatting||already largely standardized with BibTeX, Endnote and similar || ||standardized to some extent by the wiki syntax, via [http://en.citizendium.org/wiki/Template:Citation citation templates] and [http://clinical.uthscsa.edu/cite/ automated reference wikification] || |- | manuscript version tracking||requires external tools, e.g. Subversion, Google doc or a wiki || || standard || |- | choosing publication venue|| scope and perceived "quality" of a journal || || there are not too many suitable wikis around and indeed, one of the purposes of publishing in a wiki would be to have all relevant information in one freely accessible spot, rather than in zillions of journals as in the paper-based world|| |- | abstract||always written anew || only provided in a human-readable manner || always written anew || could easily be made machine-readable even after initial publication |- | introduction||always written anew, with some author-specific redundancy|| || updated each time || |- | methods||always written anew, with some author-specific redundancy|| || updated each time || |- | results||always written anew || only provided in a human-readable manner || always written anew || could easily be made machine-readable even after initial publication |- | discussion||always written anew, with some author-specific redundancy|| || updated each time || |- | conclusions|| || || || |- | references|| separate section; never linked to online version, often not even with URI || tedious for both author and reader; often not balanced|| link to online version is standard || could be facilitated by separated namespace for references |- | raw data|| often missing, especially if it does not fit on paper (like audio or video files) || example case [http://www.michaeleisen.org/blog/?p=192 here]|| can be provided in the same wiki environment || |- | supplementary materials|| often distributed into [http://www.nature.com/nature/journal/v437/n7062/suppinfo/nature04084.html multiple] [http://www.pnas.org/content/103/41/15212/suppl/DC1 files], not always integrable with paper ||discussions [http://network.nature.com/people/scurry/blog/2009/07/07/vital-supplements here] and [http://ff.im/5furO here] || not necessary - see above || |- | peer review||can be open, single-blind or double-blind; can be made available to the editors only or to a wider audience that could include the other reviewers, the authors, and the public || peer reviews are hard to track in their entirety, especially if non-published ||can be open, single-blind or double-blind; can be made available to the editors only or to a wider audience that could include the other reviewers, the authors, and the public || simpler to track |- | author contributions||need to be written down specifically (particularly detailed example [http://www.biomedcentral.com/1471-2342/9/8 here]) || || are always recorded; can possibly be automatically displayed (example in [http://www.wikigenes.org/ WikiGenes]) || |- | errata|| published separately (occasionally even [http://www.ncbi.nlm.nih.gov/pubmed/1508269?dopt=Abstract more than once] or as a [http://www.ncbi.nlm.nih.gov/pubmed/11501562 complete republication]), with no mention in the original paper version (another example [http://www.pnas.org/content/103/45/17064.1.full here])|| online versions frequently add [http://www.nature.com/nature/journal/v450/n7166/full/450044a.html a] [http://dx.doi.org/10.1371/journal.pone.0005373 note] about the updates but they are [http://www.nature.com/nchembio/journal/v5/n7/abs/nchembio0709-441.html rarely] incorporated into a corrected file that contains all of the information; non-text corrections further complicate the picture, as these files are often stored independently online and not reprinted (e.g. [http://www.nature.com/nature/journal/v449/n7163/fig_tab/449665a_F1.html here] or [http://dx.doi.org/10.1371/journal.pone.0010440 Fig. 1 in here]) || can be easily corrected in the original location || a note about the update can be added easily, too |- | retractions|| published separately, with no mention in the original paper version || online versions frequently (but [http://scienceblogs.com/pharyngula/2010/08/another_publisher_stonewalls_o.php#comment-2724834 not always]) add a note about the updates (possibly [http://www.virologyj.com/content/7/1/169/comments#424680 hidden in the comments]) but they are rarely incorporated into a corrected file that contains all of the information; [http://old.rintesting.com/node/653 "retractions at Wiley-Blackwell are now running at more than one a week"] || can be easily corrected in the original location || a note about the update can be added easily, too |- | scientific correspondence||[http://www.ncbi.nlm.nih.gov/pubmed/9310563?dopt=Abstract slow]; danger of misunderstandings due to ambiguous wording || ||quick; disambiguated hyperlinks to explanations of important concepts can reduce such friction || |- | access || often barred by subscription fees, generally with a delay after submission and/or peer review that may range from days to sometimes years || || open by default || immediate |- | reuse|| copyright usually retained by the publisher, with important restrictions of reuse || || CC or GFDL licenses are standard || |- | metadata|| [http://iphylo.blogspot.com/2010/05/why-we-need-wikis.html error-prone and hard to correct] || can be fixed in an easy, simple and transparent manner || || |- | outreach|| roughly proportional to access and usability || ||roughly proportional to access and usability || |- | impact|| || || || |- | applications|| || || || |- | teaching|| || || || |- | resource use|| || || || |- |} ==Examples of scholarly wikis== ''A number of scholarly wikis are also contained in [[w:List_of_online_encyclopedias|Wikipedia's list of online encyclopedias]].'' *https://wiki.sustainablejustcities.eu - Hosts resources for sustainable and just cities *[http://openwetware.org OpenWetWare] - Hosts biology 200+ lab web pages and protocols *[http://www.scholarpedia.org/ Scholarpedia] - invitation-only cross-disciplinary wiki with real names, ISSN and classical anonymous peer review process that leads to stable versions *[http://en.citizendium.org/ Citizendium] - cross-disciplinary wiki with real names and discipline-specific review process that leads to stable versions *[http://www.eoearth.org/ Encyclopedia of Earth] - focus on Earth sciences, real names, discipline-specific review process that leads to stable versions *[http://species-id.net/wiki/Main_Page Species-ID] - biodiversity information; data facilitating the identification of species on Earth *[http://groupprops.subwiki.org/ GroupPropsWiki] - on Group Theory *[http://www.wikisurgery.com/ WikiSurgery] - on surgery; spam-ridden *[http://www.biopython.org/wiki/Biopython Biopython] - Python tools for computational molecular biology *[http://prelive.tricki.org/ Tricky] - on mathematical problem-solving techniques *[http://wwww.wikieducator.org/ WikiEducator] - for teaching purposes *[http://wwww.wikigenes.org/ WikiGenes] - for genes, with authorship tracking of text bits *[http://michaelnielsen.org/polymath1/index.php?title=Main_Page The Polymath wiki] - highlights a series of collaborative contributions to a mathematical research question, ranging from its initial formulation to its solution in just a few weeks *[http://www.quantiki.org/wiki/index.php/Main_Page Quantiki] - on quantum information *[http://scherk.pbworks.com/ Quizzes] *[http://notable.math.ucdavis.edu/wiki/Main_Page Mathematics Jobs Wiki] *[http://www.sklogwiki.org/ SklogWiki] on the thermodynamics of simple liquids, complex fluids, and soft condensed matter. *[http://toxipedia.org/ Toxipedia] - about drugs and toxicity *[http://www.medpedia.com/ Medpedia] - about Health topics *[http://www.bioenergywiki.net/index.php/Main_Page BioenergyWiki] *[http://ecomedia.wikispaces.com/ non-print media in environmental discourse] *[http://www.neurolex.org/wiki/Main_Page NeuroLex] - a glossary of neuroscientific terms *[http://acawiki.org/Home AcaWiki] - for scientific journal clubs online *[http://www.neuronbank.org/ NeuronBank Wiki] - for the description of neuronal cell lines and circuitry *[http://neuro.imm.dtu.dk/wiki/Main_Page BredeWiki] - neuroscience *[http://www.subtiwiki.uni-goettingen.de/ SubtiWiki] - dedicated to Bacillus subtilis *[http://nmrwiki.org/ NMRWiki] - for Magnetic Resonance (focus on spectroscopy) *[http://www.wikipathways.org WikiPathways] - for metabolic pathways *[http://wikiindex.org/Category:Science wikiindex.org/Category:Science] *[http://biowikifarm.net/ BioWikiFarm] - a suite of wikis dedicated to biodiversity and related issues *[http://www.bioinformatics.org/wiki/BioWiki list of biowikis] ==Desirable features of future scholarly wikis== ''For context, see [http://friendfeed.com/science-2-0/4c011684/what-features-should-future-scholarly-wikis-or here].'' *Some system of peer review (basically, any wiki allows comments, annotations or formal reviews on talk pages of users or articles but these ratings should be featured more prominently; templates like those [http://en.citizendium.org/wiki/Template:Rpl/Doc visualizing article status] at Citizendium may help with that); this may be as simple as disallowing individuals to add information to Citizendium when the only available support is their own non-reviewed research published at OpenWetWare &mdash; the real name policy will minimize misuse<br> *Uploadability of all kinds of media that traditionally (if you can call a habit that barely is a decade old a tradition already) went along with paper-based publications as "supporting online information" (which would be easily integrated in an all-online non-printable article with no sharp space limitations). <br> *Stable versions for content that has undergone peer review (like the [http://en.citizendium.org/wiki/Category:Approved_Articles Approved Articles] at Citizendium, or the results of the double phase review model at the OA journal [http://www.atmospheric-chemistry-and-physics.net/ ACPD/ACP]), along with draft versions for anything else (including improvements to and updates of previous stable versions); like any non-protected page at the Wikipedias, these draft versions can serve as a playground, though a real-name policy would probably make it a more educational one<br> *Search engines that integrate or otherwise compare favourably with major scholarly search engines on the web (the already mentioned Google Scholar and PubMed as well as, say, the [http://biosearch.berkeley.edu/ BioText Search Engine] that searches Open Access text and images), also in terms of the [http://friendfeed.com/search?q=computer updating frequency].<br> *pan-disciplinary scope, with consistent disambiguation of specialist terms ([http://en.citizendium.org/wiki/Category:Disambiguation mainly] but [http://en.citizendium.org/wiki/CZ:List_of_words_with_multiple_uses not fully] achieved at Citizendium) *Separate [[w:Wikipedia:MediaWiki_namespace|namespaces]] for references (already in use at the Dispersive PDE Wiki and the [[w:fr:Aide:Espace_référence|French Wikipedia]], [http://en.citizendium.org/wiki/Special:PrefixIndex/CZ:Ref: in test] at Citizendium); as a side line, this would open up ways for new citation metrics, via the [http://en.citizendium.org/wiki/Special:WhatLinksHere/CZ:Ref:DOI:10.1016/j.tins.2008.08.010 What links here] function<br> *Separate namespaces for original research: Encyclopedic endeavours need expert input. This is most likely to be achievable if the encyclopedic activites can be integrated with the experts' workflow, e.g. via platforms like OpenWetWare. <br> *Attributability of contributions (automatically realized, though not in the traditional scholarly way, in any wiki with a real name policy like [http://en.citizendium.org/wiki/CZ:Why_Citizendium%3F#Real_names_are_better that at Citizendium], via the [http://en.citizendium.org/wiki/Special:Contributions/Daniel_Mietchen User contributions] function; special arrangements exist at Scholarpedia and WikiGenes; OpenWetWare does allow nicknames but real names prevail; the Wikiversities have basically the same user name policy as the Wikipedias) *Easy download of selected sets of pages for local archiving or analysis.<br> *Licenses that allow unrestricted reuse and derivative work if the original source is properly acknowledged (typically [http://openwetware.org/wiki/Copyright CC-by-SA or the older GFDL], both of which have been made [http://creativecommons.org/weblog/entry/14647 compatible now]) *Resource-effective design (see also discussions on the energy use [http://dx.doi.org/10.1088/1748-9326/3/3/034008 of the internet] and [http://ecopreneurist.com/2008/12/29/greening-your-business-website/ individual websites]). This overview may also help in working out an ecological footprint scheme applicable to research, as described [http://ways.org/en/2008/jun/03/%5Bhour%5D%5Bmin%5D/%5Buser%5D/on_impact_research previously]. *integration with the non-scholarly world (certainly achieved in the [[w:Humour_(disambiguation)|Wikipedias]] and [http://en.citizendium.org/wiki/Led_Zeppelin Citizendium]), particularly with students (cf. the [http://en.citizendium.org/wiki/CZ:Eduzendium Eduzendium initiative] at Citizendium) and non-English contents<br> *Automation of the formatting, as already common in non-wiki environments, e.g. with [http://www.atmospheric-chemistry-and-physics.net/submission/latex_instructions.html LaTeX templates], for which [http://www.scribtex.com/ collaborative editing environments] exist too. None of the wikis we know comes close to that, albeit templates are heavily used at the various [[w:Wikipedia:Template_messages|Wikipedias]] and, to a lesser extent but in a more consistent manner, at [http://en.citizendium.org/wiki/CZ:Templates Citizendium]; they seem to be rather rarely used on smaller or more specialized wikis. The same applies to references, though [http://toolserver.org/~diberri/cgi-bin/templatefiller/?type=&id= automated wikification] has already progressed considerably here, despite the lack of wiki export functions at publisher's sites (or of suitable [http://en.wikipedia.org/w/index.php?title=XML&oldid=259659653 XML]-to-wiki converters for those who provide XML) <br> *Integration with mind maps (which structure knowledge) and databases (which harbour bits of knowledge that do not make much sense without a broader context).<br> *Distributed version control, e.g. via [http://github.com/blog/699-making-github-more-open-git-backed-wikis git] ([http://p2pfoundation.net/Open_Science_differs_from_Open_Source_Software Warning: open science is not open source]) ==Alternatives to wikis== *Basically anything that is more WYSIWYG (e.g. Open Office, MS Word), more real time (e.g. Etherpad/ Google Doc/ Google <s>Wave</s> Sites / Google Knol) or more integrated with references or other non-text elements of publishing, or more semantic. *[http://www.eol.org/ Encyclopedia of Life]: focussing on species descriptions, it is not a wiki. EoL is more similar to a news aggregator, using semantic meshup pulled from associated content sites ==See also== *[[Educational wikis]] *[[Open Scientist]] *[[Wikiversity:Publishing_original_research#List_of_wiki_journals|List of wiki journals]] *[[Collaborative research on Wikiversity]] ==External links== *[http://www.ipodvideosconverter.com/ Ipod Video Converter] *Related threads on Friendfeed: [http://friendfeed.com/e/dd0f80f0-5973-4e78-acc0-e0d7510b573f/What-s-the-most-successful-science-wiki/ What's the most successful science wiki?] and [http://friendfeed.com/jcbradley/e6896d56/scholarly-publishing-what-would-do-over-look Scholarly publishing: what would a do-over look like?] as well as [http://friendfeed.com/cameronneylon/aa693875/implementing-publication-as-aggregation Implementing the “Publication as Aggregation”] and [http://friendfeed.com/cameronneylon/f93025ec/distriwiki-proposal DistriWiki: A Proposal] *[http://blog.openwetware.org/scienceintheopen/2009/03/03/what-is-the-cost-of-peer-review-can-we-afford-not-to-have-high-impact-journals/ What is the cost of peer review? Can we afford (not to have) high impact journals?] - a blog post on economic aspects of the scientific communication cycle :Data for the costs (though no hint on their provenance) are in [http://www.rin.ac.uk/files/Daniel_Hulls_What_cost_11Dec08.pdf this presentation by Daniel Hull (pdf)] *[http://adamg83.wordpress.com/2008/11/05/heres-a-great-idea-that-apparently-doesnt-work/ Here’s a Great Idea (that apparently doesn’t work)] - a blog post on the apparent lack of (cross-disciplinary) scholarly wikis *[[meta:User:Yaroslav_Blanter/Temp17|Discussion of the role of experts in Wikimedia projects]] *[http://www.sklogwiki.org/SklogWiki/index.php/Wiki Wiki entry at SklogWiki] - a list of resources (mainly blog posts) relating to the use of wikis in research *[http://blog.wikimedia.org/2009/04/27/scholarly-community-gives-feedback-regarding-wikipedia/ A survey of scientists on their attitude towards Wikipedia and possible integration of it with Open Access scientific publications] [[category:Research]] [[Category:e-Learning]] [[Category:Wikis]] [[Category:Social sciences]] sinvns1w6e9mtro0h4uo49k40ngrlf6 0 96387 2835259 2835115 2026-10-01T02:45:36Z Jtneill 10242 /* Marking rubric */ 2835259 wikitext text/x-wiki {{title|Book chapter — Guidelines}} <div style="text-align: center;">''Collaborative online book chapter authoring'' <!-- ---------------------------------- ---> <!-- Count down --> <!-- ---------------------------------- ---><!-- {{countdown |year = 2026 |month = 10 |day = 12 |hour = 0 |event = this assessment is due }} --><!-- {{Motivation and emotion/Assessment/In development}} --> {{/Contents/}}</div> {{TOCright}} ==Overview== * Weight: 50% * Due {{/Due}} * Tasks ** Author an online [[Motivation and emotion/Book|book chapter]] (up to 4,000 words) that explains key psychological theory and research about a unique, specific motivation or emotion topic. ** Develop the chapter by building on the [[Motivation and emotion/Assessment/Topic|topic development]] plan and addressing feedback. ** Contribute to the development of other book chapters (social contribution). * Follow the [[#Instructions|instructions]] and address the [[#Marking criteria|marking criteria]]. ==Purpose== The purpose of the book chapter is to explain and critically evaluate what psychological science says about a specific motivation or emotion topic, and to demonstrate how this knowledge can be applied to understanding and improving human behaviour in everyday life. ==Marking and feedback== * Submissions will be marked according to the [[#Marking criteria|marking criteria]] and [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60/edit?usp=sharing marking rubric]. * Marks will be provided via {{Motivation and emotion/Canvas}} when the university releases unit results (see [https://www.canberra.edu.au/about-uc/key-dates/ Key dates]). * Up to 5 bonus marks will be awarded in exceptional circumstances where social contributions are above and beyond those required for HD-level (see [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60 rubric]). * Written feedback about how well the chapter addresses the marking criteria will be available via the topic's Wikiversity discussion page. * Follow up with the [[Motivation and emotion/About/Staff|unit convener]] if you have any questions. ==Extensions and late submissions== * Apply for extension using the unit's online Extension Application Form (see {{Motivation and emotion/Canvas}}) with appropriate documentary evidence. * Submissions will be accepted up to 3 days late (-10% per day). * If you don't submit this assessment it is unlikely that you will pass the unit. ==Learning outcomes== How the unit's [[Motivation and emotion/About/Learning outcomes|learning outcomes]] are addressed by this assessment exercise: {| border=1 cellpadding=5 cellspacing="0" background:transparent style="width:90%; margin: auto; vertical-align:top;" |- | style="width:40%;" | '''Learning outcome''' | style="width:60%;" | '''Assessment task''' |- | style="vertical-align:top;" | Integrate theories and current research towards explaining the role of motivation and emotions in human behaviour. | style="vertical-align:top;" | Use the most relevant theories and peer-reviewed research to explain a specific motivation or emotion topic. |- | style="vertical-align:top;" | Critically apply knowledge of motivation or emotion to an indepth understanding of a specific topic in this field. | style="vertical-align:top;" | Explain how psychological science can be applied to a specific motivation or emotion topic. Use figures, examples, and/or other interactive learning features to illustrate how this knowledge can apply to understanding human behaviour in everyday life. |} ==Graduate attributes== How the unit's [[Motivation and emotion/About/Graduate attributes|graduate attributes]] are addressed by this assessment exercise: {| border=1 cellpadding=5 cellspacing="0" background:transparent style="width:90%; margin: auto;" |- ! style="width:20%;" | Category ! style="width:20%;" | Graduate attribute ! style="width:60%;" | Assessment task |- | rowspan="4" style="vertical-align:top;" | '''Be professional''' | style="vertical-align:top;" | Communicate effectively | style="vertical-align:top;" | Review scholarly knowledge in an open, online environment and address feedback. |- | style="vertical-align:top;" | Display initiative and drive | style="vertical-align:top;" | Produce an online book chapter about a novel motivation or emotion topic. |- | style="vertical-align:top;" | Up-to-date knowledge and skills | style="vertical-align:top;" | Utilise the most relevant psychological theory and research to address a practical question. |- | style="vertical-align:top;" | Solve problems via thinking | style="vertical-align:top;" | Use critical thinking to explain how psychological science can address real-world problems. |- | rowspan="3" style="vertical-align:top;" | '''Be a global citizen''' | style="vertical-align:top;" | Informed and balanced | style="vertical-align:top;" | Provide a balanced, critical chapter which is accessible to a lay audience. |- | style="vertical-align:top;" | Communicate diversely | style="vertical-align:top;" | Collaborate with peers to communicate knowledge openly with a global audience. |- | style="vertical-align:top;" | Creative use of technology | style="vertical-align:top;" | Learn how to collaborate using wiki technology. |- | rowspan="2" style="vertical-align:top;" | '''Be a lifelong learner''' | style="vertical-align:top;" | Engage in new ideas | style="vertical-align:top;" | Engage in a collaborative learning culture by incorporating feedback and suggestions. |- | style="vertical-align:top;" | Evaluate and adopt new technology | style="vertical-align:top;" | Experience project work in a collaborative, online editing environment. |} ==Instructions== The book chapter should communicate your understanding of the topic based on the best available psychological theory and research. Explain and apply the most relevant evidence in a clear, engaging, and accessible way. The aim is to demonstrate your ability to synthesise and critically evaluate psychological science in order to understand and respond to a specific motivation or emotion phenomenon. The following instructions should be used to guide the development of the book chapter. ===Theme=== * Chapters should fit the book theme which is "understanding and improving our motivational and emotional lives using psychological science" ===Audience=== * The target audience is a general (non-topic-expert) reader interested in personal growth and development based on knowledge in psychological science (theory and research). This is a [[w:science communication|science communication]] exercise. ===Wikiversity=== * Present the chapter as a single page on the [[Main Page|English Wikiversity]] website. A link to the chapter should appear in the [[Motivation and emotion/Book|table of contents]] along with the lead author's Wikiversity user name ===Topic=== * The title and sub-title must be approved by the [[Motivation and emotion/About/Staff|unit convener]] ===Collaboration and feedback=== * Chapters should be independently developed and written primarily by the lead author, but collaboration is strongly encouraged (e.g., by incorporating useful edits and feedback from others) * [[Motivation and emotion/Assessment/Using generative AI|Generative AI]] may be used with appropriate acknowledgement * Lead authors are encouraged to seek feedback about the chapter during the drafting process (e.g., start a {{Motivation and emotion/Canvas}} discussion thread<!-- (use the chapter title and subtitle in the subject line and include a clickable hyperlink to the chapter in the message)-->) * Feedback is usually best placed on the chapter's wiki discussion page * Feedback on the [[Motivation and emotion/Assessment/Topic|topic development]] (chapter plan) will be provided by the [[Motivation and emotion/About/Staff|unit convener]] ===Length (word count)=== {{Anchor|Wordcount}}{{Anchor|Word count}} * There is no minimum length * Maximum 4,000 words ** There is no additional 10% allowance ** Words beyond the maximum will not be considered for marking purposes ** Count everything from top to bottom of the editable page (in view mode, not edit mode): *** Include the title, subtitle, headings, text, tables, figures, references, see also, and external links; don't include menu text across the top and down the left, or categories at the bottom ** How to count: *** Google Chrome extension: [https://chromewebstore.google.com/detail/word-counter/cbjddaobmdfhbfgdgjocbhklpmclcboe Word Counter]. This extension is probably the easiest reliable method for counting words on a Wikiversity page. However, UC recently started blocking this extension on UC devices. *** Website: Paste the URL into [https://hsuper.tools/web-page-word-counter Webpage Word Counter] (it overcounts by ~100 words because it includes menus etc.) *** Word processor: Cut and paste into a word processor (i.e., copy starting at title and finishing with the last external link) * If the chapter exceeds the maximum word count, see [[/Word count|these suggestions]] for strategies to reduce the length while retaining the key content. ===Submission=== * Submit the chapter URL (website address), your Wikiversity user name, and a PDF of the chapter via {{Motivation and emotion/Canvas}} ==Marking criteria== [[File:Balanced scales.svg|right|125px]] Book chapters will be marked against the following criteria. ===Overview (5%)=== * Scenario: Provide an engaging scenario or case study in a feature box, with an illustrative figure * Problem statement: Easy to read and understand outline of the key concepts and explanation of practical/real-world problem to be solved * Focus questions: Establish [[/Focus questions|focus questions]] which align with the sub-title and subsequent heading structure ===Theory (20%)=== * Clearly explain the theoretical framework for understanding the topic * Select the most relevant psychological theories/models that apply to the problem. Depending on the topic, this may involve focusing on a single theory or comparing and contrasting two or more theories. * Use at least the best dozen or so peer-reviewed theory references about the topic (e.g., see [[Motivation and emotion/Journals|list of motivation and emotion journals]]) * Clearly explain and apply the theory(ies) * Include illustrative examples, such as case studies * Demonstrate a critical perspective ===Research (25%)=== * Clearly explain how key, peer-reviewed research findings apply to the problem * Use at least the best dozen or so peer-reviewed research references about the topic (e.g., see [[Motivation and emotion/Journals|list of motivation and emotion journals]]) * Include relevant major reviews (such as systematic reviews and meta-analyses) * [[w:Critical thinking|Critical analyse]] the key research findings, including limitations and implications ===Integration (10%)=== * Integrate discussion of theory and review of relevant research * Use research to critically inform interpretation and application of the theory(ies) ===Conclusion (5%)=== * Clear and concise communication of key points and take-home messages * Aligned with the subtitle and focus questions, with implications for the [[Motivation and emotion/Book/Theme|book theme]] ===Style (20%)=== * Overall ** Present and illustrate the problem and knowledge in an interesting way, using a logical structure, clear layout, correct spelling and grammar, and [[APA style]] ** [[/Readability|Readable]] for a layperson interested in psychological science ** Address the [[#Theme|book theme]] by providing practical, academically sound, self-improvement information ** Address an international audience (i.e., avoid an overly local or national perspective) ** Use default wiki style for paragraph alignment, font colour, type, and size, and heading styles ** Use Australian spelling (e.g., hypothesise, behaviour, fulfilment) rather than American spelling (e.g., hypothesize, behavior, fulfillment) ** Correct grammar (e.g., see [[/Writing tips|writing tips]]) * Structure ** Use a logical heading structure that aligns with the focus questions ** Use [https://www.masterclass.com/articles/sentence-case-explained sentence casing] throughout, including for headings and sub-headings ** Use the default heading style (e.g., do not add italics and/or bold) ** Sub-headings are optional *** Avoid having sections with a single sub-heading — each section should contain 0 or 2+ sub-headings. *** If sub-headings are used, provides at least 1 introductory paragraph before branching into sub-sections. * Sentences ** [[w:Narration#Narrative point of view|Narrative point of view]][https://www.grammarly.com/blog/first-second-and-third-person/]: In the main text, use [[w:Narration#Third-person|3rd person perspective]] (e.g., "it", "they"). Where [[w:Aside|aside]]s are used, such as examples, case studies, and feature boxes, [[w:First-person narrative|1st person perspective]] (e.g., "I" and "we") and/or [[w:Narration#Second-person|2nd person perspective]] (e.g., "you") can work well. * Paragraphs ** A well-constructed paragraph is generally 3 to 5 sentences (opening sentence, body sentences, and a concluding/linking sentence). Avoid one-sentence paragraphs and overly long paragraphs. ** Paragraphs flow logically * Use APA style (as much as reasonably possible), paying particular attention to: ** citations ** references (especially capitalisation, italicisation, and providing hyperlinked dois) ** table and figure captions ** quotes (include page numbers) * Citations ** Claims need citations using APA style or [[w:Wikipedia:Citing_sources|wiki citation style]]. Only use one style throughout the chapter — don't mix and match. For most psychology students, APA style will be the choice. ** Maximum of 3 citations per point (i.e., avoid 4 or more citations together). * References ** List all cited academic references in APA style or [[w:Wikipedia:Citing_sources|wiki citation style]]. Only use one style. ** Non-academic sources are not used in references. They can be included in the external links section. ===Learning features (5%)=== * Embed interactive learning features such as scenarios/case studies/examples, feature boxes, figures, quizzes, links to relevant Wikipedia and Wikipedia pages, as well as links to key resources via the "See also" and "External links" sections * Case studies ** Include 1 or more examples, scenarios, or case studies ** They can be true (if so, include citations) or fictional ** Use these examples to enhance understanding of theory, research, focus questions, and/or take-home messages ** Present in a feature box and include a figure ** Consider using a "progressive case study" (i.e., a case study presented in separate parts which describe, for example, the problem, attempt at change, and resolution/outcomes). ** Examples of chapters which make effective use of case studies: *** [[Motivation and emotion/Book/2019/Emotional abuse|emotional abuse]] (2019) *** [[Motivation and emotion/Book/2019/Food and fear|food and fear]] (2019) *** [[Motivation and emotion/Book/2019/Opioid system and human emotion|opioid system and human emotion]] (2019) *** [[Motivation and emotion/Book/2019/Social support and emotion|social support and emotion]] (2019) * [[Motivation and emotion/Wikiversity/Feature box|Feature boxes]] ** Use to highlight key information, but avoid overuse ** There are various ways of creating coloured boxes, but the [[Template:RoundBoxTop|RoundBox]] template is a good option. * [[Motivation and emotion/Wikiversity/Figures|Figures]] ** Include relevant, accompanying figures (e.g., photos, drawings, diagrams) to facilitate readers' understanding of the concepts ** Figures are accompanied by explanatory captions and be cited at least once in the main text ** For more information, see [[Motivation and emotion/Assessment/Chapter/Figures|How to use figures]]). * [[Help:Links|Links]] ** In-text (embedded) links: Key words and concepts are [[Making links|linked]] to Wikipedia articles and/or related book chapters. Provide in-text wiki links the ''first time'' that key concepts are mentioned. For example: *** [[w:Emotion|emotion]] involves physiological, subjective feeling, motivational, and socially expressive aspects. The syntax for creating this link is <nowiki>[[w:Emotion|emotion]]</nowiki>). It is also possible to link to a section on this same page e.g., &lt;nowiki&gt;[[#Overview|Overview]]&lt;nowiki&gt; will link to the Overview section. *** [[Motivation and emotion/Book/2021/Fitspiration and body image|This chapter]] provides an excellent example of embedded links to Wikiversity pages. ** See also *** Provide interwiki links to key related Wikiversity book chapters and/or Wikipedia articles *** Include source in parentheses ** External links *** Provide at least three links to high quality, relevant external resources *** Include author and/or source in parentheses ** Published academic sources belong in References * [[Motivation and emotion/Wikiversity/Tables|Tables]] ** Use accompanying tables to help organise information and communicate concepts to readers ** Tables are accompanied by explanatory APA style captions and are cited in the body text * [[Help:Quiz|Quizzes]] ** Quiz questions or reflection questions encourage reader engagement ** Focus on core concepts (esp. take-home messages) rather than trivia ** Consider incorporating throughout the chapter {{anchor|Socialcontribution}} {{anchor|Social contribution}} ===Social contribution (10%)=== * '''Actions''': Logged contributions which enhance the quality of other book chapters. Useful actions include: ** '''Edits''': Direct edits which improve past or current chapters (e.g., fix errors, enhance clarity) or flag potential improvements by adding [[Template:Clarification templates|clarification templates]]. [[/Search for chapters to improve|Search for chapters to improve]]. ** '''Comments''': Feedback provided on book chapter [[Help:Talk page|talk page]]s ** '''Media uploads''': Upload free-to-use educational images to [[commons:|Wikimedia Commons]] ** '''{{Motivation and emotion/Canvas}} discussion posts''' * '''Evidence''': ** Provide a [[mw:Help:Lists|numbered list]] with summaries of contributions on your [[Help:User page|Wikiversity user page]], and '''direct links''' that show each change or contribution.<!-- To receive credit, contributions must be publicly logged (i.e., log in to Wikiversity so that the edit is recorded with your user name and time-stamp). Summarise each edit on your user page (in a section called "Social contributions") --> ** More info: [[/Summarising social contributions|summarising social contributions]] * '''Marking''' ** Marking of social contributions will be based on a combination of: *** '''Quantity''': **** Breadth: number of chapters contributed to **** Channels: range of communication channels used *** '''Quality''': **** Depth/extent/thoroughness **** Insightfulness **** Practical value *** '''Timeliness''' — there is generally: **** Greater value in earlier contributions **** Lesser value in last-minute contributions ** Marks will be allocated to each clearly evidenced contribution as follows: *** Minor <= 0.25 *** Moderate 0.50 *** Major 1.00 *** Very significant > 1.00 * '''Bonus marks''' ** Up to 5 bonus marks (out of 100 for the book chapter) will be awarded in exceptional circumstances where social contributions are above and beyond those required for HD-level. ** Approximately 5% of students receive social contribution bonus marks. ** This could include extensive copyediting of multiple chapters and/or regular feedback or support on multiple chapter discussion pages. It may also involve substantial activity on the UCLearn discussion forum. ==Marking rubric== {{Notice|1=[https://docs.google.com/document/d/1yQd1-IekznJNLwhef-yEBaxKtRR6dAVESWXoTa-ti3c/edit?usp=sharing Marking rubric]}} ==Examples== Examples of high quality [[Motivation and emotion/Book|motivation and emotion book chapters]]: * [[Motivation and emotion/Book/2025/AI use, cognitive load, and motivation|AI use, cognitive load, and motivation]] - How does generative AI reduce cognitive effort, and what are the motivational consequences? (2025) * [[Motivation and emotion/Book/2025/Autonomy and intrinsic motivation in self-determination theory|Autonomy and intrinsic motivation in self-determination theory]]: How does autonomy influence intrinsic motivation according to SDT? (2025) * [[Motivation and emotion/Book/2022/Disappointment|Disappointment]]: What is disappointment, what causes it, and how can it be managed? (2022) * [[Motivation and emotion/Book/2016/Illicit drug taking at music festivals|Illicit drug taking at music festivals]]: What motivates young people to take illicit drugs at music festivals? (2016) * [[Motivation and emotion/Book/2019/Organisational change motivation|Organisational change motivation]]: How can leaders build a culture of agility, adaptability, and resilience to deal with a constantly changing workplace? (2019) * [[Motivation and emotion/Book/2019/Phobias|Phobias]]: What are phobias and how can they be dealt with? (2019) * [[Motivation and emotion/Book/2025/Transactive goal dynamics theory and motivation|Transactive goal dynamics theory and motivation]]: What is transactive goal dynamics theory and how does it impact motivation? (2025) Note that as of 2025, chapters no longer include multimedia presentations. For more examples, see the {{Motivation and emotion/Book/High}}s in the [[Motivation and emotion/Book|lists of previous book chapters]]<!-- and the [[:Category:Motivation and emotion/Book/2022/Top|top chapters of 2022]] -->. ==Licensing== Contributions to Wikiversity are made under a [http://creativecommons.org/licenses/by-sa/4.0/ Creative Commons 4.0 Share-alike] (CC-BY-SA 4.0) license which is irrevocable. This license gives permission for others to edit and re-use, with appropriate acknowledgement. For more information, see the [[wmf:Terms of use|Wikimedia Foundation's Terms of use]]. If you do not wish to contribute your work under this license, discuss [[Motivation and emotion/Assessment/Alternative|alternative assessment options]] with the unit convener. ==See also== * [[/FAQ/]] * [[Motivation and emotion/Book|Previous chapters]] * Marking and feedback ** [[Motivation and emotion/Assessment/Chapter/Feedback|General feedback]] ** [[Template:MEBF|Feedback template]] ** [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60/edit?usp=sharing Marking rubric] * [[#Socialcontribution|Social contributions]] ** [[/Search for chapters to improve/]] ** [[/Summarising social contributions/]] * [[Motivation and emotion/Tutorials|Tutorials]] <!-- ** [[Motivation and emotion/Tutorials/Topic selection|Tutorial 01: Topic selection]] --> ** [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2: Wiki editing]] ** [[Motivation and emotion/Tutorials/Functionalist theory and self-tracking#Google Scholar|Tutorial 5: Google Scholar]] ** [[Motivation and emotion/Tutorials/Measuring emotion#Topic development feedback|Tutorial 8: Topic development feedback]] * Wikiversity ** [[/Feature boxes/]] ** [[/Figures/]] ** [[How to find free-to-use images|Find free images]] ** [[/Tables/]] * [[/Writing tips/]] ** [[/How to handle a lack of information/|Handling a lack of information]] ** [[/Readability|Readability]] ** [[Motivation and emotion/Assessment/Using generative AI|Using generative AI]] ** [[/Word count|Word count]] {{Motivation and emotion/Assessment/Navigation}} [[Category:Motivation and emotion/Assessment/Chapter| ]] [[Category:Motivation and emotion guidelines]] syrcx6mkvfo3u8mtjcrbot6l3ozvek9 0 139384 2835176 2835052 2026-09-30T12:54:49Z Young1lim 21186 /* Adder */ 2835176 wikitext text/x-wiki == Adder == * Binary Adder Architecture Exploration ( [[Media:Adder.20131113.pdf|pdf]] ) {| class="wikitable" |- ! Adder type !! Overview !! Analysis !! VHDL Level Design !! CMOS Level Design |- | '''1. Ripple Carry Adder''' || [[Media:VLSI.Arith.1A.RCA.20250522.pdf|A]]|| || [[Media:Adder.rca.20140313.pdf|pdf]] || [[Media:VLSI.Arith.1D.RCA.CMOS.20211108.pdf|pdf]] |- | '''2. Carry Lookahead Adder''' || [[Media:VLSI.Arith.2A.CLA.20260722.pdf|A]], [[Media:VLSI.Arith.2B.CLA.20260929.pdf|B]], [[Media:VLSI.Arith.2C.CLA.20260929.pdf|C]], [[Media:VLSI.Arith.2D.CLA.20260720.pdf|D]] || || [[Media:Adder.cla.20140313.pdf|pdf]]|| |- | '''3. Carry Save Adder''' || [[Media:VLSI.Arith.1.A.CSave.20151209.pdf|A]]|| || || |- || '''4. Carry Select Adder''' || [[Media:VLSI.Arith.1.A.CSelA.20191002.pdf|A]]|| || || |- || '''5. Carry Skip Adder''' || [[Media:VLSI.Arith.5A.CSkip.20250405.pdf|A]]|| || || [[Media:VLSI.Arith.5D.CSkip.CMOS.20211108.pdf|pdf]] |- || '''6. Carry Chain Adder''' || [[Media:VLSI.Arith.6A.CCA.20211109.pdf|A]]|| || [[Media:VLSI.Arith.6C.CCA.VHDL.20211109.pdf|pdf]], [[Media:Adder.cca.20140313.pdf|pdf]] || [[Media:VLSI.Arith.6D.CCA.CMOS.20211109.pdf|pdf]] |- || '''7. Kogge-Stone Adder''' || [[Media:VLSI.Arith.1.A.KSA.20140315.pdf|A]]|| || [[Media:Adder.ksa.20140409.pdf|pdf]]|| |- || '''8. Prefix Adder''' || [[Media:VLSI.Arith.1.A.PFA.20140314.pdf|A]]|| || || |- || '''9.1 Variable Block Adder''' || [[Media:VLSI.Arith.1A.VBA.20221110.pdf|A]], [[Media:VLSI.Arith.1B.VBA.20230911.pdf|B]], [[Media:VLSI.Arith.1C.VBA.20240622.pdf|C]], [[Media:VLSI.Arith.1C.VBA.20250218.pdf|D]]|| || || |- || '''9.2 Multi-Level Variable Block Adder''' || [[Media:VLSI.Arith.1.A.VBA-Multi.20221031.pdf|A]]|| || || |} </br> === Adder Architectures Suitable for FPGA === * FPGA Carry-Chain Adder ([[Media:VLSI.Arith.1.A.FPGA-CCA.20210421.pdf|pdf]]) * FPGA Carry Select Adder ([[Media:VLSI.Arith.1.B.FPGA-CarrySelect.20210522.pdf|pdf]]) * FPGA Variable Block Adder ([[Media:VLSI.Arith.1.C.FPGA-VariableBlock.20220125.pdf|pdf]]) * FPGA Carry Lookahead Adder ([[Media:VLSI.Arith.1.D.FPGA-CLookahead.20210304.pdf|pdf]]) * Carry-Skip Adder </br> == Barrel Shifter == * Barrel Shifter Architecture Exploration ([[Media:Bshift.20131105.pdf|bshfit.vhdl]], [[Media:Bshift.makefile.20131109.pdf|bshfit.makefile]]) </br> '''Mux Based Barrel Shifter''' * Analysis ([[Media:Arith.BShfiter.20151207.pdf|pdf]]) * Implementation </br> == Multiplier == === Array Multipliers === * Analysis ([[Media:VLSI.Arith.1.A.Mult.20151209.pdf|pdf]]) </br> === Tree Mulltipliers === * Lattice Multiplication ([[Media:VLSI.Arith.LatticeMult.20170204.pdf|pdf]]) * Wallace Tree ([[Media:VLSI.Arith.WallaceTree.20170204.pdf|pdf]]) * Dadda Tree ([[Media:VLSI.Arith.DaddaTree.20170701.pdf|pdf]]) </br> === Booth Multipliers === * [[Media:RNS4.BoothEncode.20161005.pdf|Booth Encoding Note]] * Booth Multiplier Note ([[Media:BoothMult.20160929.pdf|H1.pdf]]) </br> == Divider == * Binary Divider ([[Media:VLSI.Arith.1.A.Divider.20131217.pdf|pdf]])</br> </br> </br> go to [ [[Electrical_%26_Computer_Engineering_Studies]] ] [[Category:Digital Circuit Design]] [[Category:FPGA]] opmjvuwvdp8jyzldl93075b6am7ghox 2835321 2835176 2026-10-01T10:17:49Z Young1lim 21186 /* Adder */ 2835321 wikitext text/x-wiki == Adder == * Binary Adder Architecture Exploration ( [[Media:Adder.20131113.pdf|pdf]] ) {| class="wikitable" |- ! Adder type !! Overview !! Analysis !! VHDL Level Design !! CMOS Level Design |- | '''1. Ripple Carry Adder''' || [[Media:VLSI.Arith.1A.RCA.20250522.pdf|A]]|| || [[Media:Adder.rca.20140313.pdf|pdf]] || [[Media:VLSI.Arith.1D.RCA.CMOS.20211108.pdf|pdf]] |- | '''2. Carry Lookahead Adder''' || [[Media:VLSI.Arith.2A.CLA.20260722.pdf|A]], [[Media:VLSI.Arith.2B.CLA.20260930.pdf|B]], [[Media:VLSI.Arith.2C.CLA.20260930.pdf|C]], [[Media:VLSI.Arith.2D.CLA.20260720.pdf|D]] || || [[Media:Adder.cla.20140313.pdf|pdf]]|| |- | '''3. Carry Save Adder''' || [[Media:VLSI.Arith.1.A.CSave.20151209.pdf|A]]|| || || |- || '''4. Carry Select Adder''' || [[Media:VLSI.Arith.1.A.CSelA.20191002.pdf|A]]|| || || |- || '''5. Carry Skip Adder''' || [[Media:VLSI.Arith.5A.CSkip.20250405.pdf|A]]|| || || [[Media:VLSI.Arith.5D.CSkip.CMOS.20211108.pdf|pdf]] |- || '''6. Carry Chain Adder''' || [[Media:VLSI.Arith.6A.CCA.20211109.pdf|A]]|| || [[Media:VLSI.Arith.6C.CCA.VHDL.20211109.pdf|pdf]], [[Media:Adder.cca.20140313.pdf|pdf]] || [[Media:VLSI.Arith.6D.CCA.CMOS.20211109.pdf|pdf]] |- || '''7. Kogge-Stone Adder''' || [[Media:VLSI.Arith.1.A.KSA.20140315.pdf|A]]|| || [[Media:Adder.ksa.20140409.pdf|pdf]]|| |- || '''8. Prefix Adder''' || [[Media:VLSI.Arith.1.A.PFA.20140314.pdf|A]]|| || || |- || '''9.1 Variable Block Adder''' || [[Media:VLSI.Arith.1A.VBA.20221110.pdf|A]], [[Media:VLSI.Arith.1B.VBA.20230911.pdf|B]], [[Media:VLSI.Arith.1C.VBA.20240622.pdf|C]], [[Media:VLSI.Arith.1C.VBA.20250218.pdf|D]]|| || || |- || '''9.2 Multi-Level Variable Block Adder''' || [[Media:VLSI.Arith.1.A.VBA-Multi.20221031.pdf|A]]|| || || |} </br> === Adder Architectures Suitable for FPGA === * FPGA Carry-Chain Adder ([[Media:VLSI.Arith.1.A.FPGA-CCA.20210421.pdf|pdf]]) * FPGA Carry Select Adder ([[Media:VLSI.Arith.1.B.FPGA-CarrySelect.20210522.pdf|pdf]]) * FPGA Variable Block Adder ([[Media:VLSI.Arith.1.C.FPGA-VariableBlock.20220125.pdf|pdf]]) * FPGA Carry Lookahead Adder ([[Media:VLSI.Arith.1.D.FPGA-CLookahead.20210304.pdf|pdf]]) * Carry-Skip Adder </br> == Barrel Shifter == * Barrel Shifter Architecture Exploration ([[Media:Bshift.20131105.pdf|bshfit.vhdl]], [[Media:Bshift.makefile.20131109.pdf|bshfit.makefile]]) </br> '''Mux Based Barrel Shifter''' * Analysis ([[Media:Arith.BShfiter.20151207.pdf|pdf]]) * Implementation </br> == Multiplier == === Array Multipliers === * Analysis ([[Media:VLSI.Arith.1.A.Mult.20151209.pdf|pdf]]) </br> === Tree Mulltipliers === * Lattice Multiplication ([[Media:VLSI.Arith.LatticeMult.20170204.pdf|pdf]]) * Wallace Tree ([[Media:VLSI.Arith.WallaceTree.20170204.pdf|pdf]]) * Dadda Tree ([[Media:VLSI.Arith.DaddaTree.20170701.pdf|pdf]]) </br> === Booth Multipliers === * [[Media:RNS4.BoothEncode.20161005.pdf|Booth Encoding Note]] * Booth Multiplier Note ([[Media:BoothMult.20160929.pdf|H1.pdf]]) </br> == Divider == * Binary Divider ([[Media:VLSI.Arith.1.A.Divider.20131217.pdf|pdf]])</br> </br> </br> go to [ [[Electrical_%26_Computer_Engineering_Studies]] ] [[Category:Digital Circuit Design]] [[Category:FPGA]] 1jl6ymlg0jqg7heojvs3m8bap8ofjk5 2835323 2835321 2026-10-01T10:19:16Z Young1lim 21186 /* Adder */ 2835323 wikitext text/x-wiki == Adder == * Binary Adder Architecture Exploration ( [[Media:Adder.20131113.pdf|pdf]] ) {| class="wikitable" |- ! Adder type !! Overview !! Analysis !! VHDL Level Design !! CMOS Level Design |- | '''1. Ripple Carry Adder''' || [[Media:VLSI.Arith.1A.RCA.20250522.pdf|A]]|| || [[Media:Adder.rca.20140313.pdf|pdf]] || [[Media:VLSI.Arith.1D.RCA.CMOS.20211108.pdf|pdf]] |- | '''2. Carry Lookahead Adder''' || [[Media:VLSI.Arith.2A.CLA.20260722.pdf|A]], [[Media:VLSI.Arith.2B.CLA.20261001.pdf|B]], [[Media:VLSI.Arith.2C.CLA.20260930.pdf|C]], [[Media:VLSI.Arith.2D.CLA.20260720.pdf|D]] || || [[Media:Adder.cla.20140313.pdf|pdf]]|| |- | '''3. Carry Save Adder''' || [[Media:VLSI.Arith.1.A.CSave.20151209.pdf|A]]|| || || |- || '''4. Carry Select Adder''' || [[Media:VLSI.Arith.1.A.CSelA.20191002.pdf|A]]|| || || |- || '''5. Carry Skip Adder''' || [[Media:VLSI.Arith.5A.CSkip.20250405.pdf|A]]|| || || [[Media:VLSI.Arith.5D.CSkip.CMOS.20211108.pdf|pdf]] |- || '''6. Carry Chain Adder''' || [[Media:VLSI.Arith.6A.CCA.20211109.pdf|A]]|| || [[Media:VLSI.Arith.6C.CCA.VHDL.20211109.pdf|pdf]], [[Media:Adder.cca.20140313.pdf|pdf]] || [[Media:VLSI.Arith.6D.CCA.CMOS.20211109.pdf|pdf]] |- || '''7. Kogge-Stone Adder''' || [[Media:VLSI.Arith.1.A.KSA.20140315.pdf|A]]|| || [[Media:Adder.ksa.20140409.pdf|pdf]]|| |- || '''8. Prefix Adder''' || [[Media:VLSI.Arith.1.A.PFA.20140314.pdf|A]]|| || || |- || '''9.1 Variable Block Adder''' || [[Media:VLSI.Arith.1A.VBA.20221110.pdf|A]], [[Media:VLSI.Arith.1B.VBA.20230911.pdf|B]], [[Media:VLSI.Arith.1C.VBA.20240622.pdf|C]], [[Media:VLSI.Arith.1C.VBA.20250218.pdf|D]]|| || || |- || '''9.2 Multi-Level Variable Block Adder''' || [[Media:VLSI.Arith.1.A.VBA-Multi.20221031.pdf|A]]|| || || |} </br> === Adder Architectures Suitable for FPGA === * FPGA Carry-Chain Adder ([[Media:VLSI.Arith.1.A.FPGA-CCA.20210421.pdf|pdf]]) * FPGA Carry Select Adder ([[Media:VLSI.Arith.1.B.FPGA-CarrySelect.20210522.pdf|pdf]]) * FPGA Variable Block Adder ([[Media:VLSI.Arith.1.C.FPGA-VariableBlock.20220125.pdf|pdf]]) * FPGA Carry Lookahead Adder ([[Media:VLSI.Arith.1.D.FPGA-CLookahead.20210304.pdf|pdf]]) * Carry-Skip Adder </br> == Barrel Shifter == * Barrel Shifter Architecture Exploration ([[Media:Bshift.20131105.pdf|bshfit.vhdl]], [[Media:Bshift.makefile.20131109.pdf|bshfit.makefile]]) </br> '''Mux Based Barrel Shifter''' * Analysis ([[Media:Arith.BShfiter.20151207.pdf|pdf]]) * Implementation </br> == Multiplier == === Array Multipliers === * Analysis ([[Media:VLSI.Arith.1.A.Mult.20151209.pdf|pdf]]) </br> === Tree Mulltipliers === * Lattice Multiplication ([[Media:VLSI.Arith.LatticeMult.20170204.pdf|pdf]]) * Wallace Tree ([[Media:VLSI.Arith.WallaceTree.20170204.pdf|pdf]]) * Dadda Tree ([[Media:VLSI.Arith.DaddaTree.20170701.pdf|pdf]]) </br> === Booth Multipliers === * [[Media:RNS4.BoothEncode.20161005.pdf|Booth Encoding Note]] * Booth Multiplier Note ([[Media:BoothMult.20160929.pdf|H1.pdf]]) </br> == Divider == * Binary Divider ([[Media:VLSI.Arith.1.A.Divider.20131217.pdf|pdf]])</br> </br> </br> go to [ [[Electrical_%26_Computer_Engineering_Studies]] ] [[Category:Digital Circuit Design]] [[Category:FPGA]] 0rqukmhwlzygoxp5kng31kml141biu2 2835326 2835323 2026-10-01T10:23:21Z Young1lim 21186 /* Adder */ 2835326 wikitext text/x-wiki == Adder == * Binary Adder Architecture Exploration ( [[Media:Adder.20131113.pdf|pdf]] ) {| class="wikitable" |- ! Adder type !! Overview !! Analysis !! VHDL Level Design !! CMOS Level Design |- | '''1. Ripple Carry Adder''' || [[Media:VLSI.Arith.1A.RCA.20250522.pdf|A]]|| || [[Media:Adder.rca.20140313.pdf|pdf]] || [[Media:VLSI.Arith.1D.RCA.CMOS.20211108.pdf|pdf]] |- | '''2. Carry Lookahead Adder''' || [[Media:VLSI.Arith.2A.CLA.20260722.pdf|A]], [[Media:VLSI.Arith.2B.CLA.20261001.pdf|B]], [[Media:VLSI.Arith.2C.CLA.20261001.pdf|C]], [[Media:VLSI.Arith.2D.CLA.20260720.pdf|D]] || || [[Media:Adder.cla.20140313.pdf|pdf]]|| |- | '''3. Carry Save Adder''' || [[Media:VLSI.Arith.1.A.CSave.20151209.pdf|A]]|| || || |- || '''4. Carry Select Adder''' || [[Media:VLSI.Arith.1.A.CSelA.20191002.pdf|A]]|| || || |- || '''5. Carry Skip Adder''' || [[Media:VLSI.Arith.5A.CSkip.20250405.pdf|A]]|| || || [[Media:VLSI.Arith.5D.CSkip.CMOS.20211108.pdf|pdf]] |- || '''6. Carry Chain Adder''' || [[Media:VLSI.Arith.6A.CCA.20211109.pdf|A]]|| || [[Media:VLSI.Arith.6C.CCA.VHDL.20211109.pdf|pdf]], [[Media:Adder.cca.20140313.pdf|pdf]] || [[Media:VLSI.Arith.6D.CCA.CMOS.20211109.pdf|pdf]] |- || '''7. Kogge-Stone Adder''' || [[Media:VLSI.Arith.1.A.KSA.20140315.pdf|A]]|| || [[Media:Adder.ksa.20140409.pdf|pdf]]|| |- || '''8. Prefix Adder''' || [[Media:VLSI.Arith.1.A.PFA.20140314.pdf|A]]|| || || |- || '''9.1 Variable Block Adder''' || [[Media:VLSI.Arith.1A.VBA.20221110.pdf|A]], [[Media:VLSI.Arith.1B.VBA.20230911.pdf|B]], [[Media:VLSI.Arith.1C.VBA.20240622.pdf|C]], [[Media:VLSI.Arith.1C.VBA.20250218.pdf|D]]|| || || |- || '''9.2 Multi-Level Variable Block Adder''' || [[Media:VLSI.Arith.1.A.VBA-Multi.20221031.pdf|A]]|| || || |} </br> === Adder Architectures Suitable for FPGA === * FPGA Carry-Chain Adder ([[Media:VLSI.Arith.1.A.FPGA-CCA.20210421.pdf|pdf]]) * FPGA Carry Select Adder ([[Media:VLSI.Arith.1.B.FPGA-CarrySelect.20210522.pdf|pdf]]) * FPGA Variable Block Adder ([[Media:VLSI.Arith.1.C.FPGA-VariableBlock.20220125.pdf|pdf]]) * FPGA Carry Lookahead Adder ([[Media:VLSI.Arith.1.D.FPGA-CLookahead.20210304.pdf|pdf]]) * Carry-Skip Adder </br> == Barrel Shifter == * Barrel Shifter Architecture Exploration ([[Media:Bshift.20131105.pdf|bshfit.vhdl]], [[Media:Bshift.makefile.20131109.pdf|bshfit.makefile]]) </br> '''Mux Based Barrel Shifter''' * Analysis ([[Media:Arith.BShfiter.20151207.pdf|pdf]]) * Implementation </br> == Multiplier == === Array Multipliers === * Analysis ([[Media:VLSI.Arith.1.A.Mult.20151209.pdf|pdf]]) </br> === Tree Mulltipliers === * Lattice Multiplication ([[Media:VLSI.Arith.LatticeMult.20170204.pdf|pdf]]) * Wallace Tree ([[Media:VLSI.Arith.WallaceTree.20170204.pdf|pdf]]) * Dadda Tree ([[Media:VLSI.Arith.DaddaTree.20170701.pdf|pdf]]) </br> === Booth Multipliers === * [[Media:RNS4.BoothEncode.20161005.pdf|Booth Encoding Note]] * Booth Multiplier Note ([[Media:BoothMult.20160929.pdf|H1.pdf]]) </br> == Divider == * Binary Divider ([[Media:VLSI.Arith.1.A.Divider.20131217.pdf|pdf]])</br> </br> </br> go to [ [[Electrical_%26_Computer_Engineering_Studies]] ] [[Category:Digital Circuit Design]] [[Category:FPGA]] 28l1cq4atb7888cq1bgperdlhhe5l5t 4 159013 2835219 2830270 2026-09-30T18:36:02Z MediaWiki message delivery 983498 /* This Month in Education: September 2026 */ new section 2835219 wikitext text/x-wiki == Archives == * [[Outreach:Education/Newsletter/Archives]] == This Month in Education: January 2018 == [[File:Wikipedia Education Globe 2.pdf|frameless|left|150px|Wikipedia Education globe]] <div style="text-align:left; direction:ltr;"> <span style="font-weight:bold; color:#006699; font-size:60px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span></div> <div style="text-align:center; direction:ltr; margin-left;"> <span style="font-weight:bold; color:#006699; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; display:block; width:900px;"> Volume 7 | Issue 1 | January 2018</span> </div> <span style="font-weight:regular; text-align:center; font-size:14px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; display:block; width:1000px;">This monthly newsletter showcases the Wikipedia Education Program. It focuses on sharing: your ideas, stories, success and challenges. You can see past editions [[outreach:Education/Newsletter/Archives|here]]. You can also volunteer to help publish the newsletter. [[outreach:Education/News/Team|Join the team!]] Finally, don't forget to [[m:Global_message_delivery/Targets/Wikimedia_Education_Newsletter|subscribe!]]</span> {{anchor|back}} <div style=text-align:center; direction:ltr;"><span style="color:white; font-size:24px; font-family:times new roman; display:block; background:#339966; width:1000px;">In This Issue</span></div> {| style="width:60%;" | style="width:50%; color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/January 2018#Featured Topic|Featured Topic]] | style="width:50%; font-size:16px; font-family:times new roman;" | <!-- Enter the title of the articles for this issue --> [[outreach:Education/Newsletter/January 2018#Article 1|Bertsomate: using Basque oral poetry to illustrate math concepts]] |- | style="color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/January 2018#From the Community|From the Community]] | style="font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/January 2018#Article 2|Wikimedia Serbia celebrated 10 years from the first article written within the Education Program]] [[outreach:Education/Newsletter/January 2018#Article 3|WikiChallenge Ecoles d'Afrique update]] [[outreach:Education/Newsletter/January 2018#Article 4|The first Swedish Master's in Digital Humanities partners with Wikimedia Sverige]] [[outreach:Education/Newsletter/January 2018#Article 5|How we use PetScan to improve partnership with lecturers and professors]] |- | style="color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/January 2018#From the Education Team|From the Education Team]] | style="font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/January 2018#Article 6|The Education Survey Report is out!]] [[outreach:Education/Newsletter/January 2018#Article 7|Education Extension scheduled shutdown]] |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Global_message_delivery/Targets/Wikimedia_Education_Newsletter|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 18:42, 1 February 2018 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/Wikimedia_Education_Newsletter&oldid=17696217 --> == This Month in Education: February 2018 == [[File:Wikipedia Education Globe 2.pdf|frameless|left|150px|Wikipedia Education globe]] <div style="text-align:left; direction:ltr;"> <span style="font-weight:bold; color:#006699; font-size:60px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span></div> <div style="text-align:center; direction:ltr; margin-left;"> <span style="font-weight:bold; color:#006699; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; display:block; width:900px;"> Volume 7 | Issue 2 | February 2018</span> </div> <span style="font-weight:regular; text-align:center; font-size:14px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; display:block; width:1000px;">This monthly newsletter showcases the Wikipedia Education Program. It focuses on sharing: your ideas, stories, success and challenges. You can see past editions [[outreach:Education/Newsletter/Archives|here]]. You can also volunteer to help publish the newsletter. [[outreach:Education/News/Team|Join the team!]] Finally, don't forget to [[m:Global_message_delivery/Targets/Wikimedia_Education_Newsletter|subscribe!]]</span> <div style=text-align:center; direction:ltr;"><span style="color:white; font-size:24px; font-family:times new roman; display:block; background:#339966; width:1000px;">In This Issue</span></div> {| style="width:60%;" | style="color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/February 2018#From the Community|From the Community]] | style="font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/February 2018#Article 2|WikiProject Engineering Workshop at IIUC,Chittagong]] [[outreach:Education/Newsletter/February 2018#Article 3|What did we learn from Wikibridges MOOC?]] [[outreach:Education/Newsletter/February 2018#Article 4|Wikimedia Serbia launched Wiki scholar project]] [[outreach:Education/Newsletter/February 2018#Article 5|Wiki Club in Ohrid, Macedonia]] [[outreach:Education/Newsletter/February 2018#Article 6|Karvachar’s WikiClub: When getting knowledge is cool]] [[outreach:Education/Newsletter/February 2018#Article 7|More than 30 new courses launched in the University of the Basque Country]] [[outreach:Education/Newsletter/February 2018#Article 8|Review meeting on Christ Wikipedia Education Program]] [[outreach:Education/Newsletter/February 2018#Article 9|The Multidisciplinary Choices of High School Students: The Arabic Education Program; Wikimedia Israel]] |- | style="color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/February 2018#From the Education Team|From the Education Team]] | style="font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/February 2018#Article 10|The Education Extension is being deprecated (second call)]] [[outreach:Education/Newsletter/February 2018#Article 11|The 2017 survey report live presentation is available for viewing]] |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Global_message_delivery/Targets/Wikimedia_Education_Newsletter|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 08:53, 1 March 2018 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/Wikimedia_Education_Newsletter&oldid=17757914 --> == This Month in Education: March 2018 == [[File:Wikipedia Education Globe 2.pdf|frameless|left|150px|Wikipedia Education globe]] <div style="text-align:left; direction:ltr;"> <span style="font-weight:bold; color:#006699; font-size:60px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span></div> <div style="text-align:center; direction:ltr; margin-left;"> <span style="font-weight:bold; color:#006699; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; display:block; width:900px;"> Volume 7 | Issue 3 | March 2018</span> </div> <span style="font-weight:regular; text-align:center; font-size:14px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; display:block; width:1000px;">This monthly newsletter showcases the Wikipedia Education Program. It focuses on sharing: your ideas, stories, success and challenges. You can see past editions [[outreach:Education/Newsletter/Archives|here]]. You can also volunteer to help publish the newsletter. [[outreach:Education/News/Team|Join the team!]] Finally, don't forget to [[m:Global_message_delivery/Targets/Wikimedia_Education_Newsletter|subscribe!]]</span> <div style=text-align:center; direction:ltr;"><span style="color:white; font-size:24px; font-family:times new roman; display:block; background:#339966; width:1000px;">In This Issue</span></div> {| style="width:60%;" | style="width:50%; color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/March 2018#Featured Topic|Featured Topic]] | style="width:50%; font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/March 2018#Article 1|Education Programs Itinerary]] |- | style="color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/March 2018#From the Community|From the Community]] | style="font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/March 2018#Article 2|Animated science educational videos in Basque for secondary school student]] [[outreach:Education/Newsletter/March 2018#Article 3|Beirut WikiClub: Wikijourney that has enriched our experiences]] [[outreach:Education/Newsletter/March 2018#Article 4|Students of the Faculty of Biology in Belgrade edit Wikipedia for the first time]] [[outreach:Education/Newsletter/March 2018#Article 5|The role of Wikipedia in education - Examples from the Wiki Education Foundation]] [[outreach:Education/Newsletter/March 2018#Article 6|Multilingual resource for Open education projects]] [[outreach:Education/Newsletter/March 2018#Article 7|Wikipedia: examples of curricular integration in Portugal]] |- | style="color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/March 2018#From the Education Team|From the Education Team]] | style="font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/March 2018#Article 8|Resources and Tips to engage with Educators]] [[outreach:Education/Newsletter/March 2018#Article 9|Education Session at WMCON 2018]] |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Global_message_delivery/Targets/Wikimedia_Education_Newsletter|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 10:33, 4 April 2018 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/Wikimedia_Education_Newsletter&oldid=17882222 --> == This Month in Education: April 2018 == [[File:Wikipedia Education Globe 2.pdf|frameless|left|150px|Wikipedia Education globe]] <div style="text-align:left; direction:ltr;"> <span style="font-weight:bold; color:#006699; font-size:60px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span></div> <div style="text-align:center; direction:ltr; margin-left;"> <span style="font-weight:bold; color:#006699; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; display:block; width:900px;"> Volume 7 | Issue 4 | April 2018</span> </div> <span style="font-weight:regular; text-align:center; font-size:14px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; display:block; width:1000px;">This monthly newsletter showcases the Wikipedia Education Program. It focuses on sharing: your ideas, stories, success and challenges. You can see past editions [[outreach:Education/Newsletter/Archives|here]]. You can also volunteer to help publish the newsletter. [[outreach:Education/News/Team|Join the team!]] Finally, don't forget to [[m:Global_message_delivery/Targets/Wikimedia_Education_Newsletter|subscribe!]]</span> <div style=text-align:center; direction:ltr;"><span style="color:white; font-size:24px; font-family:times new roman; display:block; background:#339966; width:1000px;">In This Issue</span></div> {| style="width:60%;" | style="width:50%; color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/April 2018#Featured Topic|Featured Topic]] | style="width:50%; font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/April 2018#Article 1|Wikimedia at the Open Educational Resources Conference 2018]] |- | style="color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/April 2018#From the Community|From the Community]] | style="font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/April 2018#Article 2|Global perspectives from Western Norway]] [[outreach:Education/Newsletter/April 2018#Article 3|Togh's WikiClub: Wikipedia is the 8th wonder of the world!]] [[outreach:Education/Newsletter/April 2018#Article 4|Aboriginal Volunteers in Taiwan Shared Experience about Incubating Minority Language Wikipedia in Education Magazine]] [[outreach:Education/Newsletter/April 2018#Article 5|Workshops with Wiki Clubs members in the Republic of Macedonia]] [[outreach:Education/Newsletter/April 2018#Article 6|Celebrating Book's Day in the University of the Basque Country: is Wikipedia the largest Basque language book?]] [[outreach:Education/Newsletter/April 2018#Article 7|Txikipedia is born and you'll love it]] [[outreach:Education/Newsletter/April 2018#Article 8|Students Write Wiktionary]] |- | style="color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/April 2018#From the Education Team|From the Education Team]] | style="font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/April 2018#Article 9|Presenting the Wikipedia Education Program at the Open Education Global Conference]] |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Global_message_delivery/Targets/Wikimedia_Education_Newsletter|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 07:33, 4 May 2018 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/Wikimedia_Education_Newsletter&oldid=17992472 --> == This Month in Education: May 2018 == [[File:Wikipedia Education Globe 2.pdf|frameless|left|150px|Wikipedia Education globe]] <div style="text-align:left; direction:ltr;"> <span style="font-weight:bold; color:#006699; font-size:60px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span></div> <div style="text-align:center; direction:ltr; margin-left;"> <span style="font-weight:bold; color:#006699; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; display:block; width:900px;"> Volume 4 | Issue 5 | May 2018</span> </div> <span style="font-weight:regular; text-align:center; font-size:14px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; display:block; width:1000px;">This monthly newsletter showcases the Wikipedia Education Program. It focuses on sharing: your ideas, stories, success and challenges. You can see past editions [[outreach:Education/Newsletter/Archives|here]]. You can also volunteer to help publish the newsletter. [[outreach:Education/News/Team|Join the team!]] Finally, don't forget to [[m:Global_message_delivery/Targets/Wikimedia_Education_Newsletter|subscribe!]]</span> <div style=text-align:center; direction:ltr;"><span style="color:white; font-size:24px; font-family:times new roman; display:block; background:#339966; width:1000px;">In This Issue</span></div> {| style="width:60%;" | style="color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/May 2018#From the Community|From the Community]] | style="font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/May 2018#Article 2|Creating and reusing OERs for a Wikiversity science journalism course from Brazil]] [[outreach:Education/Newsletter/May 2018#Article 3|Inauguration Ceremony of Sri Jayewardenepura University Wiki Club]] [[outreach:Education/Newsletter/May 2018#Article 4|Wiki Education publishes evaluation of Fellows pilot]] [[outreach:Education/Newsletter/May 2018#Article 5|The first students of Russia with diplomas of Wikimedia and Petrozavodsk State University]] [[outreach:Education/Newsletter/May 2018#Article 6|Selet WikiSchool]] |- | style="color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/May 2018#From the Education Team|From the Education Team]] | style="font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/May 2018#Article 8|A lofty vision for the Education Team]] [[outreach:Education/Newsletter/May 2018#Article 9|UNESCO Mobile Learning Week 2018, Digital Skills for Life and Work]] |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Global_message_delivery/Targets/Wikimedia_Education_Newsletter|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 21:44, 4 June 2018 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/Wikimedia_Education_Newsletter&oldid=18071070 --> == This Month in Education: June 2018 == [[File:Wikipedia Education Globe 2.pdf|frameless|left|150px|Wikipedia Education globe]] <div style="text-align:left; direction:ltr;"> <span style="font-weight:bold; color:#006699; font-size:60px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span></div> <div style="text-align:center; direction:ltr; margin-left;"> <span style="font-weight:bold; color:#006699; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; display:block; width:900px;"> Volume 4 | Issue 6 | June 2018</span> </div> <span style="font-weight:regular; text-align:center; font-size:14px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; display:block; width:1000px;">This monthly newsletter showcases the Wikipedia Education Program. It focuses on sharing: your ideas, stories, success and challenges. You can see past editions [[outreach:Education/Newsletter/Archives|here]]. You can also volunteer to help publish the newsletter. [[outreach:Education/News/Team|Join the team!]] Finally, don't forget to [[m:Global_message_delivery/Targets/Wikimedia_Education_Newsletter|subscribe!]]</span> <div style=text-align:center; direction:ltr;"><span style="color:white; font-size:24px; font-family:times new roman; display:block; background:#339966; width:1000px;">In This Issue</span></div> {| style="width:60%;" | style="width:50%; color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/June 2018#Featured Topic|Featured Topic]] | style="width:50%; font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/June 2018#Article 1|Academia and Wikipedia: the first Irish conference on Wikipedia in education]] |- | style="color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/June 2018#From the Community|From the Community]] | style="font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/June 2018#Article 2|Ashesi Wiki Club: Charting the cause for Wikipedia Education Program in West Africa]] [[outreach:Education/Newsletter/June 2018#Article 3|Wikimedia Serbia has received a new accreditation for the Accredited seminars for teachers]] [[outreach:Education/Newsletter/June 2018#Article 4|Côte d'Ivoire: Wikipedia Classes 2018 are officially up and running]] [[outreach:Education/Newsletter/June 2018#Article 5|Basque secondary students have now better coverage for main topics thanks to the Education Program]] [[outreach:Education/Newsletter/June 2018#Article 6|What lecturers think about their first experience in the Basque Education Program]] |- | style="color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/June 2018#From the Education Team|From the Education Team]] | style="font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/June 2018#Article 7|Education Extension scheduled deprecation]] |- | style="color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/June 2018#In the News|In the News]] | style="font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/June 2018#Article 8|Wikipedia calls for participation to boost content from the continent]] [[outreach:Education/Newsletter/June 2018#Article 9|Wikipedia in the History Classroom]] [[outreach:Education/Newsletter/June 2018#Article 10|Wikipedia as a Pedagogical Tool Complicating Writing in the Technical Writing Classroom]] [[outreach:Education/Newsletter/June 2018#Article 11|When the World Helps Teach Your Class: Using Wikipedia to Teach Controversial Issues]] |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 06:03, 30 June 2018 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=18158878 --> == This Month in Education: July 2018 == [[File:Wikipedia Education Globe 2.pdf|frameless|left|150px|Wikipedia Education globe]] <div style="text-align:left; direction:ltr;"> <span style="font-weight:bold; color:#006699; font-size:60px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span></div> <div style="text-align:center; direction:ltr; margin-left;"> <span style="font-weight:bold; color:#006699; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; display:block; width:900px;"> Volume 4 | Issue 7 | July 2018</span> </div> <span style="font-weight:regular; text-align:center; font-size:14px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; display:block; width:1000px;">This monthly newsletter showcases the Wikipedia Education Program. It focuses on sharing: your ideas, stories, success and challenges. You can see past editions [[outreach:Education/Newsletter/Archives|here]]. You can also volunteer to help publish the newsletter. [[outreach:Education/News/Team|Join the team!]] Finally, don't forget to [[m:Global_message_delivery/Targets/Wikimedia_Education_Newsletter|subscribe!]]</span> <div style=text-align:center; direction:ltr;"><span style="color:white; font-size:24px; font-family:times new roman; display:block; background:#339966; width:1000px;">In This Issue</span></div> {| style="width:60%;" | style="width:50%; color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/July 2018#Featured Topic|Featured Topic]] | style="width:50%; font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/July 2018#Article 1|Wikipedia+Education Conference 2019: Community Engagement Survey]] |- | style="color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/July 2018#From the Community|From the Community]] | style="font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/July 2018#Article 2|Young wikipedian: At WikiClub you get knowledge on your own will]] [[outreach:Education/Newsletter/July 2018#Article 3|Wikipedia in schools project at the "New Technologies in Education" Conference]] [[outreach:Education/Newsletter/July 2018#Article 4|Basque Education Program: 2017-2018 school year report]] |- | style="color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/July 2018#In the News|In the News]] | style="font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/July 2018#Article 10|UNESCO ICT in Education Prize call for nominations opens]] [[outreach:Education/Newsletter/July 2018#Article 11|An educator's overview of Wikimedia (in short videos format)]] |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 06:32, 2 August 2018 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=18263925 --> == This Month in Education: August 2018 == [[File:Wikipedia Education Globe 2.pdf|frameless|left|150px|Wikipedia Education globe]] <div style="text-align:left; direction:ltr;"> <span style="font-weight:bold; color:#006699; font-size:60px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span></div> <div style="text-align:center; direction:ltr; margin-left;"> <span style="font-weight:bold; color:#006699; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; display:block; width:900px;"> Volume 4 | Issue 8 | August 2018</span> </div> <span style="font-weight:regular; text-align:center; font-size:14px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; display:block; width:1000px;">This monthly newsletter showcases the Wikipedia Education Program. It focuses on sharing: your ideas, stories, success and challenges. You can see past editions [[outreach:Education/Newsletter/Archives|here]]. You can also volunteer to help publish the newsletter. [[outreach:Education/News/Team|Join the team!]] Finally, don't forget to [[m:Global_message_delivery/Targets/Wikimedia_Education_Newsletter|subscribe!]]</span> <div style=text-align:center; direction:ltr;"><span style="color:white; font-size:24px; font-family:times new roman; display:block; background:#339966; width:1000px;">In This Issue</span></div> {| style="width:60%;" | style="color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/August 2018#From the Community|From the Community]] | style="font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/August 2018#Article 2|The reconnection of Wikimedia Projects in Brazil]] [[outreach:Education/Newsletter/August 2018#Article 3|Christ (DU) students enrolls for 3rd Wikipedia certificate course]] [[outreach:Education/Newsletter/August 2018#Article 4|Educational wiki-master-classes at International "Selet" forum]] [[outreach:Education/Newsletter/August 2018#Article 5|54 students help enrich the digital Arabic content]] |- | style="color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/August 2018#From the Education Team|From the Education Team]] | style="font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/August 2018#Article 6|Mapping education in the Wikimedia Movement]] |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 03:12, 2 September 2018 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=18288215 --> == This Month in Education: September 2018 == [[File:Wikipedia Education Globe 2.pdf|frameless|left|150px|Wikipedia Education globe]] <div style="text-align:left; direction:ltr;"> <span style="font-weight:bold; color:#006699; font-size:60px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span></div> <div style="text-align:center; direction:ltr; margin-left;"> <span style="font-weight:bold; color:#006699; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; display:block; width:900px;"> Volume 4 | Issue 9 | September 2018</span> </div> <span style="font-weight:regular; text-align:center; font-size:14px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; display:block; width:1000px;">This monthly newsletter showcases the Wikipedia Education Program. It focuses on sharing: your ideas, stories, success and challenges. You can see past editions [[outreach:Education/Newsletter/Archives|here]]. You can also volunteer to help publish the newsletter. [[outreach:Education/News/Team|Join the team!]] Finally, don't forget to [[m:Global_message_delivery/Targets/Wikimedia_Education_Newsletter|subscribe!]]</span> <div style=text-align:center; direction:ltr;"><span style="color:white; font-size:24px; font-family:times new roman; display:block; background:#339966; width:1000px;">In This Issue</span></div> {| style="width:60%;" | style="color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/September 2018#From the Community|From the Community]] | style="font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/September 2018#Article 1|Edu Wiki Camp 2018: New Knowledge for New Generation]] [[outreach:Education/Newsletter/September 2018#Article 2|Education loves Monuments: A Brazilian Tale]] [[outreach:Education/Newsletter/September 2018#Article 3|“I have always liked literature, now I like it even more thanks to Wikipedia”. Literature is in the air of WikiClubs․]] [[outreach:Education/Newsletter/September 2018#Article 4|History of Wikipedia Education programme at Christ (Deemed to be University)]] [[outreach:Education/Newsletter/September 2018#Article 5|Preparation for the autumn educational session of Selet WikiSchool is started]] [[outreach:Education/Newsletter/September 2018#Article 6|Wiki Camp Doyran 2018]] [[outreach:Education/Newsletter/September 2018#Article 7|Wikicamp Czech Republic 2018]] [[outreach:Education/Newsletter/September 2018#Article 8|Wikipedia offline in rural areas of Colombia]] |- | style="color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/September 2018#From the Education Team|From the Education Team]] | style="font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/September 2018#Article 9|Presentation on mapping education in the Wikimedia Movement]] |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 01:14, 9 October 2018 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=18394865 --> == This Month in Education: November 2018 == [[File:Wikipedia Education Globe 2.pdf|frameless|left|150px|Wikipedia Education globe]] <div style="text-align:left; direction:ltr;"> <span style="font-weight:bold; color:#006699; font-size:60px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span></div> <div style="text-align:center; direction:ltr; margin-left;"> <span style="font-weight:bold; color:#006699; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; display:block; width:900px;"> Volume 4 | Issue 10 | October 2018</span> </div> <span style="font-weight:regular; text-align:center; font-size:14px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; display:block; width:1000px;">This monthly newsletter showcases the Wikipedia Education Program. It focuses on sharing: your ideas, stories, success and challenges. You can see past editions [[outreach:Education/Newsletter/Archives|here]]. You can also volunteer to help publish the newsletter. [[outreach:Education/News/Team|Join the team!]] Finally, don't forget to [[m:Global_message_delivery/Targets/Wikimedia_Education_Newsletter|subscribe!]]</span> <div style=text-align:center; direction:ltr;"><span style="color:white; font-size:24px; font-family:times new roman; display:block; background:#339966; width:1000px;">In This Issue</span></div> {| style="width:60%;" | style="color:#990000; font-size:20px; font-family:times new roman;" | [[outreach:Education/Newsletter/October 2018#From the Community|From the Community]] | style="font-size:16px; font-family:times new roman;" | [[outreach:Education/Newsletter/October 2018#Article 1|A new academic course featuring Wikidata at Tel Aviv University]] [[outreach:Education/Newsletter/October 2018#Article 2|How we included Wikipedia edition into a whole University department curriculum]] [[outreach:Education/Newsletter/October 2018#Article 3|Meet the first board of the UG Wikipedia & Education]] [[outreach:Education/Newsletter/October 2018#Article 4|The education program has kicked off as the new academic year starts]] [[outreach:Education/Newsletter/October 2018#Article 5|The education program has kicked off as the new academic year starts in Albania]] [[outreach:Education/Newsletter/October 2018#Article 6|The first Wikimedia+Education conference will happen on April 5-7 at Donostia-Saint Sebastian]] [[outreach:Education/Newsletter/October 2018#Article 7|Using ORES to assign articles in Basque education program]] [[outreach:Education/Newsletter/October 2018#Article 8|What to write for Wikipedia about? Monuments!]] [[outreach:Education/Newsletter/October 2018#Article 9|Wikifridays: editing Wikipedia in the university]] [[outreach:Education/Newsletter/October 2018#Article 10|Writing articles on Wikipedia is our way of leaving legacy to the next generations]] |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 05:55, 12 November 2018 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=18504430 --> == This Month in Education: November 2018 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em; direction:ltr;" | <span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 4 &bull; Issue 10 &bull; October 2018</span> ------ <span style="font-size:larger;">[[outreach:Education/Newsletter/November 2018|Contents]] &bull; [[outreach:Education/Newsletter/November 2018/Single page|Single page view]] &bull; [[:m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ------- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> *[[:outreach:Education/News/November 2018/WikiEducation - Report from Wikimedians of Albanian Language UG |WikiEducation - Report from Wikimedians of Albanian Language UG]] *[[:outreach:Education/News/November 2018/Wikipedia Education Program in ICETC 2018 , Japan |Wikipedia Education Program in ICETC 2018, Japan]] *[[:outreach:Education/News/November 2018/Wikipedia has become the inseparable part of my daily life |Wikipedia has become the inseparable part of my daily life]] *[[:outreach:Education/News/November 2018/Wikipedia is a world in which anyone of us has his own place |Wikipedia is a world in which anyone of us has his own place]] *[[:outreach:Education/News/November 2018/Wiki conference for teachers in Ohrid |Wiki conference for teachers in Ohrid]] *[[:outreach:Education/News/November 2018/Our baby is 3! |Our baby is 3!]] *[[:outreach:Education/News/November 2018/highlighting work of Sailesh Patnaik |Highlighting work of Sailesh Patnaik]] *[[:outreach:Education/News/November 2018/Important updates from Wikimedia Education Team |Important updates from Wikimedia Education Team]] *[[:outreach:Education/News/November 2018/Welcome Melissa to the Education Team |Welcome Melissa to the Education Team]] *[[:outreach:Education/News/November 2018/What has the education team been up to? Year end review and updates! |What has the education team been up to? Year end review and updates! ]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 18:18, 30 November 2018 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=18673623 --> == This Month in Education: January 2019 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" | <span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 8 &bull; Issue 1 &bull; January 2019</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/January 2019|Contents]] &bull; [[outreach:Education/Newsletter/January 2019/Headlines|Headlines]] &bull; [[:m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> *[[:outreach:Education/News/January 2019/Registration for Wikimedia+Education Conference is open|Registration for Wikimedia+Education Conference is open]] *[[:outreach:Education/News/January 2019/Collaboration with Yerevan State University of Languages and Social Sciences after V. Brusov|Collaboration with Yerevan State University of Languages and Social Sciences after V. Brusov]] *[[:outreach:Education/News/January 2019/Meet the first Programs & Events Dashboard sysops|Meet the first Programs & Events Dashboard sysops]] *[[:outreach:Education/News/January 2019/More than a hundred students gathered in Ecuador to edit Wikipedia|More than a hundred students gathered in Ecuador to edit Wikipedia]] *[[:outreach:Education/News/January 2019/Selet WikiSchool continues to teach young Tatar language Wikipedians|Selet WikiSchool continues to teach young Tatar language Wikipedians]] *[[:outreach:Education/News/January 2019/The WikiClub contributes to the development of our human qualities |The WikiClub contributes to the development of our human qualities]] *[[:outreach:Education/News/January 2019/Third prize for Wikipedia in schools project|Third prize for Wikipedia in schools project]] *[[:outreach:Education/News/January 2019/We've updated the design of Education space!|We've updated the design of Education space!]] *[[:outreach:Education/News/January 2019/WikiChallenge Ecoles d'Afrique 2019|The WikiChallenge Ecoles d'Afrique is back]] *[[:outreach:Education/News/January 2019/Wiki Advanced Training at VVIT|Wiki Advanced Training at VVIT]] *[[:outreach:Education/News/January 2019/WikiEducation in Albania from WoALUG|Creating our first WikiClub]] *[[:outreach:Education/News/January 2019/WikiClubs participate in edit-a-thon of cartoons|WikiClubs participate in edit-a-thon of cartoons]] *[[:outreach:Education/News/January 2019/Wikimedia and Education in Portugal: Where are we now|Wikimedia and Education in Portugal: Where are we now]] *[[:outreach:Education/News/January 2019/Wikimedia Israel: “Wikipedia Ambassadors” program for Arabic-speaking schools is launched|Wikimedia Israel: “Wikipedia Ambassadors” program for Arabic-speaking schools is launched]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 04:41, 29 January 2019 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=18816770 --> == This Month in Education: February 2019 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" | <span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 8 &#x2022; Issue 2 &#x2022; February 2019</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/February 2019|Contents]] &#x2022; [[outreach:Education/Newsletter/February 2019/Headlines|Headlines]] &#x2022; [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[:outreach:Education/News/February 2019/Wikimedia User Group Nigeria in Collaboration with AfroCrowd Celebrate Black Month History with a 2Day Editathon|Wikimedia User Group Nigeria in Collaboration with AfroCrowd Celebrate Black Month History with a 2Day Editathon]] * [[:outreach:Education/News/February 2019/Wikimedia+Education Programme announced|Wikimedia+Education Programme announced]] * [[:outreach:Education/News/February 2019/Wikipedia in Education, Uruguay|Wikipedia in Education, Uruguay]] * [[:outreach:Education/News/February 2019/Oslo Metropolitan University hires “Wikipedia-assistants”|Oslo Metropolitan University hires “Wikipedia-assistants”]] * [[:outreach:Education/News/February 2019/Basque Education Program: 2018 in review|Basque Education Program: 2018 in review]] * [[:outreach:Education/News/February 2019/Wikimedia Israel introduces Wikidata to Education|Wikimedia Israel introduces Wikidata to Education]] * [[:outreach:Education/News/February 2019/Wikimedia Serbia made tutorials in Serbian language on editing Wikipedia|Wikimedia Serbia made tutorials in Serbian language on editing Wikipedia]] * [[:outreach:Education/News/February 2019/Seminar on wikis in education|Seminar on wikis in education]] * [[:outreach:Education/News/February 2019/Wikimedia, Tourism and Education: Launching project ISAL|Wikimedia, Tourism and Education: Launching project ISAL]] * [[:outreach:Education/News/February 2019/The Swiss Lab: Wikipedia as a game|The Swiss Lab: Wikipedia as a game]] * [[:outreach:Education/News/February 2019/Meet Hungary|Meet Hungary]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 17:52, 27 February 2019 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=18903920 --> == This Month in Education: March 2019 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" | <span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 8 &#x2022; Issue 3 &#x2022; March 2019</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/March 2019|Contents]] &#x2022; [[outreach:Education/Newsletter/March 2019/Headlines|Headlines]] &#x2022; [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[:outreach:Education/News/March 2019/Wikimedia at MLW2019|Wikimedia at UNESCO Mobile Learning Week 2019]] * [[:outreach:Education/News/March 2019/Wiki Education publishes evaluation on how to get subject matter experts to edit|Wiki Education publishes evaluation on how to get subject matter experts to edit]] * [[:outreach:Education/News/March 2019/WikiGap brings editors to close WikiGap|WikiGap brings editors to close WikiGap and open Wiki Pathshala]] * [[:outreach:Education/News/March 2019/Education Mapping exercise is open for public review|Education Mapping exercise is open for public review]] * [[:outreach:Education/News/March 2019/Wikimedia movement projects and activities presented at EDU RUSSIA 2019 forum|Wikimedia movement projects and activities presented at EDU RUSSIA 2019 forum]] * [[:outreach:Education/News/March 2019/“Edit-a-thons give us opportunity to distract from common interests” The club members write articles about New Year|“Edit-a-thons give us opportunity to distract from common interests” The club members write articles about New Year]] * [[:outreach:Education/News/March 2019/WikiClub as a non-formal educational centre in rural communities|WikiClub as a non-formal educational centre in rural communities]] * [[:outreach:Education/News/March 2019/Mini-MWT at VVIT (Feb 2019)|Mini MediaWiki Training at VVIT]]</div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 06:31, 28 March 2019 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=18959709 --> == Bring your idea for Wikimedia in Education to life! Launch of the Wikimedia Education Greenhouse == {{center|'''Apply for Education Greenhouse'''}} [[File:Wikimedia Education Greenhouse logo button.svg|frameless|left|120px]] Are you passionate about open education? Do you have an idea to apply Wikimedia projects to an education initiative but don’t know where to start? Join the the Wikimedia & Education Greenhouse! It is an immersive co-learning experience that lasts 9 months and will equip you with the skills, knowledge and support you need to bring your ideas to life. You can apply as a team or as an individual, by May 12th. Find out more <big> [[:outreach:Education/Greenhouse|Education Greenhouse]].</big> For more information reachout to mguadalupe{{@}}wikimedia.org —[[User:MediaWiki message delivery|MediaWiki message delivery]] ([[User talk:MediaWiki message delivery|discuss]] • [[Special:Contributions/MediaWiki message delivery|contribs]]) 11:16, 5 April 2019 (UTC) <!-- Message sent by User:Saileshpat@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=18981257 --> == This Month in Education: April 2019 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" | <span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 8 &#x2022; Issue 4 &#x2022; April 2019</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/April 2019|Contents]] &#x2022; [[outreach:Education/Newsletter/April 2019/Headlines|Headlines]] &#x2022; [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[:outreach:Education/News/April 2019/Launch of the Wikimedia & Education Greenhouse!|Launch of the Wikimedia & Education Greenhouse!]] * [[:outreach:Education/News/April 2019/Wikipedia Student Scholar|Wikipedia Student Scholar]] * [[:outreach:Education/News/April 2019/Wikimedia Commons: a highly hostile place for multimedia students contributions|Wikimedia Commons: a highly hostile place for multimedia students contributions]] * [[:outreach:Education/News/April 2019/Wikimedia+Education Conference highlights|Wikimedia+Education Conference highlights]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 01:27, 24 April 2019 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=19034809 --> == This Month in Education: May 2019 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" | <span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 8 &#x2022; Issue 5 &#x2022; May 2019</span> ---- <span style="font-size:larger;">[[Outreach:Education/Newsletter/May 2019|Contents]] &#x2022; [[Outreach:Education/Newsletter/May 2019/Headlines|Headlines]] &#x2022; [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> *[[:Outreach:Education/News/May 2019/Education in Wales|Education in Wales]] *[[:Outreach:Education/News/May 2019/Wikimedia & Education Greenhouse: Applications closed!|Wikimedia & Education Greenhouse: Applications closed!]] *[[:Outreach:Education/News/May 2019/Meet Germany|Wiki Camp 'Meet Germany']] *[[:Outreach:Education/News/May 2019/Seniors also count!|Seniors also count!]] *[[:Outreach:Education/News/May 2019/Mandatory internship at Wikimedia Armenia|Mandatory internship at Wikimedia Armenia]] *[[:Outreach:Education/News/May 2019/Wikimedia Experience Survey by VVIT WikiConnect|Wikimedia Experience Survey by VVIT WikiConnect]] *[[:Outreach:Education/News/May 2019/OFWA Wikipedia Education Highlights April 2019|OFWA Wikipedia Education Highlights April 2019]] *[[:Outreach:Education/News/May 2019/Wikimedia Education at "Wikicamp Chattogram 2019"|Wikimedia Education at "Wikicamp Chattogram 2019"]] *[[:Outreach:Education/News/May 2019/Edit a thon about flora and fauna to celebrate the earth day|Edit a thon about flora and fauna to celebrate the earth day]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 07:16, 29 May 2019 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=19113682 --> == This Month in Education: June 2019 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" | <span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 8 &#x2022; Issue 6 &#x2022; June 2019</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/June 2019|Contents]] &#x2022; [[outreach:Education/Newsletter/June 2019/Headlines|Headlines]] &#x2022; [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> *[[outreach:Education/News/June 2019/The introduction of the Wikipedia into the educational program has expanded|The introduction of the Wikipedia into the educational program has expanded]] *[[outreach:Education/News/June 2019/Welcome Vasanthi|Welcome Vasanthi to the Education Team!]] *[[outreach:Education/News/June 2019/Wikimedia Education SAARC Conference happening in India|Wikimedia Education SAARC Conference happening in India]] *[[outreach:Education/News/June 2019/"Won't somebody please think of the children?"|"Won't somebody please think of the children?"]] *[[outreach:Education/News/June 2019/The first Annual Report of VVIT WikiConnect|The first Annual Report of VVIT WikiConnect]] *[[outreach:Education/News/June 2019/An effective collaboration of WikiClubs and schools|An effective collaboration of WikiClubs and schools]] *[[outreach:Education/News/June 2019/Wikiclassroom: New way for students' inspiration|Wikiclassroom: New way for students' inspiration]] *[[outreach:Education/News/June 2019/Wikipedia as a classroom activity kicks off in Kosovo|Wikipedia as a classroom activity kicks off in Kosovo]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 17:40, 6 July 2019 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=19174995 --> == This Month in Education: July 2019 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" | <span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 8 &#x2022; Issue 7 &#x2022; July 2019</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/July 2019|Contents]] &#x2022; [[outreach:Education/Newsletter/July 2019/Headlines|Headlines]] &#x2022; [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> *[[:outreach:Education/News/July 2019/First WikiEducation gathering in Mexico|First WikiEducation gathering in Mexico]] *[[:outreach:Education/News/July 2019/SEABA school in India has hired a Wikimedian to teach Wikimedia project in their school.|SEABA school in India has hired a Wikimedian to teach Wikimedia project in their school.]] *[[:outreach:Education/News/July 2019/Selet WikiSchool: results of first half of 2019|Selet WikiSchool: results of first half of 2019]] *[[:outreach:Education/News/July 2019/Students Use Archival Documents in a Competition, WMIL|Students Use Archival Documents in a Competition, WMIL]] *[[:outreach:Education/News/July 2019/Stepanakert WikiClub: Meeting with the Speaker of the Artsakh Parliament - Ashot Ghoulian|Stepanakert WikiClub: Meeting with the Speaker of the Artsakh Parliament - Ashot Ghoulian]] *[[:outreach:Education/News/July 2019/Collaboration with American University of Armenia|Collaboration with American University of Armenia]] *[[:outreach:Education/News/July 2019/Finalizing the Collaboration with Armenian Education Foundation|Finalizing the Collaboration with Armenian Education Foundation]] *[[:outreach:Education/News/July 2019/Wikimedia Education SAARC Conference Journey|Wikimedia Education SAARC Conference Journey]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 09:53, 30 July 2019 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=19221452 --> == This Month in Education: August 2019 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" | <span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 8 &#x2022; Issue 8 &#x2022; August 2019</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/August 2019|Contents]] &#x2022; [[outreach:Education/Newsletter/August 2019/Headlines|Headlines]] &#x2022; [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[outreach:Education/News/August 2019/Summer WikiCamp for secondary school students 2019 in Armenia|Summer WikiCamp for secondary school students 2019 in Armenia]] * [[outreach:Education/News/August 2019/Together, we can create an environment that promotes Quality Education|Together, we can create an environment that promotes Quality Education]] * [[outreach:Education/News/August 2019/International Days and pop culture motivate primary and secondary education students to write on Wikipedia and Wikidata|International Days and pop culture motivate primary and secondary education students to write on Wikipedia and Wikidata]] * [[outreach:Education/News/August 2019/Quality learning and recruiting students at Edu Wiki camp|Quality learning and recruiting students at Edu Wiki camp]] * [[outreach:Education/News/August 2019/We spend such wonderful days in WikiCamps that noone wants to return home|We spend such wonderful days in WikiCamps that noone wants to return home]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 01:00, 5 September 2019 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=19308048 --> == This Month in Education: September 2019 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" | <span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 8 &#x2022; Issue 9 &#x2022; September 2019</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/September 2019|Contents]] &#x2022; [[outreach:Education/Newsletter/September 2019/Headlines|Headlines]] &#x2022; [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> *[[:outreach:Education/News/September 2019/Learning history by expanding articles about novels|Learning history by expanding articles about novels]] *[[:outreach:Education/News/September 2019/Organizing the Education space at Wikimania 2019 - A conversation with Shani Evenstein|Organizing the Education space at Wikimania 2019 - A conversation with Shani Evenstein]] *[[:outreach:Education/News/September 2019/Wiki Goes to School is back in three cities in Indonesia|Wiki Goes to School is back in three cities in Indonesia]] *[[:outreach:Education/News/September 2019/Wikipedia workshop at the Summer IT School for Teachers|Wikipedia workshop at the Summer IT School for Teachers]] *[[:outreach:Education/News/September 2019/WikiChallenge Ecoles d'Afrique 2019 is over|WikiChallenge Ecoles d'Afrique 2019 is over]] *[[:outreach:Education/News/September 2019/Wikipedia Education Program launched in Bangladesh|Wikipedia Education Program held at Netrokona Government College, Bangladesh]] *[[:outreach:Education/News/September 2019/Stepanakert WikiClub turns 4!|Stepanakert WikiClub turns 4!]] *[[:outreach:Education/News/September 2019/Wikimedia Indonesia trained the trainers through WikiPelatih 2019|Wikimedia Indonesia trained the trainers through WikiPelatih 2019]] *[[:outreach:Education/News/September 2019/Students learning Wikipedia editing by attending Wikicamp at Nabran|Students learning Wikipedia editing by attending Wikicamp at Nabran]] *[[:outreach:Education/News/September 2019/What is happening at Wikimedia Space?|What is happening at Wikimedia Space?]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 19:34, 1 October 2019 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=19418815 --> == This Month in Education: October 2019 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" | <span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 8 &#x2022; Issue 10 &#x2022; October 2019</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/October 2019|Contents]] &#x2022; [[outreach:Education/Newsletter/October 2019/Headlines|Headlines]] &#x2022; [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> *[[outreach:Education/News/October 2019/Wikimedia Chile launched its new online course for school teachers|Wikimedia Chile launched its new online course for school teachers]] *[[outreach:Education/News/October 2019/Wikimedia Norway is developing an education program for Sámi students and universities teaching Sámi subjects|Wikimedia Norway is developing an education program for Sámi students and universities teaching Sámi subjects]] *[[outreach:Education/News/October 2019/Teachers Association of the Republic of Indonesia (PGRI) Keeps Improving Teachers’ Digital Literacy Through the Use of Wikipedia|Teachers Association of the Republic of Indonesia (PGRI) Keeps Improving Teachers’ Digital Literacy Through the Use of Wikipedia]] *[[outreach:Education/News/October 2019/Lectures on Wikipedia at the the University of Warsaw|Lectures on Wikipedia at the the University of Warsaw]] *[[outreach:Education/News/October 2019/Wikicamp in Armenia through the Eyes of Foreigners| Wikicamp in Armenia through the Eyes of Foreigners]] *[[outreach:Education/News/October 2019/New Wiki Education evaluation report of Wikidata courses published|New Wiki Education evaluation report of Wikidata courses published courses.]] *[[outreach:Education/News/October 2019/Youth Salon by VVIT WikiConnect along with Wikipedia & Education user group|Wikimedia 2030 Strategoy Youth Salon by VVIT WikiConnect]] *[[outreach:Education/News/October 2019/Wikimedia & Education Greenhouse – Highlights from the first unit of the online course|Wikimedia & Education Greenhouse – Highlights from the first unit of the online courses.]] *[[outreach:Education/News/September 2019/What is happening at Wikimedia Space?|What is happening at Wikimedia Space?]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 08:30, 25 October 2019 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=19436525 --> == This Month in Education: November 2019 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" | <span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 8 &#x2022; Issue 11 &#x2022; November 2019</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/October 2019|Contents]] &#x2022; [[outreach:Education/Newsletter/October 2019/Headlines|Headlines]] &#x2022; [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> *[[:outreach:Education/News/November 2019/GOES for Ghana|Wikimedians aim to make a difference in the lives of students in Ghana with support from the Wikimedia & Education Greenhouse]] *[[:outreach:Education/News/November 2019/The Third "Editatón WikiUNAM"|The Third "Editatón WikiUNAM"]] *[[:outreach:Education/News/November 2019/Spreading Free Knowledge in the Land of Minangkabau|Spreading Free Knowledge in the Land of Minangkabau]] *[[:outreach:Education/News/November 2019/What can we learn from the Open Education movement about attaining educational SDG in the digital age?|What can we learn from the Open Education movement about attaining educational SDG in the digital age?]] *[[:outreach:Education/News/November 2019/We are highlighting the work User:Ixocactus for his contributions in Wikimedia & Education‎| We are highlighting the work of User:Ixocactus this month‎]] *[[:outreach:Education/News/November 2019/“Olympic sports through history” on Serbian Wikipedia|“Olympic sports through history” on Serbian Wikipedia courses.]] *[[:outreach:Education/News/November 2019/Workshops with Wiki Club members|Workshops with Wiki Club members]] *[[:outreach:Education/News/November 2019/"Learning about other Culture" SEABA School, Lehragaga|"Learning about other Culture" SEABA School, Lehragaga.]] *[[:outreach:Education/News/November 2019/What is happening at Wikimedia Space?|What is happening at Wikimedia Space?]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 03:15, 29 November 2019 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=19589002 --> == This Month in Education: January 2020 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" | <span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 9 &bull; Issue 1 &bull; January 2020</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/January 2019|Contents]] &bull; [[outreach:Education/Newsletter/January 2019/Headlines|Headlines]] &bull; [[:m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[:outreach:Education/News/January 2020/Featured education community member of January 2020|Meet this month's featured Wikimedia & Education community member: User:Parvathisri]] * [[:outreach:Education/News/January 2020/Alva's college collaboration|Alva's college collaboration]] * [[:outreach:Education/News/January 2020/EtnoWiki strikes again!|EtnoWiki strikes again in Poland!]] * [[:outreach:Education/News/January 2020/Internship program: Engaging New Volunteers to Join the Community|Internship program: Engaging New Volunteers to Join the Community]] * [[:outreach:Education/News/January 2020/Joint translations as language studying tool in Karvachar’s Wikiclub|Joint translations as language studying tool in Karvachar’s Wikiclub]] * [[:outreach:Education/News/January 2020/Selet WikiSchool introduces Wikinews and other Wikimedia projects|Selet WikiSchool introduces Wikinews and other Wikimedia projects]] * [[:outreach:Education/News/January 2020/Training of Trainers for Teachers in South Sulawesi Was Organized For the First Time|Training of Trainers for Teachers in South Sulawesi Was Organized For the First Time]] * [[:outreach:Education/News/January 2020/Twenty video tutorials in Serbian language on editing Wikipedia|Twenty video tutorials in Serbian language on editing Wikipedia]] * [[:outreach:Education/News/January 2020/Updates from Wikimedia Education database edit-a-thon|Updates from Wikimedia Education database edit-a-thon]] * [[:outreach:Education/News/January 2020/Wiki Club Ohrid grows|Wiki Club Ohrid grows]] * [[:outreach:Education/News/January 2020/Wiki Masuk Sekolah (Wiki Goes to School) Involved the Students in Producing and Sharing Knowledge Through Wikipedia|Wiki Masuk Sekolah (Wiki Goes to School) Involved the Students in Producing and Sharing Knowledge Through Wikipedia]] * [[:outreach:Education/News/January 2020/Wikiclassroom as a New Means of Gaining Knowledge|Wikiclassroom as a New Means of Gaining Knowledge]] * [[:outreach:Education/News/January 2020/Wikimedia & Education Greenhouse – Highlights from the second unit of the online course|Wikimedia & Education Greenhouse – Highlights from the second unit of the online course]] * [[:outreach:Education/News/January 2020/WoALUG collaboration with educational institution BONEVET in Prishtina|WoALUG collaboration with educational institution BONEVET in Prishtina]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 07:26, 3 February 2020 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=19722205 --> == This Month in Education: February 2020 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" |<span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 9 &#x2022; Issue 1 &#x2022; February 2020</span> ----<span style="font-size:larger;">[[outreach:Education/Newsletter/February 2020|Contents]] &#x2022; [[outreach:Education/Newsletter/February 2020/Headlines|Headlines]] &#x2022; [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ----<span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[:outreach:Education/News/February 2020/Featured education community member of February 2020|Featured education community member of February 2020]] * [[:outreach:Education/News/February 2020/Wikipedia in Mayan Language|Wikipedia in Mayan Language]] * [[:outreach:Education/News/February 2020/Open Education Week - events with Wikimedia Poland|Open Education Week - events with Wikimedia Poland]] * [[:outreach:Education/News/February 2020/Youngest wikimedians ever editing Txikipedia|Youngest wikimedians ever editing Txikipedia]] * [[:outreach:Education/News/February 2020/Fashion and digital citizenship at Bath Spa University|Fashion and digital citizenship at Bath Spa University]] * [[:outreach:Education/News/February 2020/WoALUG and REC Albania continue their collaboration in Wikimedia Education|WoALUG and REC Albania continue their collaboration in Wikimedia Education]] * [[:outreach:Education/News/February 2020/Respati Project|Respati Project]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 22:06, 3 March 2020 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=19845865 --> == This Month in Education: March 2020 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" |<span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 9 &#x2022; Issue 3 &#x2022; March 2020</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/March 2020|Contents]] &#x2022; [[outreach:Education/Newsletter/March 2020/Headlines|Headlines]] &#x2022; [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[outreach:Education/News/March 2020/An Update on Wikimedia Indonesia’s Education Program|An Update on Wikimedia Indonesia’s Education Program]] * [[outreach:Education/News/March 2020/Education Program in CUC Sur, Jalisco, México|Education Program in CUC Sur, Jalisco, México]] * [[outreach:Education/News/March 2020/Featured education community member of March 2020|Meet this month's featured Wikimedia & Education community member: Amber Berson]] * [[outreach:Education/News/March 2020/Enhancing Armenian Wikipedia with professional articles|Enhancing Armenian Wikipedia with professional articles]] * [[outreach:Education/News/March 2020/How collaborations and perseverance contributed to an especially impactful educational project|How collaborations and perseverance contributed to an especially impactful educational project]] * [[outreach:Education/News/March 2020/Wikimedia Argentina carried out the first training program in education and Human Rights for the Wikimedia Movement|Wikimedia Argentina carried out the first training program in education and Human Rights for the Wikimedia Movement]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 15:30, 30 March 2020 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=19864438 --> == This Month in Education: April 2020 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" | <span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 9 &#x2022; Issue 4 &#x2022; April 2020</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/April 2020|Contents]] &#x2022; [[outreach:Education/Newsletter/April 2020/Headlines|Headlines]] &#x2022; [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[outreach:Education/News/April 2020/ Wikipedia Reveals New Sides of Translation|Wikipedia Reveals New Sides of Translation]] * [[outreach:Education/News/April 2020/Education Webinars organized by Wikimedia México|Education Webinars organized by Wikimedia México]] * [[outreach:Education/News/April 2020/Fact checking tool with library under cc-license|Fact checking tool with library under cc-license]] * [[outreach:Education/News/April 2020/Fast help for schools: An interactive platform for Open Educational Resources|Fast help for schools: An interactive platform for Open Educational Resources]] * [[outreach:Education/News/April 2020/Featured education community member of April 2020|Meet this month's featured Wikimedia & Education community member]] * [[outreach:Education/News/April 2020/Wiki Club Ashesi Welcomes Onboard a New Patron|Wiki Club Ashesi Welcomes Onboard a New Patron]] * [[outreach:Education/News/April 2020/Wiki-school project with Wikimedia Poland|Wiki-school. A new program for teachers in Poland]] * [[outreach:Education/News/April 2020/Wikimedia Serbia was organized action on improving students assignments on Wikipedia|Wikimedia Serbia was organized action on improving students assignments on Wikipedia]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 10:45, 5 May 2020 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=20024483 --> == This Month in Education: May 2020 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" |<span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 9 &#x2022; Issue 5 &#x2022; May 2020</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/May 2020|Contents]] &#x2022; [[outreach:Education/Newsletter/May 2020/Headlines|Headlines]] &#x2022; [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issuse</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[outreach:Education/News/May 2020/EduWiki challenge México by Wikimedia México|EduWiki challenge México by Wikimedia México]] * [[outreach:Education/News/May 2020/Featured education community member of May 2020|Featured education community member of May 2020]] * [[outreach:Education/News/May 2020/Sharing Wikimedia Education Projects in the Philippines|Sharing Wikimedia Education Projects in the Philippines]] * [[outreach:Education/News/May 2020/Turkish professors are giving Wikipedia assignments during Covid-19 days|Turkish professors are giving Wikipedia assignments during Covid-19 days]] * [[outreach:Education/News/May 2020/Wikidata introduced in Faculty of Economics, University of Belgrade|Wikidata introduced in Faculty of Economics, University of Belgrade]] * [[outreach:Education/News/May 2020/Wikipedia as career counseling tool for teenagers|Wikipedia as career counseling tool for teenagers]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 16:39, 10 June 2020 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=20130275 --> == This Month in Education: June 2020 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" |<span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 9 &#x2022; Issue 6 &#x2022; June 2020</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/June 2020|Contents]] &#x2022; [[outreach:Education/Newsletter/June 2020/Headlines|Headlines]] &#x2022; [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issuse</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[outreach:Education/News/June 2020/Understanding Wikimedia Affiliates Evaluation in Education Report|Understanding Wikimedia Affiliates Evaluation in Education Report]] * [[outreach:Education/News/June 2020/Understanding Wikimedia Community as Research Fellows|Understanding Wikimedia Community as Research Fellows]] * [[outreach:Education/News/June 2020/Participants of Wiki/Ponder online workshop in Kosovo edit Wikipedia|Participants of Wiki/Ponder online workshop in Kosovo edit Wikipedia]] * [[outreach:Education/News/June 2020/Wikimedia & Education Greenhouse – Celebrating the final unit of the online course!|Wikimedia & Education Greenhouse – Celebrating the final unit of the online course!]] * [[outreach:Education/News/June 2020/Wikipedia in schools competing for innovations in teaching award|Wikipedia in schools competing for innovations in teaching award]] * [[outreach:Education/News/June 2020/Featured education community member of June 2020|Meet this month's featured Wikimedia & Education community member: Oleh Kushch]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 03:54, 24 June 2020 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=20166080 --> == This Month in Education: July 2020 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" |<span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 9 &#x2022; Issue 7 &#x2022; July 2020</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/July 2020|Contents]] &#x2022; [[outreach:Education/Newsletter/July 2020/Headlines|Headlines]] &#x2022; [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issuse</span><div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[outreach:Education/News/July 2020/About Education at the Wikimedia Polska Conference|About Education at the Wikimedia Polska Conference]] * [[outreach:Education/News/July 2020/Featured education community member of July 2020|Featured education community member]] * [[outreach:Education/News/July 2020/The importance of having an Education and Human Rights Program|The importance of having an Education and Human Rights Program]] * [[outreach:Education/News/July 2020/The Welsh Wiki-Education project|The Welsh Wiki-Education project]] * [[outreach:Education/News/July 2020/Wikimedia Chile faces the challenge of mandatory virtuality|Wikimedia Chile faces the challenge of mandatory virtuality]] * [[outreach:Education/News/July 2020/WoALUG and Canadian Institute of Technology write about women in tech|WoALUG and Canadian Institute of Technology write about women in tech]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 05:27, 5 August 2020 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=20337242 --> == This Month in Education: August 2020 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" |<span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 9 • Issue 8 • August 2020</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/August 2020|Contents]] • [[outreach:Education/Newsletter/August 2020/Headlines|Headlines]] • [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issuse</span><div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[outreach:Education/News/August 2020/Collaboration between Karvachar Armath laboratory and Karvachar’s Wikiclub as a new educational platform for the teenagers|Collaboration between Karvachar Armath laboratory and Karvachar’s Wikiclub as a new educational platform for the teenagers]] * [[outreach:Education/News/August 2020/Education cycle “Wikipedia, the free encyclopedia: an instructional strategy for the teaching practice” organized by the Faculty of Education Sciences of the Universidad Autónoma de Tlaxcala and Wikimedia México.|Education cycle “Wikipedia, the free encyclopedia: an instructional strategy for the teaching practice”]] * [[outreach:Education/News/August 2020/3rd edition of Wikipedia Education Program in Hebron, Palestine. (COVID-19 edition)|3rd edition of Wikipedia Education Program in Hebron, Palestine. (COVID-19 edition)]] * [[outreach:Education/News/August 2020/Introductory Wikipedia Workshop with Future Engineers: First Step of Education Program|Introductory Wikipedia Workshop with Future Engineers: First Step of Education Program]] * [[outreach:Education/News/August 2020/A picture is worth a thousand words: history students research pictures on Commons|A picture is worth a thousand words: history students research pictures on Commons]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 13:33, 23 August 2020 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=20345269 --> == This Month in Education: September 2020 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" |<span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 9 • Issue 9 • September 2020</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/September 2020|Contents]] • [[outreach:Education/Newsletter/September 2020/Headlines|Headlines]] • [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issuse</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[outreach:Education/News/September 2020/Active autumn in the Polish wiki-education|Active autumn in the Polish wiki-education]] * [[outreach:Education/News/September 2020/Cycle "Caminos y voces de la educación con Wikipedia"|Cycle "Caminos y voces de la educación con Wikipedia"]] * [[outreach:Education/News/September 2020/Featured education community member of September 2020|Featured education community member of September 2020]] * [[outreach:Education/News/September 2020/The Use of Wikipedia and Wikimedia Commons as tool for Module Development in the Philippines|The Use of Wikipedia and Wikimedia Commons as tool for Module Development in the Philippines]] * [[outreach:Education/News/September 2020/Wikimedia Indonesia Education Team Launched Their Books About Wikipedia|Wikimedia Indonesia Education Team Launched Their Books About Wikipedia]] * [[outreach:Education/News/September 2020/Wikimedia Serbia is organizing the first online Edu Wiki camp|Wikimedia Serbia is organizing the first online Edu Wiki camp]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 12:49, 23 September 2020 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=20463283 --> == This Month in Education: October 2020 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" |<span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 9 • Issue 10 • October 2020</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/October 2020|Contents]] • [[outreach:Education/Newsletter/October 2020/Headlines|Headlines]] • [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issuse</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[outreach:Education/News/October 2020/Collegiate Students Fight Historical Revisionism Through Online Wikipedia Edit-a-thon|Collegiate Students Fight Historical Revisionism Through Online Wikipedia Edit-a-thon]] * [[outreach:Education/News/October 2020/Digital skills using Wikimedia Art + Feminism|Digital skills using Wikimedia Art + Feminism]] * [[outreach:Education/News/October 2020/Editathon “¡No se olvida!” (We don’t forget!)|Editathon “¡No se olvida!” (We don’t forget!)]] * [[outreach:Education/News/October 2020/Education news bytes|Education news bytes]] * [[outreach:Education/News/October 2020/Featured education community member of October 2020|Featured education community member of October 2020]] * [[outreach:Education/News/October 2020/Teaching Wikipedia at University of Tromsø with support from the Sámi Parliament|Teaching Wikipedia at University of Tromsø with support from the Sámi Parliament]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 12:59, 25 October 2020 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=20514345 --> == This Month in Education: November 2020 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" |<span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 9 • Issue 11 • November 2020</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/November 2020|Contents]] • [[outreach:Education/Newsletter/November 2020/Headlines|Headlines]] • [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issuse</span><div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[outreach:Education/News/November 2020/Celebrating 10 years of student editing in the United States and Canada|Celebrating 10 years of student editing in the United States and Canada]] * [[outreach:Education/News/November 2020/Cooperation in digital education – Wikimedia Polska conference|Cooperation in digital education – Wikimedia Polska conference]] * [[outreach:Education/News/November 2020/Education Team 2020 Year End Review|Education Team 2020 Year End Review]] * [[outreach:Education/News/November 2020/Featured education community members of 2020|Featured education community members of 2020]] * [[outreach:Education/News/November 2020/Fifteen years of implementation of the Wikipedia Education Program in Serbia|Fifteen years of implementation of the Wikipedia Education Program in Serbia]] * [[outreach:Education/News/November 2020/Hablon User Group and UP Internet Freedom Network Wikipedia Edit-a-thon|Hablon User Group and UP Internet Freedom Network Wikipedia Edit-a-thon]] * [[outreach:Education/News/November 2020/Online trainings on Wikipedia with high school students of Kosova|Online trainings on Wikipedia with high school students of Kosova]] * [[outreach:Education/News/November 2020/Photographics and free culture training in Cameroon and Switzerland|Photographics and free culture training in Cameroon and Switzerland]] * [[outreach:Education/News/November 2020/The article about Wiki-education in the science magazine|The article about Wiki-education in the science magazine]] * [[outreach:Education/News/November 2020/The first Online EduWiki Camp in Serbia|The first Online EduWiki Camp in Serbia]] * [[outreach:Education/News/November 2020/Wikimedia Mexico’s Education Program celebrates Open Access Week 2020|Wikimedia Mexico’s Education Program celebrates Open Access Week 2020]] * [[outreach:Education/News/November 2020/Wikipedia as a Tool to Educate and to Be Educated|Wikipedia as a Tool to Educate and to Be Educated]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 07:14, 17 December 2020 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=20831200 --> == This Month in Education: January 2021 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" |<span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 10 • Issue 1 • January 2021</span> ----<span style="font-size:larger;">[[outreach:Education/Newsletter/January 2021|Contents]] • [[outreach:Education/Newsletter/January 2021/Headlines|Headlines]] • [[metawiki:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ----<span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issuse</span><div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[outreach:Education/News/January 2021/Featured education community member of January 2021|Featured education community member of January 2021]] * [[outreach:Education/News/January 2021/Open Education Global 2020 Conference|Open Education Global 2020 Conference]] * [[outreach:Education/News/January 2021/Reading Wikipedia in Bolivia|Reading Wikipedia in Bolivia]] * [[outreach:Education/News/January 2021/The impact of war on young Wikimedians in Stepanakert|The impact of war on young Wikimedians in Stepanakert]] * [[outreach:Education/News/January 2021/The Possibility of Open-Access Learning Portals in the Philippines|The Possibility of Open-Access Learning Portals in the Philippines]] * [[outreach:Education/News/January 2021/Training Resources about Author’s Rights published by Wiki in Africa|Training Resources about Author’s Rights published by Wiki in Africa]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 17:26, 23 January 2021 (UTC)</div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=20974633 --> == This Month in Education: January 2021 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" |<span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 10 • Issue 1 • January 2021</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/January 2021|Contents]] • [[outreach:Education/Newsletter/January 2021/Headlines|Headlines]] • [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issuse</span><div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[outreach:Education/News/January 2021/Featured education community member of January 2021|Featured education community member of January 2021]] * [[outreach:Education/News/January 2021/Open Education Global 2020 Conference|Open Education Global 2020 Conference]] * [[outreach:Education/News/January 2021/Reading Wikipedia in Bolivia|Reading Wikipedia in Bolivia]] * [[outreach:Education/News/January 2021/The impact of war on young Wikimedians in Stepanakert|The impact of war on young Wikimedians in Stepanakert]] * [[outreach:Education/News/January 2021/The Possibility of Open-Access Learning Portals in the Philippines|The Possibility of Open-Access Learning Portals in the Philippines]] * [[outreach:Education/News/January 2021/Training Resources about Author’s Rights published by Wiki in Africa|Training Resources about Author’s Rights published by Wiki in Africa]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 15:35, 24 January 2021 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=21000945 --> == This Month in Education: February 2021 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" |<span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 10 • Issue 2 • February 2021</span> ----<span style="font-size:larger;">[[outreach:Education/Newsletter/February 2021|Contents]] • [[outreach:Education/Newsletter/February 2021/Headlines|Headlines]] • [[metawiki:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ----<span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issuse</span><div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[outreach:Education/News/February 2021/Education news bytes|Wikimedia Education news bytes]] * [[outreach:Education/News/February 2021/Featured education community member of February 2021|Featured education community member of February 2021]] * [[outreach:Education/News/February 2021/Karvachar Wikiclub continues its activities online|Karvachar Wikiclub continues its activities online]] * [[outreach:Education/News/February 2021/Over 4,000 references added|Over 4,000 more references added! 1Lib1Ref campaign in Poland]] * [[outreach:Education/News/February 2021/Philippines Climate Change Translate-a-thon|Philippines Climate Change Translate-a-thon]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 07:33, 24 February 2021 (UTC)</div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=21035028 --> == This Month in Education: March 2021 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" |<span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 10 • Issue 3 • March 2021</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/March 2021|Contents]] • [[outreach:Education/Newsletter/March 2021/Headlines|Headlines]] • [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issuse</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[outreach:Education/News/March 2021/A Wikipedia Webinar for Indonesian Women Teachers|A Wikipedia Webinar for Indonesian Women Teachers]] * [[outreach:Education/News/March 2021/Educational program of GLAM Macedonia|Educational program of GLAM Macedonia]] * [[outreach:Education/News/March 2021/Filling Gaps - the Conference about Education in Poland|Filling the Gaps & Open Education Week]] * [[outreach:Education/News/March 2021/Featured education community member of March 2021|Meet this month's featured Wikimedia & Education community member: Bara'a Zama'reh]] * [[outreach:Education/News/March 2021/Using Wikipedia and Bridging the Gender Gap: In-Service training for Teachers in Philippines|Using Wikipedia and Bridging the Gender Gap: In-Service training for Teachers in Philippines]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 11:46, 26 March 2021 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=21247888 --> == This Month in Education: April 2021 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" |<span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 10 • Issue 4 • April 2021</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/April 2021|Contents]] • [[outreach:Education/Newsletter/April 2021/Headlines|Headlines]] • [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issuse</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[outreach:Education/News/April 2021/Collaboration with Brusov State University|Collaboration with Brusov State University]] * [[outreach:Education/News/April 2021/Editing contest "Meet Russia"|Editing contest "Meet Russia"]] * [[outreach:Education/News/April 2021/Educational project: Wikipedia at the University with the University Center for Economic-Administrative Sciences|Educational project: Wikipedia at the University with the University Center for Economic-Administrative Sciences (Centro Universitario de Ciencias Económico Administrativas (CUCEA)) of the University of Guadalajara]] * [[outreach:Education/News/April 2021/Regional Meeting of Latin American Education by the EWOC|Regional Meeting of Latin American Education by the EWOC]] * [[outreach:Education/News/April 2021/Students of the Faculty of Philosophy in Belgrade have started an internship program|Students of the Faculty of Philosophy in Belgrade have started an internship program]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 22:48, 25 April 2021 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=21372399 --> == This Month in Education: May 2021 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" |<span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 10 • Issue 5 • May 2021</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/May 2021|Contents]] • [[outreach:Education/Newsletter/May 2021/Headlines|Headlines]] • [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[outreach:Education/News/May 2021/A Multimedia-Rich Wikiversity MOOC from Brazil|A Multimedia-Rich Wikiversity MOOC from Brazil]] * [[outreach:Education/News/May 2021/Featured education community member of May 2021|Meet this month's featured Wikimedia & Education community member: Maria Weronika Kmoch]] * [[outreach:Education/News/May 2021/Offline workshop with Nikola Koperniku High School in Albania|Offline workshop with Nikola Koperniku High School in Albania]] * [[outreach:Education/News/May 2021/Wiki Education Program Organized with the University Students for the First time in Bangladesh|Wiki Education Program Organized with the University Students for the First time in Bangladesh]] * [[outreach:Education/News/May 2021/Wikimedia Commons workshop with high school students in Kosovo; Workshop with telecommunication students at University of Prishtina|Wikimedia Commons workshop with high school students in Kosovo]] * [[outreach:Education/News/May 2021/Wikipedia training for the Safeguardians of the Intangible Cultular Heritage|Wikipedia training for the Bearers of Intangible Cultural Heritage in Poland]] * [[outreach:Education/News/May 2021/“Writing a Wikipedia article isn’t as difficult and unimaginable as it seems”: A case for Wikipedia Education Program in Ukraine|“Writing a Wikipedia article isn’t as difficult and unimaginable as it seems”: A case for Wikipedia Education Program in Ukraine]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 17:37, 27 May 2021 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=21425406 --> == This Month in Education: June 2021 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" |<span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 10 • Issue 6 • June 2021</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/June 2021|Contents]] • [[outreach:Education/Newsletter/June 2021/Headlines|Headlines]] • [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[outreach:Education/News/June 2021/Children writing for an encyclopedia – is it possible?|Can children write articles for a wiki encyclopedia?]] * [[outreach:Education/News/June 2021/Editing contest "Biosphere reserves in the world"|Editing contest "Biosphere reserves in the world"]] * [[outreach:Education/News/June 2021/Training & workshop on Wikidata and Wikimedia Commons with students from Municipal Learning Center, Gurrakoc|Training & workshop on Wikidata and Wikimedia Commons with students from Municipal Learning Center, Gurrakoc]] * [[outreach:Education/News/June 2021/Wiki for Human Rights Campaign in the Philippines|Wiki for Human Rights Campaign in the Philippines]] * [[outreach:Education/News/June 2021/Wiki-School program in Poland at the end of school year|Wikipedia makes children and teachers happy!]] * [[outreach:Education/News/June 2021/Workshop with students of Language Faculty of Philology, University of Prishtina "Hasan Prishtina"|Workshop with the students of Language Faculty of Philology, University of Prishtina "Hasan Prishtina"]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 19:57, 23 June 2021 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=21553405 --> == This Month in Education: July 2021 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" |<span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 10 • Issue 7 • July 2021</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/July 2021|Contents]] • [[outreach:Education/Newsletter/July 2021/Headlines|Headlines]] • [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[outreach:Education/News/July 2021/UHI Editathon celebrates 10 years as a university|University celebrates 10th anniversary with an Editathon]] * [[outreach:Education/News/July 2021/A paper on Students' Attitudes Towards the Use of Wikipedia|A paper on Students' Attitudes Towards the Use of Wikipedia]] * [[outreach:Education/News/July 2021/Announcing the Training of Trainers program for Reading Wikipedia in the Classroom!|Announcing the Training of Trainers program for "Reading Wikipedia in the Classroom"]] * [[outreach:Education/News/July 2021/MOOC Conocimiento Abierto y Software Libre|MOOC Conocimiento Abierto y Software Libre]] * [[outreach:Education/News/July 2021/Leamos Wikipedia en Bolivia|Updates on the Leamos Wikipedia en Bolivia 2021]] * [[outreach:Education/News/July 2021/E-lessons on Wikipedia from Wikimedia Polska|Virtual lessons on Wikipedia from Wikimedia Polska for schools]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 19:32, 3 August 2021 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=21829196 --> == This Month in Education: August 2021 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" |<span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 10 • Issue 8 • August 2021</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/August 2021|Contents]] • [[outreach:Education/Newsletter/August 2021/Headlines|Headlines]] • [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[outreach:Education/News/August 2021/Workshop for the Teachers from Poland|GLAM-wiki Summer in the City: Polish Teachers met in Warsaw]] * [[outreach:Education/News/August 2021/Wikipedia for School – our largest article contest for Ukrainian teachers|Wikipedia for School – our largest article contest for Ukrainian teachers]] * [[outreach:Education/News/August 2021/The importance of Social Service: Modality of educational linkage with ITESM, Querétaro campus and Wikimedia Mexico|The importance of Social Service: Modality of educational linkage with ITESM, Querétaro campus and Wikimedia Mexico]] * [[outreach:Education/News/August 2021/"Searching for the unschooling vibes around Wikipedia" at the Wikimania 2021|Wikimania 2021 and the unschooling vibes around Wikipedia by Wikimedia Polska, Education team]] * [[outreach:Education/News/August 2021/Open Foundation West Africa Introduces KIWIX Offline to the National Association of Graduate Teachers|Open Foundation West Africa Introduces KIWIX Offline to the National Association of Graduate Teachers]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 13:37, 25 August 2021 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=21914750 --> == This Month in Education: September 2021 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" |<span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 10 • Issue 9 • September 2021</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/September 2021|Contents]] • [[outreach:Education/Newsletter/September 2021/Headlines|Headlines]] • [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[outreach:Education/News/September 2021/Cultural history on Wikipedia|Cultural history on Wikipedia]] * [[outreach:Education/News/September 2021/Education program in Ukraine is finally back to offline|Education program in Ukraine is finally back to offline!]] * [[outreach:Education/News/September 2021/Reading Wikipedia in the Classroom Module Distribution in the Philippines|Reading Wikipedia in the Classroom Module Distribution in the Philippines]] * [[outreach:Education/News/September 2021/Senior Citizens WikiTown 2021: Týn nad Vltavou|Senior Citizens WikiTown 2021: Týn nad Vltavou]] * [[outreach:Education/News/September 2021/WikiXLaEducación: New contest to include articles about education on Wikipedia|#WikiXLaEducación: New contest to include articles about education on Wikipedia]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:Romaine|Romaine]] 19:42, 26 September 2021 (UTC)</div> <!-- Message sent by User:Romaine@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=22072998 --> == This Month in Education: October 2021 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" |<span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 10 • Issue 10 • October 2021</span> ---- <span style="font-size:larger;">[[outreach:Education/Newsletter/October 2021|Contents]] • [[outreach:Education/Newsletter/October 2021/Headlines|Headlines]] • [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[outreach:Education/News/October 2021/1st joint contest Wikimedia UG Georgia and the Ministry of Education of Georgia.|1st joint contest Wikimedia UG Georgia and the Ministry of Education of Georgia]] * [[outreach:Education/News/October 2021/Promoting more inclusive and equitable support for the Wikimedia Education community|Promoting more inclusive and equitable support for the Wikimedia Education community]] * [[outreach:Education/News/October 2021/The Second Online EduWiki Camp in Serbia|The Second Online EduWiki Camp in Serbia]] * [[outreach:Education/News/October 2021/University courses in the UK|Higher and further education courses in the UK]] * [[outreach:Education/News/October 2021/Wikipedia on Silesia Cieszyn in Poland|Wikipedia on Silesia Cieszyn in Poland and in Czech Republic]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 15:40, 26 October 2021 (UTC)</div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=22208730 --> == This Month in Education: November 2021 == {| style="width:70%;" | valign="top" style="text-align:center; border:1px gray solid; padding:1em;" |<span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 10 • Issue 11 • November 2021</span> ---- <span style="font-size:larger;">[[m:Education/Newsletter/November 2021|Contents]] • [[m:Education/Newsletter/November 2021/Headlines|Headlines]] • [[m:Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[m:Education/News/November 2021/We talked about EduWiki Outreach Collaborators and how Wikimedia Serbia played a role being a part of it|We talked about EduWiki Outreach Collaborators and how Wikimedia Serbia played a role being a part of it]] * [[m:Education/News/November 2021/Welcome to Meta!|Welcome to Meta!]] * [[m:Education/News/November 2021/Wikipedia Education Program in Ukraine in 2021|Wikipedia Education Program in Ukraine in 2021]] * [[m:Education/News/November 2021/Wikipedia and Education Mentorship Program-Serbia and Philippines Partnership|Wikipedia and Education Mentorship Program-Serbia and Philippines Partnership]] * [[m:Education/News/November 2021/Launch of the Wikimedia Research Fund!|Launch of the Wikimedia Research Fund!]] * [[m:Education/News/November 2021/Education projects in the Land of Valencia|Education projects in the Land of Valencia]] * [[m:Education/News/November 2021/A Hatch-Tyap-Wikipedia In-person Training Event|A Hatch-Tyap-Wikipedia In-person Training Event]] * [[m:Education/News/November 2021/Celebrating Sq Wikipedia Birthday with the Vasil Kamami High School students|Celebrating Sq Wikipedia Birthday with the Vasil Kamami High School students]] * [[m:Education/News/November 2021/Celebrating Wikidata with the Nikola Koperniku High School students|Celebrating Wikidata with the Nikola Koperniku High School students]] </div> |} <div style="margin-top:10px; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 16:18, 21 November 2021 (UTC)</div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=22360687 --> == This Month in Education: January 2022 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span><br/> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 11 • Issue 1 • January 2022</span> ---- <span style="font-size:larger;">[[m:Special:MyLanguage/Education/Newsletter/January 2022|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/January 2022/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span></div> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/January 2022/30-h Wikipedia Article Writing Challenge|30-h Wikipedia Article Writing Challenge]] * [[m:Special:MyLanguage/Education/News/January 2022/Announcing Wiki Workshop 2022|Announcing Wiki Workshop 2022]] * [[m:Special:MyLanguage/Education/News/January 2022/Final exhibition about Cieszyn Silesia region|Final exhibition about Cieszyn Silesia region]] * [[m:Special:MyLanguage/Education/News/January 2022/Join us this February for the EduWiki Week|Join us this February for the EduWiki Week]] * [[m:Special:MyLanguage/Education/News/January 2022/Offline Education project WikiChallenge closed its third edition|Offline Education project WikiChallenge closed its third edition]] * [[m:Special:MyLanguage/Education/News/January 2022/Reading Wikipedia in the Classroom ToT Experience of a Filipina Wikimedian|Reading Wikipedia in the Classroom ToT Experience of a Filipina Wikimedian]] * [[m:Special:MyLanguage/Education/News/January 2022/Welcoming new trainers of the Reading Wikipedia in the Classroom program|Welcoming new trainers of the Reading Wikipedia in the Classroom program]] * [[m:Special:MyLanguage/Education/News/January 2022/Wikimedia Israel’s education program: Students enrich Hebrew Wiktionary with Biblical expressions still in use in modern Hebrew|Wikimedia Israel’s education program: Students enrich Hebrew Wiktionary with Biblical expressions still in use in modern Hebrew]] </div></div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 17:28, 24 January 2022 (UTC)</div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=22669905 --> == This Month in Education: February 2022 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> {{int:please-translate}} <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 11 • Issue 2 • February 2022</span> ---- <span style="font-size:larger;">[[m:Special:MyLanguage/Education/Newsletter/February 2022|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/February 2022/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1; width:100%;">In This Issue</div> </div> <div style="column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/February 2022/Open Foundation West Africa Expands Open Movement With UHAS|Open Foundation West Africa Expands Open Movement With UHAS]] * [[m:Special:MyLanguage/Education/News/February 2022/Celebrating the 18th anniversary of Ukrainian Wikipedia|Celebrating the 18th anniversary of Ukrainian Wikipedia]] * [[m:Special:MyLanguage/Education/News/February 2022/Integrating Wikipedia in the academic curriculum in a university in Mexico|Integrating Wikipedia in the academic curriculum in a university in Mexico]] * [[m:Special:MyLanguage/Education/News/February 2022/Results of "Reading Wikipedia" workshop in the summer school of Plan Ceibal in Uruguay|Results of "Reading Wikipedia" workshop in the summer school of Plan Ceibal in Uruguay]] * [[m:Special:MyLanguage/Education/News/February 2022/WikiFundi, offline editing plateform : last release notes and how-tos|WikiFundi, offline editing plateform : last release notes and how-tos]] * [[m:Special:MyLanguage/Education/News/February 2022/Writing Wikipedia as an academic assignment in STEM fields|Writing Wikipedia as an academic assignment in STEM fields]] * [[m:Special:MyLanguage/Education/News/February 2022/The Learning and Connection – 1Lib1Ref with African Librarians|The Learning and Connection – 1Lib1Ref with African Librarians]] </div> </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 15:09, 28 February 2022 (UTC)</div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=22886200 --> == This Month in Education: March 2022 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 11 • Issue 3 • March 2022</span> ---- <span style="font-size:larger;">[[m:Special:MyLanguage/Education/Newsletter/March 2022|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/March 2022/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span></div> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/March 2022/Arte+Feminismo Pilipinas:Advocacy on Women Empowerment|Arte+Feminismo Pilipinas:Advocacy on Women Empowerment]] * [[m:Special:MyLanguage/Education/News/March 2022/The edit-a-thon on Serbian Wikipedia on the occasion of Edu Wiki Week|The edit-a-thon on Serbian Wikipedia on the occasion of Edu Wiki Week]] * [[m:Special:MyLanguage/Education/News/March 2022/Call for Participation: Higher Education Survey|Call for Participation: Higher Education Survey]] * [[m:Special:MyLanguage/Education/News/March 2022/Collection of Good Practices in Wikipedia Education|Collection of Good Practices in Wikipedia Education]] * [[m:Special:MyLanguage/Education/News/March 2022/Conversation: Open education in the Wikimedia Movement views from Latin America|Conversation: Open education in the Wikimedia Movement views from Latin America]] * [[m:Special:MyLanguage/Education/News/March 2022/EduWiki Week 2022, celebrations and learnings|EduWiki Week 2022, celebrations and learnings]] * [[m:Special:MyLanguage/Education/News/March 2022/EduWiki Week in Armenia|EduWiki Week in Armenia]] * [[m:Special:MyLanguage/Education/News/March 2022/Open Education Week at the Universidad Autónoma de Nuevo León|Open Education Week at the Universidad Autónoma de Nuevo León]] * [[m:Special:MyLanguage/Education/News/March 2022/Wikipedia + Education Talk With Leonard Hagan|Wikipedia + Education Talk With Leonard Hagan]] * [[m:Special:MyLanguage/Education/News/March 2022/Wikimedia Israel cooperates with Yad Vashem in developing a training course for teachers|Wikimedia Israel cooperates with Yad Vashem in developing a training course for teachers]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 16:57, 25 March 2022 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=23020683 --> == This Month in Education: April 2022 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 11 • Issue 4 • April 2022</span> ---- <span style="font-size:larger;">[[m:Special:MyLanguage/Education/Newsletter/April 2022|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/April 2022/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span></div> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/April 2022/Audio-Educational Seminar of Wikimedia Mexico|Audio-Educational Seminar of Wikimedia Mexico]] * [[m:Special:MyLanguage/Education/News/April 2022/Dagbani Wikimedians using digital TV broadcast to train Wikipedia contributors in Ghana|Dagbani Wikimedians using digital TV broadcast to train Wikipedia contributors in Ghana]] * [[m:Special:MyLanguage/Education/News/April 2022/Digital Education & The Open Space With Herbert Acheampong|Digital Education & The Open Space With Herbert Acheampong]] * [[m:Special:MyLanguage/Education/News/April 2022/HerStory walks as a part of edit-a-thons|HerStory walks as a part of edit-a-thons]] * [[m:Special:MyLanguage/Education/News/April 2022/Join us for Wiki Workshop 2022|Join us for Wiki Workshop 2022]] * [[m:Special:MyLanguage/Education/News/April 2022/The youngest member of Tartu Wikiclub is 15-year-old student|The youngest member of Tartu Wikiclub is 15-year-old student]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 12:51, 24 April 2022 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=23177152 --> == This Month in Education: May 2022 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 11 • Issue 5 • May 2022</span> ---- <span style="font-size:larger;">[[m:Special:MyLanguage/Education/Newsletter/May 2022|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/May 2022/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span></div> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[Education/News/May 2022/Wiki Hackathon in Kwara State|Wiki Hackathon in Kwara State]] * [[Education/News/May 2022/Introduction of the Wikimedia Fan Club to Kwara State University Malete|Introduction of the Wikimedia Fan Club to Kwara State University Malete]] * [[Education/News/May 2022/Education in Kosovo|Education in Kosovo]] * [[Education/News/May 2022/Bringing the Wikiprojects to the Island of Catanduanes|Bringing the Wikiprojects to the Island of Catanduanes]] * [[Education/News/May 2022/Tyap Wikipedia Goes Live|Tyap Wikipedia Goes Live]] * [[Education/News/May 2022/Spring 1Lib1Ref edition in Poland|Spring 1Lib1Ref edition in Poland]] * [[Education/News/May 2022/Tyap Editors Host Maiden Wiktionary In-person Training Workshop|Tyap Editors Host Maiden Wiktionary In-person Training Workshop]] * [[Education/News/May 2022/Wikibooks project in teaching|Wikibooks project in teaching]] * [[Education/News/May 2022/Africa Eduwiki Network Hosted Conversation about Wikimedian in Education with Nebojša Ratković|Africa Eduwiki Network Hosted Conversation about Wikimedian in Education with Nebojša Ratković]] * [[Education/News/May 2022/My Journey In The Wiki-Space By Thomas Baah|My Journey In The Wiki-Space By Thomas Baah]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education| Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 02:43, 1 June 2022 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=23282386 --> == This Month in Education: May 2022 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:40px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:20px; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif; width:900px;"> Volume 11 • Issue 5 • May 2022</span> ---- <span style="font-size:larger;">[[m:Special:MyLanguage/Education/Newsletter/May 2022|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/May 2022/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</span> ---- <span style="color:white; font-size:26px; font-family:Montserrat; display:block; background:#92BFB1; width:100%;">In This Issue</span></div> <div style="text-align: left; column-count: 2; column-width: 35em; -moz-column-count: 2; -moz-column-width: 35em; -webkit-column-count: 2; -webkit-column-width: 35em;"> * [[m:Education/News/May 2022/Wiki Hackathon in Kwara State|Wiki Hackathon in Kwara State]] * [[m:Education/News/May 2022/Introduction of the Wikimedia Fan Club to Kwara State University Malete|Introduction of the Wikimedia Fan Club to Kwara State University Malete]] * [[m:Education/News/May 2022/Education in Kosovo|Education in Kosovo]] * [[m:Education/News/May 2022/Bringing the Wikiprojects to the Island of Catanduanes|Bringing the Wikiprojects to the Island of Catanduanes]] * [[m:Education/News/May 2022/Tyap Wikipedia Goes Live|Tyap Wikipedia Goes Live]] * [[m:Education/News/May 2022/Spring 1Lib1Ref edition in Poland|Spring 1Lib1Ref edition in Poland]] * [[m:Education/News/May 2022/Tyap Editors Host Maiden Wiktionary In-person Training Workshop|Tyap Editors Host Maiden Wiktionary In-person Training Workshop]] * [[m:Education/News/May 2022/Wikibooks project in teaching|Wikibooks project in teaching]] * [[m:Education/News/May 2022/Africa Eduwiki Network Hosted Conversation about Wikimedian in Education with Nebojša Ratković|Africa Eduwiki Network Hosted Conversation about Wikimedian in Education with Nebojša Ratković]] * [[m:Education/News/May 2022/My Journey In The Wiki-Space By Thomas Baah|My Journey In The Wiki-Space By Thomas Baah]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education| Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 02:54, 1 June 2022 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=23351176 --> == This Month in Education: June 2022 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 11 • Issue 6 • June 2022</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/June 2022|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/June 2022/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/June 2022/Black Lunch Table: Black History Month with Igbo Wikimedians User Group|Black Lunch Table: Black History Month with Igbo Wikimedians User Group]] * [[m:Special:MyLanguage/Education/News/June 2022/Bolivian Teachers Welcomed Wikipedia in their Classroom|Bolivian Teachers Welcomed Wikipedia in their Classroom]] * [[m:Special:MyLanguage/Education/News/June 2022/Educational program & Wikivoyage in Ukrainian University|Educational program & Wikivoyage in Ukrainian University]] * [[m:Special:MyLanguage/Education/News/June 2022/The Great Learning and Connection: Experience from AFLIA|The Great Learning and Connection: Experience from AFLIA]] * [[m:Special:MyLanguage/Education/News/June 2022/New Mexico Students Join Wikimedia Movement Through WikiForHumanRights Campaign|New Mexico Students Join Wikimedia Movement Through WikiForHumanRights Campaign]] * [[m:Special:MyLanguage/Education/News/June 2022/The school wiki-project run by a 15 year old student came to an end|The school wiki-project run by a 15 year old student came to an end]] * [[m:Special:MyLanguage/Education/News/June 2022/The students of Kadir Has University, Istanbul contribute Wikimedia projects in "Civic Responsibility Project" course|The students of Kadir Has University, Istanbul contribute Wikimedia projects in "Civic Responsibility Project" course]] * [[m:Special:MyLanguage/Education/News/June 2022/Wiki Trip with Vasil Kamami Wikiclub to Berat, the town of one thousand windows|Wiki Trip with Vasil Kamami Wikiclub to Berat, the town of one thousand windows]] * [[m:Special:MyLanguage/Education/News/June 2022/Wikiclubs in Albania|Wikiclubs in Albania]] * [[m:Special:MyLanguage/Education/News/June 2022/Wikidata in the classroom FGGC Bwari Experience|Wikidata in the classroom FGGC Bwari Experience]] * [[m:Special:MyLanguage/Education/News/June 2022/Wikipedia and Secondary Schools in Aotearoa New Zealand|Wikipedia and Secondary Schools in Aotearoa New Zealand]] * [[m:Special:MyLanguage/Education/News/June 2022/А large-scale online course for teaching beginners to work in Wikipedia has been developed in Russia|А large-scale online course for teaching beginners to work in Wikipedia has been developed in Russia]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 18:50, 4 July 2022 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=23406065 --> == This Month in Education: July 2022 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 11 • Issue 7 • July 2022</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/July 2022|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/July 2022/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/July 2022/Wikimedia Chile launched a teacher guidebook with Wiki tools for Heritage Education|Wikimedia Chile launched a teacher guidebook with Wiki tools for Heritage Education]] * [[m:Special:MyLanguage/Education/News/July 2022/Wikimedia Serbia received a new accreditation for the professional development program|Wikimedia Serbia received a new accreditation for the professional development program]] * [[m:Special:MyLanguage/Education/News/July 2022/Wikimedia for Illiterate Persons|Wikimedia for Illiterate Persons]] * [[m:Special:MyLanguage/Education/News/July 2022/EtnoWiki edit-a-thon in Poland|Polish Wikipedia is enriched with new EtnoWiki content]] * [[m:Special:MyLanguage/Education/News/July 2022/Career Education through Wikipedia|Career Education through Wikipedia]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 17:38, 3 August 2022 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=23607963 --> == This Month in Education: August 2022 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 11 • Issue 8 • August 2022</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/August 2022|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/August 2022/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/August 2022/The Making of a Certified Trainer of Reading Wikipedia in the Classroom|The Making of a Certified Trainer of Reading Wikipedia in the Classroom]] * [[m:Special:MyLanguage/Education/News/August 2022/Wikimania SDGs 2022: The Kwara Experience|Wikimania SDGs 2022: The Kwara Experience]] * [[m:Special:MyLanguage/Education/News/August 2022/An adapted Module teacher’s guide in Yoruba and English about Reading Wikipedia in the Classroom in Nigeria is now available on Commons|An adapted Module teacher’s guide in Yoruba and English about Reading Wikipedia in the Classroom in Nigeria is now available on Commons]] * [[m:Special:MyLanguage/Education/News/August 2022/Reading Wikipedia in the Classroom Kwara, Nigeria: The Trainers Experience|Reading Wikipedia in the Classroom Kwara, Nigeria: The Trainers Experience]] * [[m:Special:MyLanguage/Education/News/August 2022/Edu Wiki Camp 2022 in Serbia: Together again|Edu Wiki Camp 2022 in Serbia: Together again]] * [[m:Special:MyLanguage/Education/News/August 2022/Reading Wikipedia in the Classroom Program Nigeria: The Teacher experience |Reading Wikipedia in the Classroom Program Nigeria: The Teacher experience]] * [[m:Special:MyLanguage/Education/News/August 2022/Wiki For Senior Citizens|Wiki For Senior Citizens]] * [[m:Special:MyLanguage/Education/News/August 2022/WikiLoves SDGs Nigeria Tours Kwara State University Malete|WikiLoves SDGs Nigeria Tours Kwara State University Malete]] * [[m:Special:MyLanguage/Education/News/August 2022/Wikiteka project in Poland - summertime|Wikiteka project in Poland - summertime]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 16:00, 7 September 2022 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=23758285 --> == This Month in Education: September 2022 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 11 • Issue 9 • September 2022</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/September 2022|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/September 2022/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/September 2022/OpenEdu.ch: centralising training documents, a platform for the teachers' community in Switzerland|OpenEdu.ch: centralising training documents, a platform for the teachers' community in Switzerland]] * [[m:Special:MyLanguage/Education/News/September 2022/Senior Citizens WikiTown 2022: Exploring Olomouc and its heritage|Senior Citizens WikiTown 2022: Exploring Olomouc and its heritage]] * [[m:Special:MyLanguage/Education/News/September 2022/Wikimedia Research Fund|Wikimedia Research Fund]] * [[m:Special:MyLanguage/Education/News/September 2022/Wikimedia Youths Commemorate the International Youth Day 2022 in an exciting way across the globe|Wikimedia Youths Commemorate the International Youth Day 2022 in an exciting way across the globe]] * [[m:Special:MyLanguage/Education/News/September 2022/Wikipedia, Education, and the Crisis of Information|Wikipedia, Education, and the Crisis of Information]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 16:55, 3 October 2022 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=23879722 --> == This Month in Education: End of the 2022 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 11 • Issue 10 • October–November 2022</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/End of the 2022|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/End of the 2022/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/October 2022/2nd Latin American Regional Meeting on Education|2nd Latin American Regional Meeting on Education]] * [[m:Special:MyLanguage/Education/News/October 2022/Adopting Wikipedia for Secondary School Students in Nigeria Classroom|Adopting Wikipedia for Secondary School Students in Nigeria Classroom]] * [[m:Special:MyLanguage/Education/News/October 2022/Celebrating 2022 Vibrance in Kwara State University Malete|Celebrating 2022 Vibrance in Kwara State University Malete]] * [[m:Special:MyLanguage/Education/News/October 2022/Celebrating the Wikipedia and Wikidata Birthday in school|Celebrating the Wikipedia and Wikidata Birthday in school]] * [[m:Special:MyLanguage/Education/News/October 2022/Report on school libraries in Poland for the Wikiteka project|Report on school libraries in Poland for the Wikiteka project]] * [[m:Special:MyLanguage/Education/News/October 2022/Wiki For Senior Citizens Network|Wiki For Senior Citizens Network]] * [[m:Special:MyLanguage/Education/News/October 2022/WikiEducation, Educational practices and experiences in Mexico with Wikipedia and other open resources|WikiEducation, Educational practices and experiences in Mexico with Wikipedia and other open resources]] * [[m:Special:MyLanguage/Education/News/October 2022/Wikimedia & Education Workshops: a Wiki Movimento Brasil initiative|Wikimedia & Education Workshops: a Wiki Movimento Brasil initiative]] * [[m:Special:MyLanguage/Education/News/November 2022/An event at the National History Museum in Tirana|An event at the National History Museum in Tirana]] * [[m:Special:MyLanguage/Education/News/November 2022/Students 24-hour competition on Wikipedia article writing|Students 24-hour competition on Wikipedia article writing]] * [[m:Special:MyLanguage/Education/News/November 2022/Wiki-Data a Giant at 10|Wiki-Data a Giant at 10]] * [[m:Special:MyLanguage/Education/News/November 2022/WikiGraphers: Visualizing Open Knowledge|WikiGraphers: Visualizing Open Knowledge]] * [[m:Special:MyLanguage/Education/News/November 2022/Wikimedia Israel’s Educational Innovation: “Students Write Wikipedia” as a Matriculation-Exam Alternative|Wikimedia Israel’s Educational Innovation: “Students Write Wikipedia” as a Matriculation-Exam Alternative]] * [[m:Special:MyLanguage/Education/News/November 2022/Wikimedia Morocco User Group Empowers Moroccan Teachers to Use Wikipedia in the Classroom |Wikimedia Morocco User Group Empowers Moroccan Teachers to Use Wikipedia in the Classroom]] * [[m:Special:MyLanguage/Education/News/November 2022/Wikimedia Russia has released the "Introduction to Wikipedia" textbook|Wikimedia Russia has released the "Introduction to Wikipedia" textbook]] * [[m:Special:MyLanguage/Education/News/November 2022/“Wikipedia for School” contest was held in Ukraine for the third time|“Wikipedia for School” contest was held in Ukraine for the third time]] * [[m:Special:MyLanguage/Education/News/November 2022/Announcing the Wikipedia & Education User Group Election Results|Announcing the Wikipedia & Education User Group Election Results]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 06:56, 19 December 2022 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=24091294 --> == This Month in Education: January 2023 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 12 • Issue 1 • January 2023</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/January 2023|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/January 2023/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/January 2023/Educational Projects 2023-1 in Mexico|Educational Projects 2023-1 in Mexico]] * [[m:Special:MyLanguage/Education/News/January 2023/Integration of Wikipedia in Ukrainian universities – teacher-led and student-led|Integration of Wikipedia in Ukrainian universities – teacher-led and student-led]] * [[m:Special:MyLanguage/Education/News/January 2023/Transitional Justice in Kosovo edit-a-thon and Partnership with Faculty of Electrical and Computer Engineering - University of Prishtina|Transitional Justice in Kosovo edit-a-thon and Partnership with Faculty of Electrical and Computer Engineering - University of Prishtina]] * [[m:Special:MyLanguage/Education/News/January 2023/Wikidata Citation Hunt Program for secondary school students, Dubai|Wikidata Citation Hunt Program for secondary school students, Dubai]] * [[m:Special:MyLanguage/Education/News/January 2023/Wikipedia edit-a-thon with students from Art Faculty - University of Prishtina|Wikipedia edit-a-thon with students from Art Faculty - University of Prishtina]] * [[m:Special:MyLanguage/Education/News/January 2023/Тeacher from Belgrade got a reward for using Wikibooks in teaching|Тeacher from Belgrade got a reward for using Wikibooks in teaching]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 17:32, 6 February 2023 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=24472891 --> == This Month in Education: February 2023 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 12 • Issue 2 • February 2023</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/February 2023|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/February 2023/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/February 2023/A Strategic Direction for a Massive Online Course for Educators in Brazil|A Strategic Direction for a Massive Online Course for Educators in Brazil]] * [[m:Special:MyLanguage/Education/News/February 2023/Alliance Funding for Wikipedia as a school resource in Tāmaki Makaurau Auckland, New Zealand|Alliance Funding for Wikipedia as a school resource in Tāmaki Makaurau Auckland, New Zealand]] * [[m:Special:MyLanguage/Education/News/February 2023/Call for Submissions to Wiki Workshop 2023|Call for Submissions to Wiki Workshop 2023]] * [[m:Special:MyLanguage/Education/News/February 2023/Collaboration with Charles University on the creation of Czech Wikipedia started in January|Collaboration with Charles University on the creation of Czech Wikipedia started in January]] * [[m:Special:MyLanguage/Education/News/February 2023/Open Education Week 2023 in the Wikimedia Mexico Education Program|Open Education Week 2023 in the Wikimedia Mexico Education Program]] * [[m:Special:MyLanguage/Education/News/February 2023/Wikiclubs with different schools in Albania |Wikiclubs with different schools in Albania]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 21:08, 12 March 2023 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=24706239 --> == This Month in Education: March 2023 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 12 • Issue 3 • March 2023</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/March 2023|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/March 2023/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/March 2023/Audio-seminar project of the Wikimedia Mexico Education Program|Audio-seminar project of the Wikimedia Mexico Education Program]] * [[m:Special:MyLanguage/Education/News/March 2023/Empowering Nigerian Female Artists: Through Art & Feminism Edith-A-Thon at KWASU Fan Club|Empowering Nigerian Female Artists: Through Art & Feminism Edith-A-Thon at KWASU Fan Club]] * [[m:Special:MyLanguage/Education/News/March 2023/Exploring How Wikipedia Works|Exploring How Wikipedia Works]] * [[m:Special:MyLanguage/Education/News/March 2023/Florida graduate students complete Library History edit-a-thon for credit|Florida graduate students complete Library History edit-a-thon for credit]] * [[m:Special:MyLanguage/Education/News/March 2023/Improving hearing health content in Brazil|Improving hearing health content in Brazil]] * [[m:Special:MyLanguage/Education/News/March 2023/Media Literacy Portal to become a key resource for media education in Czech Libraries |Media Literacy Portal to become a key resource for media education in Czech Libraries]] * [[m:Special:MyLanguage/Education/News/March 2023/Wikeys in the Albanian language|Wikeys in the Albanian language]] * [[m:Special:MyLanguage/Education/News/March 2023/Wikimarathon is an opportunity to involve students and teachers in creating and editing articles in Wikipedia|Wikimarathon is an opportunity to involve students and teachers in creating and editing articles in Wikipedia]] * [[m:Special:MyLanguage/Education/News/March 2023/Wikimedia Polska short report|Wikimedia Polska short report]] * [[m:Special:MyLanguage/Education/News/March 2023/Wikimedia Serbia participated in the State Seminar of the The Mathematical Society of Serbia|Wikimedia Serbia participated in the State Seminar of the The Mathematical Society of Serbia]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 18:45, 8 April 2023 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=24824837 --> == This Month in Education: April 2023 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 12 • Issue 4 • April 2023</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/April 2023|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/April 2023/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/April 2023/Auckland Museum Alliance fund project update|Auckland Museum Alliance fund project update]] * [[m:Special:MyLanguage/Education/News/April 2023/Introducing Wikipedia to Kusaal Language Teachers|Introducing Wikipedia to Kusaal Language Teachers]] * [[m:Special:MyLanguage/Education/News/April 2023/KWASU Fan Club Leads the Way in 21st Century Learning with Wiki in School Program|KWASU Fan Club Leads the Way in 21st Century Learning with Wiki in School Program]] * [[m:Special:MyLanguage/Education/News/April 2023/On-line Courses for Educators in Poland|On-line Courses for Educators in Poland]] * [[m:Special:MyLanguage/Education/News/April 2023/Online meeting of Ukrainian educators working with Wikipedia – four perspectives|Online meeting of Ukrainian educators working with Wikipedia – four perspectives]] * [[m:Special:MyLanguage/Education/News/April 2023/Wikiclubs Editathon in Elbasan, Albania |Wikiclubs Editathon in Elbasan, Albania]] * [[m:Special:MyLanguage/Education/News/April 2023/Wikipedia at the Brazilian Linguistics Olympiad|Wikipedia at the Brazilian Linguistics Olympiad]] * [[m:Special:MyLanguage/Education/News/April 2023/Wikipedia at the University of Łódź Information Management Conference|Wikipedia at the University of Łódź Information Management Conference]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 16:27, 23 May 2023 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=24999562 --> == This Month in Education: June 2023 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 12 • Issue 5 • June 2023</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/June 2023|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/June 2023/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/June 2023/Africa Day 2023: Abuja Teachers celebrates|Africa Day 2023: Abuja Teachers celebrates]] * [[m:Special:MyLanguage/Education/News/June 2023/From editing articles to civic power – Wikimedia UK's research on democracy and Wikipedia|From editing articles to civic power – Wikimedia UK's research on democracy and Wikipedia]] * [[m:Special:MyLanguage/Education/News/June 2023/Reading Wikipedia in the Classroom Program in Yemen Brings Positive Impact to Yemeni Teachers|Reading Wikipedia in the Classroom Program in Yemen Brings Positive Impact to Yemeni Teachers]] * [[m:Special:MyLanguage/Education/News/June 2023/Using Wikipedia in education: students' and teachers' view|Using Wikipedia in education: students' and teachers' view]] * [[m:Special:MyLanguage/Education/News/June 2023/The Journey of Reading Wikipedia in the Classroom Lagos State|The Journey of Reading Wikipedia in the Classroom Lagos State]] * [[m:Special:MyLanguage/Education/News/June 2023/WMB goes to Serbia |WMB goes to Serbia]] * [[m:Special:MyLanguage/Education/News/June 2023/But we don't want it to end!|But we don't want it to end!]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 08:44, 4 July 2023 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=25147408 --> == This Month in Education: July 2023 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 12 • Issue 7 • July 2023</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/July 2023|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/July 2023/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/July 2023/Wikimedia Kaduna Connect Campaign|Wikimedia Kaduna Connect Campaign]] * [[m:Special:MyLanguage/Education/News/July 2023/Wikimedia Serbia published a paper Promoting Equity in Access to Open Knowledge: An Example of the Wikipedia Educational Program|Wikimedia Serbia published a paper Promoting Equity in Access to Open Knowledge: An Example of the Wikipedia Educational Program]] * [[m:Special:MyLanguage/Education/News/July 2023/Wikimedia and Education Kailali Multiple campus|Wikimedia and Education Kailali Multiple campus]] * [[m:Special:MyLanguage/Education/News/July 2023/WikiCamp in Istog, Kosovo: Promoting Knowledge and Nature Appreciation|WikiCamp in Istog, Kosovo: Promoting Knowledge and Nature Appreciation]] * [[m:Special:MyLanguage/Education/News/July 2023/Wiki at the Brazilian National History Symposium|Wiki at the Brazilian National History Symposium]] * [[m:Special:MyLanguage/Education/News/July 2023/US & Canada program reaches 100M words added |US & Canada program reaches 100M words added]] * [[m:Special:MyLanguage/Education/News/July 2023/Renewed Community Wikiconference brought together experienced Wikipedians and newcomers|Renewed Community Wikiconference brought together experienced Wikipedians and newcomers]] * [[m:Special:MyLanguage/Education/News/July 2023/Kusaal Wikipedia Workshop at Ajumako Campus, University of Education, Winneba|Kusaal Wikipedia Workshop at Ajumako Campus, University of Education, Winneba]] * [[m:Special:MyLanguage/Education/News/July 2023/Join us to celebrate the Kiwix4Schools Africa Mentorship Program Graduation Ceremony|Join us to celebrate the Kiwix4Schools Africa Mentorship Program Graduation Ceremony]] * [[m:Special:MyLanguage/Education/News/July 2023/Activities that took place during the presentation of the WikiEducation book|Activities that took place during the presentation of the WikiEducation book. Educational practices and experiences in Mexico with Wikipedia and other open resources in Xalala, Veracruz from the Wikimedia Mexico Education Program]] * [[m:Special:MyLanguage/Education/News/July 2023/62+ Participants Graduates from the Kiwix4Schools Africa Mentorship Program|62+ Participants Graduates from the Kiwix4Schools Africa Mentorship Program]] * [[m:Special:MyLanguage/Education/News/July 2023/“Reading Wikipedia in the Classroom” course launched in Ukraine|“Reading Wikipedia in the Classroom” course launched in Ukraine]] * [[m:Special:MyLanguage/Education/News/July 2023/OFWA and Goethe Institute Host Wiki Skills For Librarians Workshop-Ghana|OFWA and Goethe Institute Host Wiki Skills For Librarians Workshop-Ghana]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 15:32, 14 August 2023 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=25457946 --> == This Month in Education: September 2023 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 12 • Issue 7 • September 2023</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/September 2023|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/September 2023/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/September 2023/Inauguration of the Kent Wiki Club at the Wikimania 2023 Conference|Inauguration of the Kent Wiki Club at the Wikimania 2023 Conference]] * [[m:Special:MyLanguage/Education/News/September 2023/Letter Magic: Supercharging Your WikiEducation Programs|Letter Magic: Supercharging Your WikiEducation Programs]] * [[m:Special:MyLanguage/Education/News/September 2023/Réseau @pprendre (Learning Network) : The Initiative for Educational Change in Francophone West Africa|Réseau @pprendre (Learning Network) : The Initiative for Educational Change in Francophone West Africa]] * [[m:Special:MyLanguage/Education/News/September 2023/WikiChallenge Ecoles d’Afrique closes its 5th edition with 13 winning schools|WikiChallenge Ecoles d’Afrique closes its 5th edition with 13 winning schools]] * [[m:Special:MyLanguage/Education/News/September 2023/WikiConecta: connecting Brazilian university professors and Wikimedia|WikiConecta: connecting Brazilian university professors and Wikimedia]] * [[m:Special:MyLanguage/Education/News/September 2023/Wikimedia Germany launches interactive event series Open Source AI in Education |Wikimedia Germany launches interactive event series Open Source AI in Education]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 05:01, 10 October 2023 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=25700976 --> == This Month in Education: October 2023 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">Volume 12 • Issue 8 • October 2023</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/October 2023|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/October 2023/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/October 2023/3 Generations at Wikipedia Education Program in Türkiye|3 Generations at Wikipedia Education Program in Türkiye]] * [[m:Special:MyLanguage/Education/News/October 2023/CBSUA Launches Wiki Education in Partnership with PhilWiki Community and Bikol Wikipedia Community|CBSUA Launches Wiki Education in Partnership with PhilWiki Community and Bikol Wikipedia Community]] * [[m:Special:MyLanguage/Education/News/October 2023/Celebrating Wikidata’s Birthday in Elbasan|Celebrating Wikidata’s Birthday in Elbasan]] * [[m:Special:MyLanguage/Education/News/October 2023/Edu Wiki Camp 2023 - together in Sremski Karlovci|Edu Wiki Camp 2023 - together in Sremski Karlovci]] * [[m:Special:MyLanguage/Education/News/October 2023/PhilWiki Community promotes language preservation and cultural heritage advocacies at ADNU|PhilWiki Community promotes language preservation and cultural heritage advocacies at ADNU]] * [[m:Special:MyLanguage/Education/News/October 2023/PunjabWiki Education Program: A Wikipedia Adventure in Punjab|PunjabWiki Education Program: A Wikipedia Adventure in Punjab]] * [[m:Special:MyLanguage/Education/News/October 2023/WikiConference on Education ignites formation of Wikimedia communities|WikiConference on Education ignites formation of Wikimedia communities]] * [[m:Special:MyLanguage/Education/News/October 2023/Wikimedia Estonia talked about education at CEE meeting in Tbilisi|Wikimedia Estonia talked about education at CEE meeting in Tbilisi]] * [[m:Special:MyLanguage/Education/News/October 2023/Wikimedia in Brazil is going to be a book|Wikimedia in Brazil is going to be a book]] * [[m:Special:MyLanguage/Education/News/October 2023/Wikipedian Editor Project: Arabic Sounds Workshop 2023|Wikipedian Editor Project: Arabic Sounds Workshop 2023]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 11:34, 8 November 2023 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=25784366 --> == This Month in Education: November 2023 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 12 • Issue 9 • November 2023</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/November 2023|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/November 2023/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/November 2023/4th WikiUNAM Editathon: Community knowledge strengthens education|4th WikiUNAM Editathon: Community knowledge strengthens education]] * [[m:Special:MyLanguage/Education/News/November 2023/Edit-a-thon at the Faculty of Medical Sciences of Santa Casa de São Paulo|Edit-a-thon at the Faculty of Medical Sciences of Santa Casa de São Paulo]] * [[m:Special:MyLanguage/Education/News/November 2023/EduWiki Nigeria Community: Embracing Digital Learning Through Wikipedia|EduWiki Nigeria Community: Embracing Digital Learning Through Wikipedia]] * [[m:Special:MyLanguage/Education/News/November 2023/Evening Wikischool offers Czech seniors further education on Wikipedia|Evening Wikischool offers Czech seniors further education on Wikipedia]] * [[m:Special:MyLanguage/Education/News/November 2023/Expansion of Wikipedia Education Program through Student Associations at Iranian Universities|Expansion of Wikipedia Education Program through Student Associations at Iranian Universities]] * [[m:Special:MyLanguage/Education/News/November 2023/Exploring Wikipedia through Wikiclubs and the Wikeys board game in Albania |Exploring Wikipedia through Wikiclubs and the Wikeys board game in Albania]] * [[m:Special:MyLanguage/Education/News/November 2023/First anniversary of the game Wikeys|First anniversary of the game Wikeys]] * [[m:Special:MyLanguage/Education/News/November 2023/Involve visiting students in education programs|Involve visiting students in education programs]] * [[m:Special:MyLanguage/Education/News/November 2023/Iranian Students as Wikipedians: Using Wikipedia to Teach Research Methodology and Encyclopedic Writing|Iranian Students as Wikipedians: Using Wikipedia to Teach Research Methodology and Encyclopedic Writing]] * [[m:Special:MyLanguage/Education/News/November 2023/Kiwix4Schools Nigeria: Bridging Knowledge Gap through Digital Literacy|Kiwix4Schools Nigeria: Bridging Knowledge Gap through Digital Literacy]] * [[m:Special:MyLanguage/Education/News/November 2023/Lire wikipedia en classe à Djougou au Bénin|Lire wikipedia en classe à Djougou au Bénin]] * [[m:Special:MyLanguage/Education/News/November 2023/Tyap Wikimedians Zaria Outreach|Tyap Wikimedians Zaria Outreach]] * [[m:Special:MyLanguage/Education/News/November 2023/Art Outreach at Aje Compreshensive Senior High School 1st November 2023, Lagos Mainland|Art Outreach at Aje Comprehensive Senior High School 1st November 2023, Lagos Mainland]] * [[m:Special:MyLanguage/Education/News/November 2023/PhilWiki Community holds a meet-up to advocate women empowerment|PhilWiki Community holds a meet-up to advocate women empowerment]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 08:24, 14 December 2023 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=25919737 --> == This Month in Education: January 2024 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 13 • Issue 1 • January 2024</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/January 2024|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/January 2024/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/January 2024/Cross-Continental Wikimedia Activities: A Dialogue between Malaysia and Estonia|Cross-Continental Wikimedia Activities: A Dialogue between Malaysia and Estonia]] * [[m:Special:MyLanguage/Education/News/January 2024/Czech programme SWW in 2023 – how have we managed to engage students|Czech programme SWW in 2023 – how have we managed to engage students]] * [[m:Special:MyLanguage/Education/News/January 2024/Extending Updates on Wikipedia in Education – Elbasan, Albania|Extending Updates on Wikipedia in Education – Elbasan, Albania]] * [[m:Special:MyLanguage/Education/News/January 2024/Reading Wikipedia in the Classroom Teacher’s guide – now available in Bulgarian language|Reading Wikipedia in the Classroom Teacher’s guide – now available in Bulgarian language]] * [[m:Special:MyLanguage/Education/News/January 2024/Summer students at Auckland Museum|Summer students at Auckland Museum]] * [[m:Special:MyLanguage/Education/News/January 2024/WikiDunong: EduWiki Initiatives in the Philippines Project|WikiDunong: EduWiki Initiatives in the Philippines Project]] * [[m:Special:MyLanguage/Education/News/January 2024/Wikimedia Armenia's Educational Workshops|Wikimedia Armenia's Educational Workshops]] * [[m:Special:MyLanguage/Education/News/January 2024/Wikimedia Foundation publishes its first Child Rights Impact Assessment|Wikimedia Foundation publishes its first Child Rights Impact Assessment]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 10:02, 10 February 2024 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=26091771 --> == This Month in Education: February 2024 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 13 • Issue 2 • February 2024</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/February 2024|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/February 2024/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/February 2024/2 new courses in Students Write Wikipedia Starting this February|2 new courses in Students Write Wikipedia Starting this February]] * [[m:Special:MyLanguage/Education/News/February 2024/More two wiki-education partnerships|More two wiki-education partnerships]] * [[m:Special:MyLanguage/Education/News/February 2024/Open Education Week 2024 in Mexico|Open Education Week 2024 in Mexico]] * [[m:Special:MyLanguage/Education/News/February 2024/Reading Wikipedia in Bolivia, the community grows|Reading Wikipedia in Bolivia, the community grows]] * [[m:Special:MyLanguage/Education/News/February 2024/Wiki Education Philippines promotes OERs utilization|Wiki Education Philippines promotes OERs utilization]] * [[m:Special:MyLanguage/Education/News/February 2024/Wiki Loves Librarians, Kaduna|Wiki Loves Librarians, Kaduna]] * [[m:Special:MyLanguage/Education/News/February 2024/Wiki Workshop 2024 CfP - Call for Papers Research track|Wiki Workshop 2024 CfP – Call for Papers Research track]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 18:37, 20 March 2024 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=26310117 --> == This Month in Education: March 2024 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 13 • Issue 3 • March 2024</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/March 2024|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/March 2024/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/March 2024/Reading Wikipedia in the classroom, Kaduna|Reading Wikipedia in the classroom, Kaduna]] * [[m:Special:MyLanguage/Education/News/March 2024/Reading Wikipedia in Ukraine – the course for educators is now available on demand|Reading Wikipedia in Ukraine – the course for educators is now available on demand]] * [[m:Special:MyLanguage/Education/News/March 2024/Wiki Movement Brazil will once again support the Brazilian Linguistics Olympiad|Wiki Movement Brazil will once again support the Brazilian Linguistics Olympiad]] * [[m:Special:MyLanguage/Education/News/March 2024/Wikipedia within the Education Setting in Albania|Wikipedia within the Education Setting in Albania]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 07:28, 28 April 2024 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=26659969 --> == This Month in Education: April 2024 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 13 • Issue 4 • April 2024</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/April 2024|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/April 2024/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/April 2024/EduWiki Updates From Uganda|EduWiki Updates From Uganda]] * [[m:Special:MyLanguage/Education/News/April 2024/Good news from Bolivia: Reading Wikipedia Program continues in 2024|Good news from Bolivia: Reading Wikipedia Program continues in 2024]] * [[m:Special:MyLanguage/Education/News/April 2024/Hearing Health Project: Impactful partnership with Wiki Movement Brazil|Hearing Health Project: Impactful partnership with Wiki Movement Brazil]] * [[m:Special:MyLanguage/Education/News/April 2024/Wikimedia Spain, Amical Wikimedia and the University of Valencia develop Wikipedia educational project|Wikimedia Spain, Amical Wikimedia and the University of Valencia develop Wikipedia educational project]]</div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 03:19, 14 May 2024 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=26698909 --> == This Month in Education: May 2024 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 13 • Issue 5 • May 2024</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/May 2024|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/May 2024/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/May 2024/Albania - Georgia Wikimedia Cooperation 2024|Albania - Georgia Wikimedia Cooperation 2024]] * [[m:Special:MyLanguage/Education/News/May 2024/Aleksandër Xhuvani University Editathon in Elbasan|Aleksandër Xhuvani University Editathon in Elbasan]] * [[m:Special:MyLanguage/Education/News/May 2024/Central Bicol State University of Agriculture LitFest features translation and article writing on Wikipedia|Central Bicol State University of Agriculture LitFest features translation and article writing on Wikipedia]] * [[m:Special:MyLanguage/Education/News/May 2024/Empowering Youth Council in Bulqiza through editathons|Empowering Youth Council in Bulqiza through editathons]] * [[m:Special:MyLanguage/Education/News/May 2024/We left a piece of our hearts at Arhavi|We left a piece of our hearts at Arhavi]] * [[m:Special:MyLanguage/Education/News/May 2024/Wiki Movimento Brasil at Tech Week and Education Speaker Series |Wiki Movimento Brasil at Tech Week and Education Speaker Series]] * [[m:Special:MyLanguage/Education/News/May 2024/Wikimedia MKD trains new users in collaboration with MYLA|Wikimedia MKD trains new users in collaboration with MYLA]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 13:30, 15 June 2024 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=26854161 --> == This Month in Education: June 2024 == <div class="plainlinks mw-content-ltr" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 13 • Issue 6 • June 2024</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/June 2024|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/June 2024/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/June 2024/From a Language Teacher to a Library Support Staff: The Wikimedia Effect|From a Language Teacher to a Library Support Staff: The Wikimedia Effect]] * [[m:Special:MyLanguage/Education/News/June 2024/5th WikiEducation 2024 Conference in Mexico|5th WikiEducation 2024 Conference in Mexico]] * [[m:Special:MyLanguage/Education/News/June 2024/Lviv hosted a spring wikischool for Ukrainian high school students|Lviv hosted a spring wikischool for Ukrainian high school students]] * [[m:Special:MyLanguage/Education/News/June 2024/First class of teachers graduated from Reading Wikipedia in the Classroom 2024|First class of teachers graduated from Reading Wikipedia in the Classroom 2024]] * [[m:Special:MyLanguage/Education/News/June 2024/Empowering Digital Citizenship: Unlocking the Power of Open Knowledge with Participants of the LIFE Legacy|Empowering Digital Citizenship: Unlocking the Power of Open Knowledge with Participants of the LIFE Legacy]] * [[m:Special:MyLanguage/Education/News/June 2024/Wiki Movimento Brazil supports online and in-person courses and launches material to guide educators in using Wikimedia projects |Wiki Movimento Brazil supports online and in-person courses and launches material to guide educators in using Wikimedia projects]] * [[m:Special:MyLanguage/Education/News/June 2024/Where to find images for free? Webinar for librarians answered many questions|Where to find images for free? Webinar for librarians answered many questions]] * [[m:Special:MyLanguage/Education/News/June 2024/Wikimedia MKD and University of Goce Delchev start a mutual collaboration|Wikimedia MKD and University of Goce Delchev start a mutual collaboration]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 06:58, 9 July 2024 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=27085892 --> == This Month in Education: August 2024 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 13 • Issue 7 • August 2024</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/August 2024|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/August 2024/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/August 2024/Cross-Cultural Knowledge Sharing: Wikipedia's New Frontier at University of Tehran|Cross-Cultural Knowledge Sharing: Wikipedia's New Frontier at University of Tehran]] * [[m:Special:MyLanguage/Education/News/August 2024/Let's Read Wikipedia in Bolivia reaches teachers in Cochabamba|Let's Read Wikipedia in Bolivia reaches teachers in Cochabamba]] * [[m:Special:MyLanguage/Education/News/August 2024/Results of the 2023 “Wikipedia for School” Contest in Ukraine|Results of the 2023 “Wikipedia for School” Contest in Ukraine]] * [[m:Special:MyLanguage/Education/News/August 2024/Edu Wiki Camp in Serbia, 2024|Edu Wiki Camp in Serbia, 2024]] * [[m:Special:MyLanguage/Education/News/August 2024/Wikimedia Human Rights Month this year engaged schools in large amount|Wikimedia Human Rights Month this year engaged schools in large amount]] * [[m:Special:MyLanguage/Education/News/August 2024/Strengthening Education Programs at Wikimania 2024: A Global Leap in Collaborative Learning|Strengthening Education Programs at Wikimania 2024: A Global Leap in Collaborative Learning]] * [[m:Special:MyLanguage/Education/News/August 2024/Wiki Education programs are featured in a scientific outreach magazine, and Wiki Movimento Brasil offers training for researchers in the Amazon|Wiki Education programs are featured in a scientific outreach magazine, and Wiki Movimento Brasil offers training for researchers in the Amazon]] * [[m:Special:MyLanguage/Education/News/August 2024/Wiki Movimento Brasil aims to adapt a game about Wikipedia, organize an academic event for scientific dissemination, and host the XXXIII Wiki-Education Workshop|Wiki Movimento Brasil aims to adapt a game about Wikipedia, organize an academic event for scientific dissemination, and host the XXXIII Wiki-Education Workshop]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 13:21, 11 September 2024 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=27310254 --> == This Month in Education: October 2024 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 13 • Issue 8 • October 2024</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/October 2024|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/October 2024/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/October 2024/CBSUA Wiki Education turns 1 year|CBSUA Wiki Education turns 1 year]] * [[m:Special:MyLanguage/Education/News/October 2024/7th Senior WikiTown took place in Becov nad Teplou, Czech Republic|7th Senior WikiTown took place in Becov nad Teplou, Czech Republic]] * [[m:Special:MyLanguage/Education/News/October 2024/Edit-a-thon about Modern Architecture in Kosovo|Edit-a-thon about Modern Architecture in Kosovo]] * [[m:Special:MyLanguage/Education/News/October 2024/Edu_Wiki_in_South_Sudan:_Creating_a_better_future_in_education|Empowering Digital Literacy through Wikimedia in South Sudan]] * [[m:Special:MyLanguage/Education/News/October 2024/Many new articles and contributions in September and October for Wikimedia MKD|Many new articles and contributions in September and October for Wikimedia MKD]] * [[m:Special:MyLanguage/Education/News/October 2024/New Record: 5 Events in Municipal Library within a Month |New Record: 5 Events in Municipal Library within a Month]] * [[m:Special:MyLanguage/Education/News/October 2024/Wiki-Education programs in Brazil are centered around the Wikidata and Wikisource platforms|Wiki-Education programs in Brazil are centered around the Wikidata and Wikisource platforms]] * [[m:Special:MyLanguage/Education/News/October 2024/WikiChallenge African Schools wins the “Open Pedagogy” Award 2024 from OE Global|WikiChallenge African Schools wins the “Open Pedagogy” Award 2024 from OE Global]] * [[m:Special:MyLanguage/Education/News/October 2024/Wikipedia helps in improving cognitive skills|Wikipedia helps in improving cognitive skills]] * [[m:Special:MyLanguage/Education/News/October 2024/Wikipedia in Graduate Studies: Expanding Research Impact|Wikipedia in Graduate Studies: Expanding Research Impact]] * [[m:Special:MyLanguage/Education/News/October 2024/WiLMa PH establishes a Wiki Club|WiLMa PH establishes a Wiki Club]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 14:56, 12 November 2024 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=27733413 --> == This Month in Education: November 2024 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 13 • Issue 9 • November 2024</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/November 2024|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/November 2024/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/November 2024/Auckland Museum Wikipedia Student Programme|Auckland Museum Wikipedia Student Programme]] * [[m:Special:MyLanguage/Education/News/November 2024/Citizenship and free knowledge on Wikipedia in Albanian language|Citizenship and free knowledge on Wikipedia in Albanian language]] * [[m:Special:MyLanguage/Education/News/November 2024/Engaging students with Wikipedia and Wikidata at Hasanuddin University’s Wikimedia Week|Engaging students with Wikipedia and Wikidata at Hasanuddin University’s Wikimedia Week]] * [[m:Special:MyLanguage/Education/News/November 2024/Minigrant initiative by empowering the Rrëshen community in Albania|Minigrant initiative by empowering the Rrëshen community in Albania]] * [[m:Special:MyLanguage/Education/News/November 2024/Wikidata birthday in Albania, 2024|Wikidata birthday in Albania, 2024]] * [[m:Special:MyLanguage/Education/News/November 2024/Wikidata birthday in School |Wikidata birthday in School]] * [[m:Special:MyLanguage/Education/News/November 2024/Wikimedia Education Workshop at Lumbini Technological University|Wikimedia Education Workshop at Lumbini Technological University]] * [[m:Special:MyLanguage/Education/News/November 2024/Wikimedia MKD's new collaborations and new content|Wikimedia MKD's new collaborations and new content]] * [[m:Special:MyLanguage/Education/News/November 2024/Improving Historical Knowledge on Persian Wikipedia through a continuous Wikimedia Education Program: Shahid Beheshti University Wikipedia Education Program|Improving Historical Knowledge on Persian Wikipedia through a continuous Wikimedia Education Program: Shahid Beheshti University Wikipedia Education Program]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 15:12, 10 December 2024 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=27879342 --> == This Month in Education: January 2025 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 14 • Issue 1 • January 2025</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/January 2025|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/January 2025/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/January 2025/Advancing Education Pillar in Kosovo: 2024 Journey|Advancing Education Pillar in Kosovo: 2024 Journey]] * [[m:Special:MyLanguage/Education/News/January 2025/Auckland Museum Wikipedia Students Making Progress|Auckland Museum Wikipedia Students Making Progress]] * [[m:Special:MyLanguage/Education/News/January 2025/Celebrating 10 Years of Wiki Education|Celebrating 10 Years of Wiki Education]] * [[m:Special:MyLanguage/Education/News/January 2025/Empowering Multilingual Students: Expanding Wikipedia Through Collaboration of foreign languages faculty's students of the University of Tehran|Empowering Multilingual Students: Expanding Wikipedia Through Collaboration of foreign languages faculty's students of the University of Tehran]] * [[m:Special:MyLanguage/Education/News/January 2025/Ensuring accurate and authentic information with 1Lib1Ref Campaign in Anambra|Ensuring accurate and authentic information with 1Lib1Ref Campaign in Anambra]] * [[m:Special:MyLanguage/Education/News/January 2025/Experiences of Wikipedia in the classroom with a gender perspective in Monterrey |Experiences of Wikipedia in the classroom with a gender perspective in Monterrey]] * [[m:Special:MyLanguage/Education/News/January 2025/Fine Arts University Students exploring Wikipedia in Tirana, Albania|Fine Arts University Students exploring Wikipedia in Tirana, Albania]] * [[m:Special:MyLanguage/Education/News/January 2025/Lviv hosted Ukraine’s first student photo walk for Wikipedia|Lviv hosted Ukraine’s first student photo walk for Wikipedia]] * [[m:Special:MyLanguage/Education/News/January 2025/Many new trained volunteers and new articles at the end of the year in Macedonia|Many new trained volunteers and new articles at the end of the year in Macedonia]] * [[m:Special:MyLanguage/Education/News/January 2025/Wikimedia and Scientific Events in Brazil|Wikimedia and Scientific Events in Brazil]] * [[m:Special:MyLanguage/Education/News/January 2025/Wiki Workshop- Call for Contributions|Wiki Workshop- Call for Contributions]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 15:56, 5 February 2025 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=28111205 --> == This Month in Education: February 2025 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 14 • Issue 2 • February 2025</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/February 2025|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/February 2025/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/February 2025/Activities series at the Shefit Hekali school in Peqin, Albania|Activities series at the Shefit Hekali school in Peqin, Albania]] * [[m:Special:MyLanguage/Education/News/February 2025/Wikimedia Brazil has formed a partnership with a public policy research institute|Wikimedia Brazil has formed a partnership with a public policy research institute]] * [[m:Special:MyLanguage/Education/News/February 2025/Preserving Heritage: Tuluvas Aati Month Educational Wikimedia Programs|Preserving Heritage: Tuluvas Aati Month Educational Wikimedia Programs]] * [[m:Special:MyLanguage/Education/News/February 2025/Reflecting on our Past: Farewell to the Auckland Museum Summer Students|Reflecting on our Past: Farewell to the Auckland Museum Summer Students]] * [[m:Special:MyLanguage/Education/News/February 2025/Successful Conclusion of the Second Phase of "Reading Wikipedia in the Classroom" in Yemen|Successful Conclusion of the Second Phase of "Reading Wikipedia in the Classroom" in Yemen]] * [[m:Special:MyLanguage/Education/News/February 2025/Wiki Workshop in Mitrovica |Wiki Workshop in Mitrovica]] * [[m:Special:MyLanguage/Education/News/February 2025/Wikimedia MKD' Education: Lots of new trained users, lots of new articles|Wikimedia MKD' Education: Lots of new trained users, lots of new articles]] * [[m:Special:MyLanguage/Education/News/February 2025/Wikimedia Serbia receives accreditation from the National Library of Serbia for the Wiki Senior seminar|Wikimedia Serbia receives accreditation from the National Library of Serbia for the Wiki Senior seminar]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 09:04, 12 March 2025 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=28314249 --> == This Month in Education: March 2025 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 14 • Issue 3 • March 2025</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/March 2025|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/March 2025/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/March 2025/A Whole New World: Research Findings on New Editor Integration in Serbian Wikipedia|A Whole New World: Research Findings on New Editor Integration in Serbian Wikipedia]] * [[m:Special:MyLanguage/Education/News/March 2025/Bolivia: a new round of Leamos Wikipedia begins in Bolivia|Bolivia: a new round of Leamos Wikipedia begins in Bolivia]] * [[m:Special:MyLanguage/Education/News/March 2025/Faculty of Social Sciences Workshop in Albania|Faculty of Social Sciences Workshop in Albania]] * [[m:Special:MyLanguage/Education/News/March 2025/Lots of contributions and trainings as part of Wikimedia MKD's Education Programme|Lots of contributions and trainings as part of Wikimedia MKD's Education Programme]] * [[m:Special:MyLanguage/Education/News/March 2025/Wikimedia organized multiple events of science and education in Brazil during the month of March|Wikimedia organized multiple events of science and education in Brazil during the month of March]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 15:04, 10 April 2025 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=28458563 --> == This Month in Education: April 2025 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 14 • Issue 4 • April 2025</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/April 2025|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/April 2025/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/April 2025/Ceremony of giving certificates and awarding the winners of the edit-a-thon: Meet Slovenia|Ceremony of giving certificates and awarding the winners of the edit-a-thon: Meet Slovenia]] * [[m:Special:MyLanguage/Education/News/April 2025/The Workshops Wikimedia & Education are back in Brazil|The Workshops Wikimedia & Education are back in Brazil]] * [[m:Special:MyLanguage/Education/News/April 2025/EduWiki Nigeria: Advancing Digital Literacy in Schools|EduWiki Nigeria: Advancing Digital Literacy in Schools]] * [[m:Special:MyLanguage/Education/News/April 2025/Empowering the Next Generation: Wikidata Training at Federal Government Boys College, FGBC Abuja|Empowering the Next Generation: Wikidata Training at Federal Government Boys College, FGBC Abuja]] * [[m:Special:MyLanguage/Education/News/April 2025/Final Wikipedia project with Shefit Hekali school in Peqin, Albania|Final Wikipedia project with Shefit Hekali school in Peqin, Albania]] * [[m:Special:MyLanguage/Education/News/April 2025/Teachers who graduated from the Leamos Wikipedia program in Bolivia become mentors for their colleagues |Teachers who graduated from the Leamos Wikipedia program in Bolivia become mentors for their colleagues]] * [[m:Special:MyLanguage/Education/News/April 2025/Wikivoyage in Has region, Northern Albania|Wikivoyage in Has region, Northern Albania]] * [[m:Special:MyLanguage/Education/News/April 2025/Wikivoyage workshop in Bulqiza|Wikivoyage workshop in Bulqiza]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 02:48, 10 May 2025 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=28656387 --> == This Month in Education: May 2025 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 14 • Issue 5 • May 2025</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/May 2025|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/May 2025/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/May 2025/Journalism students at Aleksandër Xhuvani University explore Wikipedia in Albania|Journalism students at Aleksandër Xhuvani University explore Wikipedia in Albania]] * [[m:Special:MyLanguage/Education/News/May 2025/Reviewing pending articles editathon with high school students in Albania|Reviewing pending articles editathon with high school students in Albania]] * [[m:Special:MyLanguage/Education/News/May 2025/Several educational workshops to promote science on Wiki were held in Brazil in the month of May|Several educational workshops to promote science on Wiki were held in Brazil in the month of May]] * [[m:Special:MyLanguage/Education/News/May 2025/Simón Bolívar Teacher Training College joins the Let's Read Wikipedia Program|Simón Bolívar Teacher Training College joins the Let's Read Wikipedia Program]] * [[m:Special:MyLanguage/Education/News/May 2025/Students become Editors: Wikimedia Chile launches Latin America's first Vikidia Workshop|Students become Editors: Wikimedia Chile launches Latin America's first Vikidia Workshop]] * [[m:Special:MyLanguage/Education/News/May 2025/The DemocraTICon competition was held, this year for the first time with a discipline focused on Wikipedia |The DemocraTICon competition was held, this year for the first time with a discipline focused on Wikipedia]] * [[m:Special:MyLanguage/Education/News/May 2025/Wikimedia MKD's "Lajka" workshop in Skopje|Wikimedia MKD's "Lajka" workshop in Skopje]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 02:57, 28 May 2025 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=28771448 --> == This Month in Education: June 2025 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 14 • Issue 6 • June 2025</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/June 2025|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/June 2025/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/June 2025/Albanian high school students at the Wikimedia Youth Conference 2025 in Prague|Albanian high school students at the Wikimedia Youth Conference 2025 in Prague]] * [[m:Special:MyLanguage/Education/News/June 2025/Bolivia has 20 new teachers graduated from the Let's Read Wikipedia in the Classroom program|Bolivia has 20 new teachers graduated from the Let's Read Wikipedia in the Classroom program]] * [[m:Special:MyLanguage/Education/News/June 2025/Brazil was present at the EduWiki Conference 2025 in Bogota|Brazil was present at the EduWiki Conference 2025 in Bogota]] * [[m:Special:MyLanguage/Education/News/June 2025/Does Wikipedia has future in the times of Chat-GPT|Does Wikipedia has future in the times of Chat-GPT]] * [[m:Special:MyLanguage/Education/News/June 2025/PhilWiki Community promotes accessible multilingual stories for children|PhilWiki Community promotes accessible multilingual stories for children]] * [[m:Special:MyLanguage/Education/News/June 2025/Reading and Editing Wikipedia in a Bangladeshi College|Reading and Editing Wikipedia in a Bangladeshi College]] * [[m:Special:MyLanguage/Education/News/June 2025/Wikimedia MKD's Workshops in June|Wikimedia MKD's Workshops in June]] * [[m:Special:MyLanguage/Education/News/June 2025/Wikipedia meets 2500 Ukrainian educators at the country’s biggest education festival|Wikipedia meets 2500 Ukrainian educators at the country’s biggest education festival]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 07:18, 27 June 2025 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=28903832 --> == This Month in Education: July 2025 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 14 • Issue 7 • July 2025</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/July 2025|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/July 2025/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/July 2025/Crafting Impactful Education Newsletters: Shared Insights from EduWiki 2025|Crafting Impactful Education Newsletters: Shared Insights from EduWiki 2025]] * [[m:Special:MyLanguage/Education/News/July 2025/Educational Outreach with Youth Centers in Albania|Educational Outreach with Youth Centers in Albania]] * [[m:Special:MyLanguage/Education/News/July 2025/Discussing educational resources at WikiCon Brasil 2025|Discussing educational resources at WikiCon Brasil 2025]] * [[m:Special:MyLanguage/Education/News/July 2025/Enhancing Mobile-Friendly Contribution in Wikimedia Education Programs|Enhancing Mobile-Friendly Contribution in Wikimedia Education Programs]] * [[m:Special:MyLanguage/Education/News/July 2025/The second semester of Leamos Wikipedia begins in Bolivia with challenges and learning|The second semester of Leamos Wikipedia begins in Bolivia with challenges and learning]] * [[m:Special:MyLanguage/Education/News/July 2025/When Travel Fails, Learning Continues: A Reflection from EduWiki 2025 |When Travel Fails, Learning Continues: A Reflection from EduWiki 2025]] * [[m:Special:MyLanguage/Education/News/July 2025/Wiki club in Kumanovo - the newest Wiki club of Wikimedia MKD|Wiki club in Kumanovo - the newest Wiki club of Wikimedia MKD]] * [[m:Special:MyLanguage/Education/News/July 2025/Jaroslav Mašek: How KISK FF MU students used AI to write Wikipedia|Jaroslav Mašek: How KISK FF MU students used AI to write Wikipedia]] * [[m:Special:MyLanguage/Education/News/July 2025/Various programmes up and rolling with Charles University Prague|Various programmes up and rolling with Charles University Prague]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 03:00, 1 August 2025 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=29005310 --> == This Month in Education: August 2025 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 14 • Issue 8 • August 2025</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/August 2025|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/August 2025/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/August 2025/Bootcamp Wikipedia in Classroom|Bootcamp Wikipedia in Classroom]] * [[m:Special:MyLanguage/Education/News/August 2025/Brazil launches campaign about Open Science on Wiki|Brazil launches campaign about Open Science on Wiki]] * [[m:Special:MyLanguage/Education/News/August 2025/Breaking Barriers: Yoruba Wikipedia Fan Club Offa's Historic Wins|Breaking Barriers: Yoruba Wikipedia Fan Club Offa's Historic Wins]] * [[m:Special:MyLanguage/Education/News/August 2025/Emerging Voices in Free Knowledge: The Journey of Wiki Club SATI|Emerging Voices in Free Knowledge: The Journey of Wiki Club SATI]] * [[m:Special:MyLanguage/Education/News/August 2025/From a Curious Student to a Wikimedia Leader|From a Curious Student to a Wikimedia Leader]] * [[m:Special:MyLanguage/Education/News/August 2025/From webinars to conferences: Wikimedia Ukraine’s approach to events for educators|From webinars to conferences: Wikimedia Ukraine’s approach to events for educators]] * [[m:Special:MyLanguage/Education/News/August 2025/Higher education with Wikipedia in Spain|Higher education with Wikipedia in Spain]] * [[m:Special:MyLanguage/Education/News/August 2025/Scientific Contribution from Serbia: Wikipedia in Education Research Published in a Prestigious Journal|Scientific Contribution from Serbia: Wikipedia in Education Research Published in a Prestigious Journal]] * [[m:Special:MyLanguage/Education/News/August 2025/Teachers with Wikipedia. What if we create a Spanish-speaking collaboration network|Teachers with Wikipedia. What if we create a Spanish-speaking collaboration network]] * [[m:Special:MyLanguage/Education/News/August 2025/The brains behind Wikipedia|The brains behind Wikipedia]] * [[m:Special:MyLanguage/Education/News/August 2025/Why EduWiki Should Be Considered by Policymakers|Why EduWiki Should Be Considered by Policymakers]] * [[m:Special:MyLanguage/Education/News/August 2025/Wikimedia Chile in Visviri: Free knowledge and education at Chile’s starting point|Wikimedia Chile in Visviri: Free knowledge and education at Chile’s starting point]] * [[m:Special:MyLanguage/Education/News/August 2025/Wikipedia as a tool presented at Media Education Summer School for Teachers|Wikipedia as a tool presented at Media Education Summer School for Teachers]] * [[m:Special:MyLanguage/Education/News/August 2025/Wikipedia vs AI at La Trobe University|Wikipedia vs AI at La Trobe University]] * [[m:Special:MyLanguage/Education/News/August 2025/St Aloysius University – Wikipedia training session for newcomers|St Aloysius University – Wikipedia training session for newcomers]] * [[m:Special:MyLanguage/Education/News/August 2025/Wiki Loves Academics, WUGN Kaduna|Wiki Loves Academics, WUGN Kaduna]] * [[m:Special:MyLanguage/Education/News/August 2025/In Just 3 Minutes: The Power of Wiki Education|In Just 3 Minutes: The Power of Wiki Education]] * [[m:Special:MyLanguage/Education/News/August 2025/Sensing Cebu: Fieldnotes of an Academic as a Wiki Volunteer|Sensing Cebu: Fieldnotes of an Academic as a Wiki Volunteer]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 15:16, 2 September 2025 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=29205629 --> == This Month in Education: September 2025 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 14 • Issue 9 • September 2025</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/September 2025|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/September 2025/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/September 2025/Brazil organizes seminar to discuss open science and scientific dissemination|Brazil organizes seminar to discuss open science and scientific dissemination]] * [[m:Special:MyLanguage/Education/News/September 2025/CBSUA Recognizes Wiki Training Completers, Awards Feminism & Folklore 2025 Winners|CBSUA Recognizes Wiki Training Completers, Awards Feminism & Folklore 2025 Winners]] * [[m:Special:MyLanguage/Education/News/September 2025/2nd International Conference on Wikimedia, Education, and Digital Cultures Mexico 2025|2nd International Conference on Wikimedia, Education, and Digital Cultures Mexico 2025]] * [[m:Special:MyLanguage/Education/News/September 2025/Accredited seminar for teachers in Veliko Gradište|Accredited seminar for teachers in Veliko Gradište]] * [[m:Special:MyLanguage/Education/News/September 2025/Breaking Barriers, Why open Knowledge matters|Breaking Barriers, Why open Knowledge matters]] * [[m:Special:MyLanguage/Education/News/September 2025/Cross-Continental Knowledge Exchange: Offa Youth Impact Initiative and St Aloysius University in 3D Education Outreach |Cross-Continental Knowledge Exchange: Offa Youth Impact Initiative and St Aloysius University in 3D Education Outreach]] * [[m:Special:MyLanguage/Education/News/September 2025/Igbo Language Audio Project in the Igbo Wiki Fan Club IMSU & Alvan|Igbo Language Audio Project in the Igbo Wiki Fan Club IMSU & Alvan]] * [[m:Special:MyLanguage/Education/News/September 2025/Let's Read Wikipedia reached teachers of the Weenhayek indigenous nation in Bolivia|Let's Read Wikipedia reached teachers of the Weenhayek indigenous nation in Bolivia]] * [[m:Special:MyLanguage/Education/News/September 2025/Monográfico sobre Wikipedia en el aula, Revista Docere|Monograph on Wikipedia in the classroom, Docere Magazine]] * [[m:Special:MyLanguage/Education/News/September 2025/The Third Training Course of the “Reading Wikipedia in the Classroom” Program in Jordan|The Third Training Course of the “Reading Wikipedia in the Classroom” Program in Jordan]] * [[m:Special:MyLanguage/Education/News/September 2025/The Ukrainian Educators’ Wikimedia Conference 2025|The Ukrainian Educators’ Wikimedia Conference 2025]] * [[m:Special:MyLanguage/Education/News/September 2025/Wikimedia MKD's edit-a-thon: Lakes|Wikimedia MKD's edit-a-thon: Lakes]] * [[m:Special:MyLanguage/Education/News/September 2025/Cultura libre en las aulas|Free culture in the classroom]] * [[m:Special:MyLanguage/Education/News/September 2025/Wikimedia Rwanda Wiki clubs|Wikimedia Rwanda Wiki clubs]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 15:09, 2 October 2025 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=29344785 --> == This Month in Education: October 2025 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 14 • Issue 10 • October 2025</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/October 2025|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/October 2025/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/October 2025/"WikiDonne Internship: Wikimedia Platforms for Open Education and Inclusive Culture!" winner at the Open Education Awards 2025|"WikiDonne Internship: Wikimedia Platforms for Open Education and Inclusive Culture!" winner at the Open Education Awards 2025]] * [[m:Special:MyLanguage/Education/News/October 2025/A Proud Chapter in My Wikimedia Journey 🇳🇬: From Editor to Organizer|A Proud Chapter in My Wikimedia Journey 🇳🇬: From Editor to Organizer]] * [[m:Special:MyLanguage/Education/News/October 2025/Debating open science and scientific dissemination in Brazil|Debating open science and scientific dissemination in Brazil]] * [[m:Special:MyLanguage/Education/News/October 2025/Enhancing Academic Articles on Wikipedia with the State University of Jakarta|Enhancing Academic Articles on Wikipedia with the State University of Jakarta]] * [[m:Special:MyLanguage/Education/News/October 2025/India’s Students and Educators Lead the Way in the Wiki Science Competition 2025|India’s Students and Educators Lead the Way in the Wiki Science Competition 2025]] * [[m:Special:MyLanguage/Education/News/October 2025/JDACA & Amman Arab University|JDACA & Amman Arab University]] * [[m:Special:MyLanguage/Education/News/October 2025/New starting page for Wikipedia users had been launched in September|New starting page for Wikipedia users had been launched in September]] * [[m:Special:MyLanguage/Education/News/October 2025/Teaching Evidence Synthesis Automation with the Wikipedia–Kaggle Dataset|Teaching Evidence Synthesis Automation with the Wikipedia–Kaggle Dataset]] * [[m:Special:MyLanguage/Education/News/October 2025/Wikimedia MKD’s Education Program activities for October|Wikimedia MKD’s Education Program activities for October]] * [[m:Special:MyLanguage/Education/News/October 2025/Wikimedia Serbia prepares eight annual Edu Wiki camp|Wikimedia Serbia prepares eight annual Edu Wiki camp]] * [[m:Special:MyLanguage/Education/News/October 2025/Wikivoyage editathon in Peshkopia, Albania|Wikivoyage editathon in Peshkopia, Albania]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 06:04, 2 November 2025 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=29511272 --> == This Month in Education: November 2025 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 14 • Issue 11 • November 2025</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/November 2025|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/November 2025/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/November 2025/Auckland Museum's Wiki Summer Student Programme is back for 2025 & 2026|Auckland Museum's Wiki Summer Student Programme is back for 2025 & 2026]] * [[m:Special:MyLanguage/Education/News/November 2025/Edu Wiki camp 2025 in Belgrade, Serbia|Edu Wiki camp 2025 in Belgrade, Serbia]] * [[m:Special:MyLanguage/Education/News/November 2025/Wikidata na Escola: estudantes da zona rural de Minas Gerais contribuem com dados sobre mulheres negras brasileiras|Wikidata na Escola: estudantes da zona rural de Minas Gerais contribuem com dados sobre mulheres negras brasileiras]] * [[m:Special:MyLanguage/Education/News/November 2025/190 students from Oteitza Lizeoa create 48 articles on the history of the Basque Country for Txikipedia in one day|190 students from Oteitza Lizeoa create 48 articles on the history of the Basque Country for Txikipedia in one day]] * [[m:Special:MyLanguage/Education/News/November 2025/2nd International Congress Wikimedia, Education, and Digital Cultures – WECUDI|2nd International Congress Wikimedia, Education, and Digital Cultures – WECUDI]] * [[m:Special:MyLanguage/Education/News/November 2025/Africa and Proud Leads Wiki Classroom Project Across Three Nigerian States|Africa and Proud Leads Wiki Classroom Project Across Three Nigerian States]] * [[m:Special:MyLanguage/Education/News/November 2025/November 2025November 2025/Annual Czech Wiki Conference took place on Saturday, Nov 8th|November 2025November 2025/Annual Czech Wiki Conference took place on Saturday, Nov 8th]] * [[m:Special:MyLanguage/Education/News/November 2025/EduWiki Meetup at GLAM Wiki Conference 2025|EduWiki Meetup at GLAM Wiki Conference 2025]] * [[m:Special:MyLanguage/Education/News/November 2025/Highly productive autumn education activities in Macedonia|Highly productive autumn education activities in Macedonia]] * [[m:Special:MyLanguage/Education/News/November 2025/Kannada Wikipedia Asian Month 2025: Edit-a-thon & Workshop Highlights from Loyola College, Karnataka|Kannada Wikipedia Asian Month 2025: Edit-a-thon & Workshop Highlights from Loyola College, Karnataka]] * [[m:Special:MyLanguage/Education/News/November 2025/Kosovo Wikivoyage Editathons in Gjakova and Krusha e Madhe|Kosovo Wikivoyage Editathons in Gjakova and Krusha e Madhe]] * [[m:Special:MyLanguage/Education/News/November 2025/Ukrainian educators create open lesson plans based on the «Reading Wikipedia in the Classroom» course|Ukrainian educators create open lesson plans based on the «Reading Wikipedia in the Classroom» course]] * [[m:Special:MyLanguage/Education/News/November 2025/United Architects of the Philippines Student Auxiliary – University of Nueva Caceres joins Wikisource Training|United Architects of the Philippines Student Auxiliary – University of Nueva Caceres joins Wikisource Training]] * [[m:Special:MyLanguage/Education/News/November 2025/Videos on Teaching Experiences with Wikipedia, Wikidata, Commons, and OSM|Videos on Teaching Experiences with Wikipedia, Wikidata, Commons, and OSM]] * [[m:Special:MyLanguage/Education/News/November 2025/Wiki as a tool for technological empowerment of indigenous knowledge|Wiki as a tool for technological empowerment of indigenous knowledge]] * [[m:Special:MyLanguage/Education/News/November 2025/Wiki Science Competition in Albania and Kosovo|Wiki Science Competition in Albania and Kosovo]] * [[m:Special:MyLanguage/Education/News/November 2025/Wiki Workshop 2026 Call for Contributions|Wiki Workshop 2026 Call for Contributions]] * [[m:Special:MyLanguage/Education/News/November 2025/Wikipedia Contribution with Faculty of Mathematical and Natural Sciences Students in Kosovo|Wikipedia Contribution with Faculty of Mathematical and Natural Sciences Students in Kosovo]] * [[m:Special:MyLanguage/Education/News/November 2025/Impact of Wikimedia Rwanda Wiki Clubs in Growth of Wikimedia User Group Rwanda Community|Impact of Wikimedia Rwanda Wiki Clubs in Growth of Wikimedia User Group Rwanda Community]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 13:46, 30 November 2025 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=29716809 --> == This Month in Education: December 2025 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 14 • Issue 12 • December 2025</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/December 2025|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/December 2025/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/December 2025/WikiLatih Wiktionary with the Goethe-Institut: Strengthening the Digital Presence of Indonesia’s Local Languages|WikiLatih Wiktionary with the Goethe-Institut: Strengthening the Digital Presence of Indonesia’s Local Languages]] * [[m:Special:MyLanguage/Education/News/December 2025/Wiki in schools - Architecture and Open Heritage|Wiki in schools - Architecture and Open Heritage]] * [[m:Special:MyLanguage/Education/News/December 2025/What are the challenges and opportunities in scientific dissemination? Reflecting on the topic in the Brazilian context|What are the challenges and opportunities in scientific dissemination? Reflecting on the topic in the Brazilian context]] * [[m:Special:MyLanguage/Education/News/December 2025/WikipediaxAI: Wikipedia, AI, and the future of knowledge|WikipediaxAI: Wikipedia, AI, and the future of knowledge]] * [[m:Special:MyLanguage/Education/News/December 2025/Wikipedia at University Another year of working alongside higher education institutions in Argentina|Wikipedia at University Another year of working alongside higher education institutions in Argentina]] * [[m:Special:MyLanguage/Education/News/December 2025/WAM - Tulu Edit-a-thon & Workshop in St Aloysius University |WAM - Tulu Edit-a-thon & Workshop in St Aloysius University]] * [[m:Special:MyLanguage/Education/News/December 2025/Visibilizando memórias negras: estudantes da UFRGS ampliam a Wikipédia com foco na imprensa e no associativismo pós-abolição|Visibilizando memórias negras: estudantes da UFRGS ampliam a Wikipédia com foco na imprensa e no associativismo pós-abolição]] * [[m:Special:MyLanguage/Education/News/December 2025/Transforming Education Through Wikimedia in Kosovo: 2025|Transforming Education Through Wikimedia in Kosovo: 2025]] * [[m:Special:MyLanguage/Education/News/December 2025/New WikiClubs and educational partnership in Albania|New WikiClubs and educational partnership in Albania]] * [[m:Special:MyLanguage/Education/News/December 2025/New WikiClub with the Dibra Youth Center in Albania|New WikiClub with the Dibra Youth Center in Albania]] * [[m:Special:MyLanguage/Education/News/December 2025/Landmark Educational Initiatives and Wikimedia Programs Transform Learning in 2025|Landmark Educational Initiatives and Wikimedia Programs Transform Learning in 2025]] * [[m:Special:MyLanguage/Education/News/December 2025/Knowledge in the Digital Age: A WMUK Collaborative Workshop|Knowledge in the Digital Age: A WMUK Collaborative Workshop]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 14:22, 17 December 2025 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=29814101 --> == This Month in Education: January 2026 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 15 • Issue 1 • January 2026</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/January 2026|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/January 2026/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/January 2026/Strengthening Wikimedia Education and Digital Literacy in 2026|Strengthening Wikimedia Education and Digital Literacy in 2026]] * [[m:Special:MyLanguage/Education/News/January 2026/Dzongkha Wikipedia Education Program in Bhutan|Dzongkha Wikipedia Education Program in Bhutan]] * [[m:Special:MyLanguage/Education/News/January 2026/Wikipedia Education Program - Train The Trainer in Nepal|Wikipedia Education Program – Train The Trainer in Nepal]] * [[m:Special:MyLanguage/Education/News/January 2026/Wikipedia 25 celebration in the Igbo Wiki Fan Club Alvan and IMSU|Wikipedia 25 celebration in the Igbo Wiki Fan Club Alvan and IMSU]] * [[m:Special:MyLanguage/Education/News/January 2026/CBSUA boosts Open Knowledge and Local Culture through expanded Wiki Education Program|CBSUA boosts Open Knowledge and Local Culture through expanded Wiki Education Program]] * [[m:Special:MyLanguage/Education/News/January 2026/WikiChallenge African Schools: Young voices, real impact, and continued (reasonable) growth|WikiChallenge African Schools: Young voices, real impact, and continued (reasonable) growth]] * [[m:Special:MyLanguage/Education/News/January 2026/Updates on Auckland Museum Summer Student Programme|Updates on Auckland Museum Summer Student Programme]] * [[m:Special:MyLanguage/Education/News/January 2026/Stronger and bolder Wikiforhumanrights 2025 in Anambra Network|Stronger and bolder Wikiforhumanrights 2025 in Anambra Network]] * [[m:Special:MyLanguage/Education/News/January 2026/Official Opening of IFAK Secondary School Wiki Club: Engaging Youth in Learning Through Open Knowledge|Official Opening of IFAK Secondary School Wiki Club: Engaging Youth in Learning Through Open Knowledge]] * [[m:Special:MyLanguage/Education/News/January 2026/Greetings from the Jeronim de Rada WikiClub in Elbasan, Albania, for Christmas 2025|Greetings from the Jeronim de Rada WikiClub in Elbasan, Albania, for Christmas 2025]] * [[m:Special:MyLanguage/Education/News/January 2026/Great and productive final activities of 2025 Wikimedia MKD education programme|Great and productive final activities of 2025 Wikimedia MKD education programme]] * [[m:Special:MyLanguage/Education/News/January 2026/Envisioning an Open Future together - WikiForAll|Envisioning an Open Future together – WikiForAll]] * [[m:Special:MyLanguage/Education/News/January 2026/A look back: reviewing the main education activities in Brazil in 2025|A look back: reviewing the main education activities in Brazil in 2025]] * [[m:Special:MyLanguage/Education/News/January 2026/A 147-Year-Old Institution Celebrates 25 Years of Wikipedia: St Aloysius University and the Spirit of Open Knowledge|A 147-Year-Old Institution Celebrates 25 Years of Wikipedia: St Aloysius University and the Spirit of Open Knowledge]] * [[m:Special:MyLanguage/Education/News/January 2026/¡Celebrando 25 años de conocimiento libre! El Proyecto "25x25" llega a las aulas de Córdoba, Argentina|Celebrating 25 years of free knowledge! The '25x25' Project reaches the classrooms of Córdoba, Argentina]] * [[m:Special:MyLanguage/Education/News/January 2026/A atuação em rede da Universidade Federal de Juiz de Fora para a difusão do conhecimento livre na Wikipédia|The collaborative efforts of the Federal University of Juiz de Fora for the dissemination of free knowledge on Wikipedia]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 18:26, 28 January 2026 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=29951116 --> == This Month in Education: February 2026 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 15 • Issue 2 • February 2026</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/February 2026|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/February 2026/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/February 2026/Cairo University Spanish Language Volunteers document Madrid’s Historic and Contemporary Palaces|Cairo University Spanish Language Volunteers document Madrid’s Historic and Contemporary Palaces]] * [[m:Special:MyLanguage/Education/News/February 2026/Celebrating 25 Years of Wikipedia in Uzbekistan|Celebrating 25 Years of Wikipedia in Uzbekistan]] * [[m:Special:MyLanguage/Education/News/February 2026/Encontro da Rede Latino Americana de Inteligência Artificial Feminista: construindo futuros possíveis|Meeting of the Latin American Network of Feminist Artificial Intelligence: building possible futures]] * [[m:Special:MyLanguage/Education/News/February 2026/Farewelling the Auckland Museum Summer Students|Farewelling the Auckland Museum Summer Students]] * [[m:Special:MyLanguage/Education/News/February 2026/Inclusive Climate Learning with Wikimedia Reaches Special School in Kumasi|Inclusive Climate Learning with Wikimedia Reaches Special School in Kumasi]] * [[m:Special:MyLanguage/Education/News/February 2026/Introducing Wikimedia in Academic curriculum for students of higher education in universities of Telangana |Introducing Wikimedia in Academic curriculum for students of higher education in universities of Telangana]] * [[m:Special:MyLanguage/Education/News/February 2026/Learning from Finland: Edit-a-thon on Finnish Education set to take place in Belgrade|Learning from Finland: Edit-a-thon on Finnish Education set to take place in Belgrade]] * [[m:Special:MyLanguage/Education/News/February 2026/Library of IME-USP Workshop: Edits in History of Mathematics|Library of IME-USP Workshop: Edits in History of Mathematics]] * [[m:Special:MyLanguage/Education/News/February 2026/LitFest 2026: Room to Dream to amplify local voices across Wikimedia|LitFest 2026: Room to Dream to amplify local voices across Wikimedia]] * [[m:Special:MyLanguage/Education/News/February 2026/New online workshops for the German language Wikipedia|New online workshops for the German language Wikipedia]] * [[m:Special:MyLanguage/Education/News/February 2026/Road to Wiki Cohort 1: Building India's Next Generation of Wikimedia Technical Contributors|Road to Wiki Cohort 1: Building India's Next Generation of Wikimedia Technical Contributors]] * [[m:Special:MyLanguage/Education/News/February 2026/The history of the Wikimedia movement in a Brazil: a book about stories and projects|The history of the Wikimedia movement in a Brazil: a book about stories and projects]] * [[m:Special:MyLanguage/Education/News/February 2026/Wiki Club Federal Government Boys College Celebrates Mother Tongue Day|Wiki Club Federal Government Boys College Celebrates Mother Tongue Day]] * [[m:Special:MyLanguage/Education/News/February 2026/Wiki Club Minalabac joins Freedom to Read 2026: One World, Many Languages|Wiki Club Minalabac joins Freedom to Read 2026: One World, Many Languages]] * [[m:Special:MyLanguage/Education/News/February 2026/Wiki Love Folklore Photowalk at Khajuraho Dance Festival 2026|Wiki Love Folklore Photowalk at Khajuraho Dance Festival 2026]] * [[m:Special:MyLanguage/Education/News/February 2026/Wiki Loves Fish Workshop Empowers Students to Document Coastal Biodiversity|Wiki Loves Fish Workshop Empowers Students to Document Coastal Biodiversity]] * [[m:Special:MyLanguage/Education/News/February 2026/WikiCendekia 2026: Insights from our training of admins in Indonesia|WikiCendekia 2026: Insights from our training of admins in Indonesia]] * [[m:Special:MyLanguage/Education/News/February 2026/Wikimedia MKD's activities- new wiki club and a lots of new training workshops|Wikimedia MKD's activities- new wiki club and a lots of new training workshops]] * [[m:Special:MyLanguage/Education/News/February 2026/WikiPatrimoine Senghor : Valorisation du patrimoine culturel africain à l'Université Senghor|WikiPatrimoine Senghor : Valuation of African cultural heritage at the University Senghor]] * [[m:Special:MyLanguage/Education/News/February 2026/Wikipedia Turns 25: Young Voices, Big Future|Wikipedia Turns 25: Young Voices, Big Future]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 11:55, 3 March 2026 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=30155806 --> == This Month in Education: March 2026 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 15 • Issue 3 • March 2026</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/March 2026|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/March 2026/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/March 2026/Advancing 21st-Century Education: Proposal to Establish the Yorùbá Wikipedia Fan Club at Arolu College of Education, Ilemona|Advancing 21st-Century Education: Proposal to Establish the Yorùbá Wikipedia Fan Club at Arolu College of Education, Ilemona]] * [[m:Special:MyLanguage/Education/News/March 2026/Awareness Programme on Language and Culture Protection by KWUG|Awareness Programme on Language and Culture Protection by KWUG]] * [[m:Special:MyLanguage/Education/News/March 2026/Teachers from Various Institutions in Rio de Janeiro Explore Wikipedia as a Means of Preserving Memory and Checking Sources|Teachers from Various Institutions in Rio de Janeiro Explore Wikipedia as a Means of Preserving Memory and Checking Sources]] * [[m:Special:MyLanguage/Education/News/March 2026/Edu Wiki Nigeria Co-Founder Facilitates Textbook Donation to AHAJAS Integrated School, Gombe|Edu Wiki Nigeria Co-Founder Facilitates Textbook Donation to AHAJAS Integrated School, Gombe]] * [[m:Special:MyLanguage/Education/News/March 2026/Inside Wikimedia Ukraine's education program|Inside Wikimedia Ukraine's education program]] * [[m:Special:MyLanguage/Education/News/March 2026/Karavali Wikimedians at Mangaluru Design Summit 2026|Karavali Wikimedians at Mangaluru Design Summit 2026]] * [[m:Special:MyLanguage/Education/News/March 2026/One School, One Article Campaign Wrap Up|One School, One Article Campaign Wrap Up]] * [[m:Special:MyLanguage/Education/News/March 2026/Seeds of Knowledge: A Wiki Project that Sparked a Community at ADUN|Seeds of Knowledge: A Wiki Project that Sparked a Community at ADUN]] * [[m:Special:MyLanguage/Education/News/March 2026/Student workshops at Serbian Universities: enriching Wikipedia with topics on culture and technology|Student workshops at Serbian Universities: enriching Wikipedia with topics on culture and technology]] * [[m:Special:MyLanguage/Education/News/March 2026/The Open Knowledge Alliance: Wikimedia and Libraries|The Open Knowledge Alliance: Wikimedia and Libraries]] * [[m:Special:MyLanguage/Education/News/March 2026/Wikimedia CR published updated guide for beginners|Wikimedia CR published updated guide for beginners]] * [[m:Special:MyLanguage/Education/News/March 2026/Wikimedia goes back to the classroom in Brazil|Wikimedia goes back to the classroom in Brazil]] * [[m:Special:MyLanguage/Education/News/March 2026/Workshop on Feminism and Folklore 2026 by Wiki Club SATI|Workshop on Feminism and Folklore 2026 by Wiki Club SATI]] * [[m:Special:MyLanguage/Education/News/March 2026/“Wikimedia MKD in Action: Teacher Conferences and Education Activities|“Wikimedia MKD in Action: Teacher Conferences and Education Activities]] * [[m:Special:MyLanguage/Education/News/March 2026/Wikipedia & Libraries: Building New Contributors|Wikipedia & Libraries: Building New Contributors]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 10:21, 1 April 2026 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=30317659 --> == This Month in Education: April 2026 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 15 • Issue 4 • April 2026</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/April 2026|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/April 2026/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/April 2026/Empowering Knowledge: Wikimedia MKD Education Update|Empowering Knowledge: Wikimedia MKD Education Update]] * [[m:Special:MyLanguage/Education/News/April 2026/WikiScholar: A School-Level Initiative to Promote Free Knowledge in Bangladesh|WikiScholar: A School-Level Initiative to Promote Free Knowledge in Bangladesh]] * [[m:Special:MyLanguage/Education/News/April 2026/Wikipedia for School 2025–2026: A Competition That Continued Despite Frost, Power Outages, and War|Wikipedia for School 2025–2026: A Competition That Continued Despite Frost, Power Outages, and War]] * [[m:Special:MyLanguage/Education/News/April 2026/Wikimedia UK and Thoughtful delivery new media literacy teacher training course|Wikimedia UK and Thoughtful delivery new media literacy teacher training course]] * [[m:Special:MyLanguage/Education/News/April 2026/Wikimedia CR supporting SDG's in Czech schools|Wikimedia CR supporting SDG's in Czech schools]] * [[m:Special:MyLanguage/Education/News/April 2026/University Students’ Mandatory Internships at Wikimedia Armenia|University Students’ Mandatory Internships at Wikimedia Armenia]] * [[m:Special:MyLanguage/Education/News/April 2026/Third year of collaboration with Aleksandër Xhuvani University in Elbasan, Albania|Third year of collaboration with Aleksandër Xhuvani University in Elbasan, Albania]] * [[m:Special:MyLanguage/Education/News/April 2026/Students Discover Open Source and Learn Wikipedia and Wikidata Skills for the First Time in Zarqa, Jordan|Students Discover Open Source and Learn Wikipedia and Wikidata Skills for the First Time in Zarqa, Jordan]] * [[m:Special:MyLanguage/Education/News/April 2026/Leveraging on Wikipedia as a tool for curbing Health Misinformation and Disinformation in Akwa Ibom and Rivers State, Nigeria|Leveraging on Wikipedia as a tool for curbing Health Misinformation and Disinformation in Akwa Ibom and Rivers State, Nigeria]] * [[m:Special:MyLanguage/Education/News/April 2026/Governance and Public Knowledge: Wikipedia as a Learning Tool in Sustainability Education through UNESCO Designated Sites|Governance and Public Knowledge: Wikipedia as a Learning Tool in Sustainability Education through UNESCO Designated Sites]] * [[m:Special:MyLanguage/Education/News/April 2026/A month full of encounters with students in Brazil|A month full of encounters with students in Brazil]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 16:01, 27 April 2026 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=30406002 --> == This Month in Education: May 2026 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 15 • Issue 5 • May 2026</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/May 2026|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/May 2026/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/May 2026/Teaching innovation with Wikimedia. Shared experiences in Spanish Universities|Teaching innovation with Wikimedia. Shared experiences in Spanish Universities]] * [[m:Special:MyLanguage/Education/News/May 2026/Editing Wikipedia with Viktor Hygo High School in Albania|Editing Wikipedia with Viktor Hygo High School in Albania]] * [[m:Special:MyLanguage/Education/News/May 2026/Debating free license in Brazil|Debating free license in Brazil]] * [[m:Special:MyLanguage/Education/News/May 2026/Microclimatic Explainers: A short-form media approach to build micro-level environmental awareness in India|Microclimatic Explainers: A short-form media approach to build micro-level environmental awareness in India]] * [[m:Special:MyLanguage/Education/News/May 2026/Ukraine publishes the first academic collection of papers on Wikipedia and Wikimedia Projects|Ukraine publishes the first academic collection of papers on Wikipedia and Wikimedia Projects]] * [[m:Special:MyLanguage/Education/News/May 2026/Wiki Digital Youth Club Launches in Tanzania: Youth Build Digital Skills Through Competitive Quest Challenges|Wiki Digital Youth Club Launches in Tanzania: Youth Build Digital Skills Through Competitive Quest Challenges]] * [[m:Special:MyLanguage/Education/News/May 2026/Wiki Youth Participation in Building Rwanda’s Open Knowledge Ecosystem|Wiki Youth Participation in Building Rwanda’s Open Knowledge Ecosystem]] * [[m:Special:MyLanguage/Education/News/May 2026/Wikimedia Digi-Youth Club in Nigeria|Wikimedia Digi-Youth Club in Nigeria]] * [[m:Special:MyLanguage/Education/News/May 2026/Wikimedia MKD's Education News & Activities|Wikimedia MKD's Education News & Activities]] * [[m:Special:MyLanguage/Education/News/May 2026/Wikipedia Serbia's interns and Wiki Ambassadors provide crucial support towards end of the school year|Wikipedia Serbia's interns and Wiki Ambassadors provide crucial support towards end of the school year]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 16:53, 1 June 2026 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=30604297 --> == This Month in Education: June 2026 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 15 • Issue 6 • June 2026</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/June 2026|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/June 2026/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/June 2026/Wikipedia Editathon at Dinajpur Govt. College: Empowering Graduate Students in the Open Knowledge Movement|Wikipedia Editathon at Dinajpur Govt. College: Empowering Graduate Students in the Open Knowledge Movement]] * [[m:Special:MyLanguage/Education/News/June 2026/Wikimedia Serbia prepares for Edu Wiki camp 2026|Wikimedia Serbia prepares for Edu Wiki camp 2026]] * [[m:Special:MyLanguage/Education/News/June 2026/Wiki Digi-Youth Clubs pilot explores challenge-based learning across three countries|Wiki Digi-Youth Clubs pilot explores challenge-based learning across three countries]] * [[m:Special:MyLanguage/Education/News/June 2026/Why the EduWiki Hub Starter Kit Matters for the Future of Education|Why the EduWiki Hub Starter Kit Matters for the Future of Education]] * [[m:Special:MyLanguage/Education/News/June 2026/Portuguese Universities adopt free knowledge tools: Wikipedia is the favorite|Portuguese Universities adopt free knowledge tools: Wikipedia is the favorite]] * [[m:Special:MyLanguage/Education/News/June 2026/Translating on Wikipedia used as extra – credit assignment in University of Prishtina, Kosovo|Translating on Wikipedia used as extra – credit assignment in University of Prishtina, Kosovo]] * [[m:Special:MyLanguage/Education/News/June 2026/Strengthening Wikimedia Education Through Community Learning and Digital Literacy Initiatives|Strengthening Wikimedia Education Through Community Learning and Digital Literacy Initiatives]] * [[m:Special:MyLanguage/Education/News/June 2026/Small Group, Big Impact: Building Skills Through the Wikimedia Volunteer Focus Group in Botswana|Small Group, Big Impact: Building Skills Through the Wikimedia Volunteer Focus Group in Botswana]] * [[m:Special:MyLanguage/Education/News/June 2026/"25x25 Project – Celebrating Wikipedia" in Córdoba, Argentina|"25x25 Project – Celebrating Wikipedia" in Córdoba, Argentina]] * [[m:Special:MyLanguage/Education/News/June 2026/Mapping and gathering educational activities on Wiki in Brazilian universities|Mapping and gathering educational activities on Wiki in Brazilian universities]] * [[m:Special:MyLanguage/Education/News/June 2026/Growing Wiki Education in the Philippines: Highlights from Bikol WikiConference 2026|Growing Wiki Education in the Philippines: Highlights from Bikol WikiConference 2026]] * [[m:Special:MyLanguage/Education/News/June 2026/From Mentee to Builder: Six Months in the EduWiki Hub Mentorship Program|From Mentee to Builder: Six Months in the EduWiki Hub Mentorship Program]] * [[m:Special:MyLanguage/Education/News/June 2026/EduWiki Hub publishes its first Community Newsletter|EduWiki Hub publishes its first Community Newsletter]] * [[m:Special:MyLanguage/Education/News/June 2026/Click, Capture, and Contribute: Scaling Open Knowledge Through Mobile Photography|Click, Capture, and Contribute: Scaling Open Knowledge Through Mobile Photography]] * [[m:Special:MyLanguage/Education/News/June 2026/Education in Action: Limkokwing School Adoption Program 2026 and Wikimedia Learning Outcomes|Education in Action: Limkokwing School Adoption Program 2026 and Wikimedia Learning Outcomes]] * [[m:Special:MyLanguage/Education/News/June 2026/Impact of Wiki Digi youth Clubs initiative in education of Rwanda|Impact of Wiki Digi youth Clubs initiative in education of Rwanda]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 04:15, 28 June 2026 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=30725833 --> == This Month in Education: July 2026 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 15 • Issue 7 • July 2026</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/July 2026|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/July 2026/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/July 2026/Practical Wikipedia Training for Teachers Held in Tetovo, Macedonia|Practical Wikipedia Training for Teachers Held in Tetovo, Macedonia]] * [[m:Special:MyLanguage/Education/News/July 2026/Wikimedia Ukraine at the Teachers of the Future Festival|Wikimedia Ukraine at the Teachers of the Future Festival]] * [[m:Special:MyLanguage/Education/News/July 2026/Six Months of Growth, Learning, and Impact: My Journey as an EduWiki Mentor|Six Months of Growth, Learning, and Impact: My Journey as an EduWiki Mentor]] * [[m:Special:MyLanguage/Education/News/July 2026/PhilWiki Community pays homage to Antoine de Saint-Exupéry at Wikimania Paris 2026|PhilWiki Community pays homage to Antoine de Saint-Exupéry at Wikimania Paris 2026]] * [[m:Special:MyLanguage/Education/News/July 2026/Google25 Expands Tamil Wikipedia Community|Google25 Expands Tamil Wikipedia Community]] * [[m:Special:MyLanguage/Education/News/July 2026/Edu Wiki camp gathers Serbian youth around the topic of open knowledge|Edu Wiki camp gathers Serbian youth around the topic of open knowledge]] * [[m:Special:MyLanguage/Education/News/July 2026/Cátedra Glaciares: A Collaborative Experience for the Study and Conservation of Colombia’s Cryosphere|Cátedra Glaciares: A Collaborative Experience for the Study and Conservation of Colombia’s Cryosphere]] * [[m:Special:MyLanguage/Education/News/July 2026/Continuing Wiki education partnerships in Brazil|Continuing Wiki education partnerships in Brazil]] * [[m:Special:MyLanguage/Education/News/July 2026/Building EduWiki in Albania: From school outreach to student contributions in Wikimedia projects|Building EduWiki in Albania: From school outreach to student contributions in Wikimedia projects]] * [[m:Special:MyLanguage/Education/News/July 2026/1Lib1Ref WUGN Kaduna, 2026|1Lib1Ref WUGN Kaduna, 2026]] * [[m:Special:MyLanguage/Education/News/July 2026/We create the first master class on access to knowledge and open technology in collaboration with National Autonomous University of Mexico, UNAM|We create the first master class on access to knowledge and open technology in collaboration with National Autonomous University of Mexico, UNAM]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 19:48, 30 July 2026 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=30838310 --> == This Month in Education: August 2026 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 15 • Issue 8 • August 2026</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/August 2026|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/August 2026/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/August 2026/Coordinating Wikimedia's Presence in Iraqi Universities|Coordinating Wikimedia's Presence in Iraqi Universities]] * [[m:Special:MyLanguage/Education/News/August 2026/The EduWiki Hub Starter Kit Is Now Available in Spanish|The EduWiki Hub Starter Kit Is Now Available in Spanish]] * [[m:Special:MyLanguage/Education/News/August 2026/Wiki and democracy campaign launches in Brazil|Wiki and democracy campaign launches in Brazil]] * [[m:Special:MyLanguage/Education/News/August 2026/Wiki Clubs strengthen youth participation in open knowledge in the Philippines|Wiki Clubs strengthen youth participation in open knowledge in the Philippines]] * [[m:Special:MyLanguage/Education/News/August 2026/Wikidata for research in the UI1|Wikidata for research in the UI1]] * [[m:Special:MyLanguage/Education/News/August 2026/Nupe Wikipedia Hits 1,000 Articles: The Next Chapter in Our Knowledge Journey |Nupe Wikipedia Hits 1,000 Articles: The Next Chapter in Our Knowledge Journey]] * [[m:Special:MyLanguage/Education/News/August 2026/Recruiting newcomers to preserve Yiddish using Wiktionary as a tool|Recruiting newcomers to preserve Yiddish using Wiktionary as a tool]] * [[m:Special:MyLanguage/Education/News/August 2026/Voices in Our Hands: How Nigerian Kids are Documenting Nigerian Sign Language for the World|Voices in Our Hands: How Nigerian Kids are Documenting Nigerian Sign Language for the World]] * [[m:Special:MyLanguage/Education/News/August 2026/Wiki in Schools, Architecture and Open Heritage|Wiki in Schools, Architecture and Open Heritage]] * [[m:Special:MyLanguage/Education/News/August 2026/More than 200 registrations, 22 speakers, and seven hours of shared experience: Wikimedia Ukraine’s Education Community Conference 2026|More than 200 registrations, 22 speakers, and seven hours of shared experience: Wikimedia Ukraine’s Education Community Conference 2026]] * [[m:Special:MyLanguage/Education/News/August 2026/Launch of Wikifying a Conference handbook|Launch of Wikifying a Conference handbook]] * [[m:Special:MyLanguage/Education/News/August 2026/EduWiki Hub Updates: Working Groups Feedback Session and a New Roundtable for Program Officers|EduWiki Hub Updates: Working Groups Feedback Session and a New Roundtable for Program Officers]] * [[m:Special:MyLanguage/Education/News/August 2026/Curiosity through academic inquiry - learning by writing Wikipedia articles in Serbia|Curiosity through academic inquiry - learning by writing Wikipedia articles in Serbia]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 17:54, 1 September 2026 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=30917014 --> == This Month in Education: September 2026 == <div class="plainlinks" lang="en" dir="ltr"> <div style="text-align: center;"> <span style="font-weight:bold; color:#00A7E2; font-size:2.9em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;">This Month in Education</span> <span style="font-weight:bold; color:#00A7E2; font-size:1.4em; font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;"> Volume 15 • Issue 9 • September 2026</span> <div style="border-top:1px solid #a2a9b1; border-bottom:1px solid #a2a9b1; padding:0.5em; font-size:larger; margin-bottom:0.2em">[[m:Special:MyLanguage/Education/Newsletter/September 2026|Contents]] • [[m:Special:MyLanguage/Education/Newsletter/September 2026/Headlines|Headlines]] • [[m:Special:MyLanguage/Global message delivery/Targets/This Month in Education|Subscribe]]</div> <div style="color:white; font-size:1.8em; font-family:Montserrat; background:#92BFB1;">In This Issue</div></div> <div style="text-align: left; column-count: 2; column-width: 35em;"> * [[m:Special:MyLanguage/Education/News/September 2026/Wikipedia Writing Training at Universitas Terbuka. WikiRempah Welcomes Wikimedians in Ternate|Wikipedia Writing Training at Universitas Terbuka. WikiRempah Welcomes Wikimedians in Ternate]] * [[m:Special:MyLanguage/Education/News/September 2026/Wikimedia MKD’s Wiki Camp & Team Building 2026|Wikimedia MKD’s Wiki Camp & Team Building 2026]] * [[m:Special:MyLanguage/Education/News/September 2026/Wikimedia Commons Training for Students at Universitas Nurul Hasan Bacan: Mobilizing Bacan's Youth with WikiRempah|Wikimedia Commons Training for Students at Universitas Nurul Hasan Bacan: Mobilizing Bacan's Youth with WikiRempah]] * [[m:Special:MyLanguage/Education/News/September 2026/Wikidata integration in the Library & Information Science course|Wikidata integration in the Library & Information Science course]] * [[m:Special:MyLanguage/Education/News/September 2026/Translating the EduWiki Newcomer's Starter Kit in Albanian language|Translating the EduWiki Newcomer's Starter Kit in Albanian language]] * [[m:Special:MyLanguage/Education/News/September 2026/Training Wikimedia Commons WikiRempah in Bacan, Bringing Digital Education to an Island Without Electricity|Training Wikimedia Commons WikiRempah in Bacan, Bringing Digital Education to an Island Without Electricity]] * [[m:Special:MyLanguage/Education/News/September 2026/Synergy Between WikiRempah, the West Halmahera Regency Education and Culture Office, and the Sultanate of Jailolo in Documenting Spice Route Cultural Sites|Synergy Between WikiRempah, the West Halmahera Regency Education and Culture Office, and the Sultanate of Jailolo in Documenting Spice Route Cultural Sites]] * [[m:Special:MyLanguage/Education/News/September 2026/St Aloysius Wiki Club Celebrates 10th Anniversary of Tulu Wikipedia|St Aloysius Wiki Club Celebrates 10th Anniversary of Tulu Wikipedia]] * [[m:Special:MyLanguage/Education/News/September 2026/Road to Open Source: bringing open source contribution into Indian engineering classrooms|Road to Open Source: bringing open source contribution into Indian engineering classrooms]] * [[m:Special:MyLanguage/Education/News/September 2026/Photography and education: initiatives in Brazil|Photography and education: initiatives in Brazil]] * [[m:Special:MyLanguage/Education/News/September 2026/Open Knowledge Initiatives Summer Internship 2026 – Project Workflow & Learnings|Open Knowledge Initiatives Summer Internship 2026 – Project Workflow & Learnings]] * [[m:Special:MyLanguage/Education/News/September 2026/Media Literacy Teacher Training with Wikimedia UK and Thoughtful|Media Literacy Teacher Training with Wikimedia UK and Thoughtful]] * [[m:Special:MyLanguage/Education/News/September 2026/Heritage Across Borders: St Aloysius Wiki Club Students Celebrate Cultural Heritage Through Wikipedia|Heritage Across Borders: St Aloysius Wiki Club Students Celebrate Cultural Heritage Through Wikipedia]] * [[m:Special:MyLanguage/Education/News/September 2026/From Bandung's Street Signs to Wikipedia: Rediscovering Sundanese Script|From Bandung's Street Signs to Wikipedia: Rediscovering Sundanese Script]] * [[m:Special:MyLanguage/Education/News/September 2026/CSPC Wiki Club launches student community for open knowledge and youth leadership|CSPC Wiki Club launches student community for open knowledge and youth leadership]] * [[m:Special:MyLanguage/Education/News/September 2026/Amplifying Underrepresented Voices: Lessons from the Language Diversity Hub 2026|Amplifying Underrepresented Voices: Lessons from the Language Diversity Hub 2026]] * [[m:Special:MyLanguage/Education/News/September 2026/Education activity: Can I trust Wikipedia?|Education activity: Can I trust Wikipedia?]] </div> <div style="margin-top:10px; text-align: center; font-size:90%; padding-left:5px; font-family:Georgia, Palatino, Palatino Linotype, Times, Times New Roman, serif;">[[m:Special:MyLanguage/Education/Newsletter/About|About ''This Month in Education'']] · [[m:Global message delivery/Targets/This Month in Education|Subscribe/Unsubscribe]] · [[m:Special:MyLanguage/MassMessage|Global message delivery]] · For the team: [[:m:User:ZI Jony|ZI Jony]] 18:36, 30 September 2026 (UTC)</div> </div> <!-- Message sent by User:ZI Jony@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Global_message_delivery/Targets/This_Month_in_Education&oldid=31092240 --> 22ucwkkrtepu5e5ktmgehpnekxxy92b 0 171005 2835181 2835055 2026-09-30T13:00:58Z Young1lim 21186 /* Geometric Series Examples */ 2835181 wikitext text/x-wiki Many of the functions that arise naturally in mathematics and real world applications can be extended to and regarded as complex functions, meaning the input, as well as the output, can be complex numbers <math>x+iy</math>, where <math>i=\sqrt{-1}</math>, in such a way that it is a more natural object to study. '''Complex analysis''', which used to be known as '''function theory''' or '''theory of functions of a single complex variable''', is a sub-field of analysis that studies such functions (more specifically, '''holomorphic''' functions) on the complex plane, or part (domain) or extension (Riemann surface) thereof. It notably has great importance in number theory, e.g. the [[Riemann zeta function]] (for the distribution of primes) and other <math>L</math>-functions, modular forms, elliptic functions, etc. <blockquote>The shortest path between two truths in the real domain passes through the complex domain. — [[wikipedia:Jacques_Hadamard|Jacques Hadamard]]</blockquote>In a certain sense, the essence of complex functions is captured by the principle of [[analytic continuation]].{{mathematics}} ==''' Complex Functions '''== * Complex Functions ([[Media:CAnal.1.A.CFunction.20140222.Basic.pdf|1.A.pdf]], [[Media:CAnal.1.B.CFunction.20140111.Octave.pdf|1.B.pdf]], [[Media:CAnal.1.C.CFunction.20140111.Extend.pdf|1.C.pdf]]) * Complex Exponential and Logarithm ([[Media:CAnal.5.A.CLog.20131017.pdf|5.A.pdf]], [[Media:CAnal.5.A.Octave.pdf|5.B.pdf]]) * Complex Trigonometric and Hyperbolic ([[Media:CAnal.7.A.CTrigHyper..pdf|7.A.pdf]], [[Media:CAnal.7.A.Octave..pdf|7.B.pdf]]) '''Complex Function Note''' : 1. Exp and Log Function Note ([[Media:ComplexExp.29160721.pdf|H1.pdf]]) : 2. Trig and TrigH Function Note ([[Media:CAnal.Trig-H.29160901.pdf|H1.pdf]]) : 3. Inverse Trig and TrigH Functions Note ([[Media:CAnal.Hyper.29160829.pdf|H1.pdf]]) ==''' Complex Integrals '''== * Complex Integrals ([[Media:CAnal.2.A.CIntegral.20140224.Basic.pdf|2.A.pdf]], [[Media:CAnal.2.B.CIntegral.20140117.Octave.pdf|2.B.pdf]], [[Media:CAnal.2.C.CIntegral.20140117.Extend.pdf|2.C.pdf]]) ==''' Complex Series '''== * Complex Series ([[Media:CPX.Series.20150226.2.Basic.pdf|3.A.pdf]], [[Media:CAnal.3.B.CSeries.20140121.Octave.pdf|3.B.pdf]], [[Media:CAnal.3.C.CSeries.20140303.Extend.pdf|3.C.pdf]]) ==''' Residue Integrals '''== * Residue Integrals ([[Media:CAnal.4.A.Residue.20140227.Basic.pdf|4.A.pdf]], [[Media:CAnal.4.B.pdf|4.B.pdf]], [[Media:CAnal.4.C.Residue.20140423.Extend.pdf|4.C.pdf]]) ==='''Residue Integrals Note'''=== * Laurent Series with the Residue Theorem Note ([[Media:Laurent.1.Residue.20170713.pdf|H1.pdf]]) * Laurent Series with Applications Note ([[Media:Laurent.2.Applications.20170327.pdf|H1.pdf]]) * Laurent Series and the z-Transform Note ([[Media:Laurent.3.z-Trans.20170831.pdf|H1.pdf]]) * Laurent Series as a Geometric Series Note ([[Media:Laurent.4.GSeries.20170802.pdf|H1.pdf]]) === Laurent Series and the z-Transform Example Note === * Overview ([[Media:Laurent.4.z-Example.20170926.pdf|H1.pdf]]) ====Geometric Series Examples==== * Causality ([[Media:Laurent.5.Causality.1.A.20191026n.pdf|A.pdf]], [[Media:Laurent.5.Causality.1.B.20191026.pdf|B.pdf]]) * Time Shift ([[Media:Laurent.5.TimeShift.2.A.20191028.pdf|A.pdf]], [[Media:Laurent.5.TimeShift.2.B.20191029.pdf|B.pdf]]) * Reciprocity ([[Media:Laurent.5.Reciprocity.3A.20191030.pdf|A.pdf]], [[Media:Laurent.5.Reciprocity.3B.20191031.pdf|B.pdf]]) * Combinations ([[Media:Laurent.5.Combination.4A.20200702.pdf|A.pdf]], [[Media:Laurent.5.Combination.4B.20201002.pdf|B.pdf]]) * Properties ([[Media:Laurent.5.Property.5A.20220105.pdf|A.pdf]], [[Media:Laurent.5.Property.5B.20220126.pdf|B.pdf]]) * Permutations ([[Media:Laurent.6.Permutation.6A.20230711.pdf|A.pdf]], [[Media:Laurent.5.Permutation.6B.20251225.pdf|B.pdf]], [[Media:Laurent.5.Permutation.6C.20260929.pdf|C.pdf]], [[Media:Laurent.5.Permutation.6C.20240528.pdf|D.pdf]]) * Applications ([[Media:Laurent.5.Application.6B.20220723.pdf|A.pdf]]) * Double Pole Case :- Examples ([[Media:Laurent.5.DPoleEx.7A.20220722.pdf|A.pdf]], [[Media:Laurent.5.DPoleEx.7B.20220720.pdf|B.pdf]]) :- Properties ([[Media:Laurent.5.DPoleProp.5A.20190226.pdf|A.pdf]], [[Media:Laurent.5.DPoleProp.5B.20190228.pdf|B.pdf]]) ====The Case Examples==== * Example Overview : ([[Media:Laurent.4.Example.0.A.20171208.pdf|0A.pdf]], [[Media:Laurent.6.CaseExample.0.B.20180205.pdf|0B.pdf]]) * Example Case 1 : ([[Media:Laurent.4.Example.1.A.20171107.pdf|1A.pdf]], [[Media:Laurent.4.Example.1.B.20171227.pdf|1B.pdf]]) * Example Case 2 : ([[Media:Laurent.4.Example.2.A.20171107.pdf|2A.pdf]], [[Media:Laurent.4.Example.2.B.20171227.pdf|2B.pdf]]) * Example Case 3 : ([[Media:Laurent.4.Example.3.A.20171017.pdf|3A.pdf]], [[Media:Laurent.4.Example.3.B.20171226.pdf|3B.pdf]]) * Example Case 4 : ([[Media:Laurent.4.Example.4.A.20171017.pdf|4A.pdf]], [[Media:Laurent.4.Example.4.B.20171228.pdf|4B.pdf]]) * Example Summary : ([[Media:Laurent.4.Example.5.A.20171212.pdf|5A.pdf]], [[Media:Laurent.4.Example.5.B.20171230.pdf|5B.pdf]]) ==''' Conformal Mapping '''== * Conformal Mapping ([[Media:CAnal.6.A.Conformal.20131224.pdf|6.A.pdf]], [[Media:CAnal.6.A.Octave..pdf|6.B.pdf]]) go to [ [[Electrical_%26_Computer_Engineering_Studies]] ] [[Category:Complex analysis]] 9ldq0yz8wg3h1node7kopo4eykjm7jr 2835331 2835181 2026-10-01T10:43:50Z Young1lim 21186 /* Geometric Series Examples */ 2835331 wikitext text/x-wiki Many of the functions that arise naturally in mathematics and real world applications can be extended to and regarded as complex functions, meaning the input, as well as the output, can be complex numbers <math>x+iy</math>, where <math>i=\sqrt{-1}</math>, in such a way that it is a more natural object to study. '''Complex analysis''', which used to be known as '''function theory''' or '''theory of functions of a single complex variable''', is a sub-field of analysis that studies such functions (more specifically, '''holomorphic''' functions) on the complex plane, or part (domain) or extension (Riemann surface) thereof. It notably has great importance in number theory, e.g. the [[Riemann zeta function]] (for the distribution of primes) and other <math>L</math>-functions, modular forms, elliptic functions, etc. <blockquote>The shortest path between two truths in the real domain passes through the complex domain. — [[wikipedia:Jacques_Hadamard|Jacques Hadamard]]</blockquote>In a certain sense, the essence of complex functions is captured by the principle of [[analytic continuation]].{{mathematics}} ==''' Complex Functions '''== * Complex Functions ([[Media:CAnal.1.A.CFunction.20140222.Basic.pdf|1.A.pdf]], [[Media:CAnal.1.B.CFunction.20140111.Octave.pdf|1.B.pdf]], [[Media:CAnal.1.C.CFunction.20140111.Extend.pdf|1.C.pdf]]) * Complex Exponential and Logarithm ([[Media:CAnal.5.A.CLog.20131017.pdf|5.A.pdf]], [[Media:CAnal.5.A.Octave.pdf|5.B.pdf]]) * Complex Trigonometric and Hyperbolic ([[Media:CAnal.7.A.CTrigHyper..pdf|7.A.pdf]], [[Media:CAnal.7.A.Octave..pdf|7.B.pdf]]) '''Complex Function Note''' : 1. Exp and Log Function Note ([[Media:ComplexExp.29160721.pdf|H1.pdf]]) : 2. Trig and TrigH Function Note ([[Media:CAnal.Trig-H.29160901.pdf|H1.pdf]]) : 3. Inverse Trig and TrigH Functions Note ([[Media:CAnal.Hyper.29160829.pdf|H1.pdf]]) ==''' Complex Integrals '''== * Complex Integrals ([[Media:CAnal.2.A.CIntegral.20140224.Basic.pdf|2.A.pdf]], [[Media:CAnal.2.B.CIntegral.20140117.Octave.pdf|2.B.pdf]], [[Media:CAnal.2.C.CIntegral.20140117.Extend.pdf|2.C.pdf]]) ==''' Complex Series '''== * Complex Series ([[Media:CPX.Series.20150226.2.Basic.pdf|3.A.pdf]], [[Media:CAnal.3.B.CSeries.20140121.Octave.pdf|3.B.pdf]], [[Media:CAnal.3.C.CSeries.20140303.Extend.pdf|3.C.pdf]]) ==''' Residue Integrals '''== * Residue Integrals ([[Media:CAnal.4.A.Residue.20140227.Basic.pdf|4.A.pdf]], [[Media:CAnal.4.B.pdf|4.B.pdf]], [[Media:CAnal.4.C.Residue.20140423.Extend.pdf|4.C.pdf]]) ==='''Residue Integrals Note'''=== * Laurent Series with the Residue Theorem Note ([[Media:Laurent.1.Residue.20170713.pdf|H1.pdf]]) * Laurent Series with Applications Note ([[Media:Laurent.2.Applications.20170327.pdf|H1.pdf]]) * Laurent Series and the z-Transform Note ([[Media:Laurent.3.z-Trans.20170831.pdf|H1.pdf]]) * Laurent Series as a Geometric Series Note ([[Media:Laurent.4.GSeries.20170802.pdf|H1.pdf]]) === Laurent Series and the z-Transform Example Note === * Overview ([[Media:Laurent.4.z-Example.20170926.pdf|H1.pdf]]) ====Geometric Series Examples==== * Causality ([[Media:Laurent.5.Causality.1.A.20191026n.pdf|A.pdf]], [[Media:Laurent.5.Causality.1.B.20191026.pdf|B.pdf]]) * Time Shift ([[Media:Laurent.5.TimeShift.2.A.20191028.pdf|A.pdf]], [[Media:Laurent.5.TimeShift.2.B.20191029.pdf|B.pdf]]) * Reciprocity ([[Media:Laurent.5.Reciprocity.3A.20191030.pdf|A.pdf]], [[Media:Laurent.5.Reciprocity.3B.20191031.pdf|B.pdf]]) * Combinations ([[Media:Laurent.5.Combination.4A.20200702.pdf|A.pdf]], [[Media:Laurent.5.Combination.4B.20201002.pdf|B.pdf]]) * Properties ([[Media:Laurent.5.Property.5A.20220105.pdf|A.pdf]], [[Media:Laurent.5.Property.5B.20220126.pdf|B.pdf]]) * Permutations ([[Media:Laurent.6.Permutation.6A.20230711.pdf|A.pdf]], [[Media:Laurent.5.Permutation.6B.20251225.pdf|B.pdf]], [[Media:Laurent.5.Permutation.6C.20260930.pdf|C.pdf]], [[Media:Laurent.5.Permutation.6C.20240528.pdf|D.pdf]]) * Applications ([[Media:Laurent.5.Application.6B.20220723.pdf|A.pdf]]) * Double Pole Case :- Examples ([[Media:Laurent.5.DPoleEx.7A.20220722.pdf|A.pdf]], [[Media:Laurent.5.DPoleEx.7B.20220720.pdf|B.pdf]]) :- Properties ([[Media:Laurent.5.DPoleProp.5A.20190226.pdf|A.pdf]], [[Media:Laurent.5.DPoleProp.5B.20190228.pdf|B.pdf]]) ====The Case Examples==== * Example Overview : ([[Media:Laurent.4.Example.0.A.20171208.pdf|0A.pdf]], [[Media:Laurent.6.CaseExample.0.B.20180205.pdf|0B.pdf]]) * Example Case 1 : ([[Media:Laurent.4.Example.1.A.20171107.pdf|1A.pdf]], [[Media:Laurent.4.Example.1.B.20171227.pdf|1B.pdf]]) * Example Case 2 : ([[Media:Laurent.4.Example.2.A.20171107.pdf|2A.pdf]], [[Media:Laurent.4.Example.2.B.20171227.pdf|2B.pdf]]) * Example Case 3 : ([[Media:Laurent.4.Example.3.A.20171017.pdf|3A.pdf]], [[Media:Laurent.4.Example.3.B.20171226.pdf|3B.pdf]]) * Example Case 4 : ([[Media:Laurent.4.Example.4.A.20171017.pdf|4A.pdf]], [[Media:Laurent.4.Example.4.B.20171228.pdf|4B.pdf]]) * Example Summary : ([[Media:Laurent.4.Example.5.A.20171212.pdf|5A.pdf]], [[Media:Laurent.4.Example.5.B.20171230.pdf|5B.pdf]]) ==''' Conformal Mapping '''== * Conformal Mapping ([[Media:CAnal.6.A.Conformal.20131224.pdf|6.A.pdf]], [[Media:CAnal.6.A.Octave..pdf|6.B.pdf]]) go to [ [[Electrical_%26_Computer_Engineering_Studies]] ] [[Category:Complex analysis]] grmosndcey4q8xg8jko1abzx108iyah 2 219126 2835156 2835151 2026-09-30T11:59:16Z ThaniosAkro 2805358 /* Calculate R */ 2835156 wikitext text/x-wiki ==Table== {| class="wikitable" |- | From <math>(3):</math> || <math>p^3</math>|| || <math>+Ap</math> || <math>+B</math>|| <math>= 0</math> || <math>\dots (5)</math> |- | From <math>(4):</math> || || <math>Cp^2</math>|| <math></math> || <math>+D</math>|| <math>= 0</math> || <math>\dots (6)</math> |- | <math>(5)*D</math> || <math>Dp^3</math>|| || <math>+DAp</math> || <math>+DB</math>|| <math>= 0</math> || <math>\dots (7)</math> |- | <math>(6)*B</math> || || <math>BCp^2</math>|| <math></math> || <math>+BD</math>|| <math>= 0</math> || <math>\dots (8)</math> |- | <math>(7)-(8)</math> || <math>Dp^3</math>||<math>-BCp^2</math> || <math>+DAp</math> || <math></math>|| <math>= 0</math> || <math>\dots (9)</math> |- | Simplify <math>(9)</math> || <math></math>||<math>Dp^2</math> || <math>-BCp</math> || <math>+DA</math>|| <math>= 0</math> || <math>\dots (10)</math> |- | <math>(6)*A</math> || || <math>ACp^2</math>|| <math></math> || <math>+AD</math>|| <math>= 0</math> || <math>\dots (11)</math> |- | <math>(10)-(11)</math> || <math></math>||<math>Dp^2-ACp^2</math> || <math>-BCp</math> || <math></math>|| <math>= 0</math> || <math>\dots (12)</math> |- | Simplify <math>(12)</math> || <math></math>|| || <math>Dp-ACp</math> || <math>-BC</math> || <math>= 0</math> || <math>\dots (13)</math> |} ====First result==== <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> Calculate values_of_i : <syntaxhighlight lang=python> print ('\nWhen ints become huge:') values_of_i = solveMbyN (matrix) sx = 'values_of_i' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> When ints become huge: solveMbyN (input_, level = -41) : <class 'OverflowError'> OverflowError('int too large to convert to float') Length of input = 23 input_[0] = Error in this row. input_[1] = Error in this row. input_[2] = Error in this row. input_[3] = [-7.048390979785929e+176, 1.1003906499643917e+176, 1.5070856217200028e+174, 1.955699032422673e+173, ...... 0.0] input_[4] = [510.0, 0.0, 0.0, 0.0, 320.0, -1150.0, 270.0, 0.0, 0.0, 320.0, -590.0, 270.0, 0.0, 0.0, 320.0, -590.0, ...... 0.0] input_[5] = [0.0, 520.0, 0.0, 0.0, 0.0, 270.0, -1060.0, 220.0, 0.0, 0.0, 270.0, -490.0, 220.0, 0.0, 0.0, 270.0, ...... 0.0] input_[6] = [0.0, 0.0, 530.0, 0.0, 0.0, 0.0, 220.0, -970.0, 170.0, 0.0, 0.0, 220.0, -390.0, 170.0, 0.0, 0.0, 220.0, ...... 0.0] input_[7] = Error in this row. values_of_i = None </syntaxhighlight> <syntaxhighlight lang=python> print ('\nConvert input to floats:') matrix1 = [ list(v) for v in matrix ] matrix1[0][0] = float(matrix1[0][0]) values_of_i = solveMbyN (matrix1) sx = 'values_of_i' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> Convert input to floats: solveMbyN (input_, level = -40) : <class 'KeyError'> KeyError('Internal error. input[1][0] = nan, should be 0.') Length of input = 24 input_[0] = [-1.7360455505275518e+174, 1.4096781959571856e+174, -2.2007812999287836e+173, -3.014171243439967e+171, ...... 0.0] input_[1] = [-3.7974175914221006e+162, 3.309163202261842e+161, 2.4114748810711523e+162, -4.426635506031073e+161, ...... 0.0] input_[2] = [-2.4975968400753463e+139, 5.704494025143264e+138, -2.7146889822895123e+138, 1.4057733058789272e+139, ...... 0.0] input_[3] = [7.667237322891148e+182, -1.7692205437935546e+182, -2.341735229706114e+180, 4.1615580570562045e+181, ...... -0.0] input_[4] = [-500.0, 0.0, 0.0, 0.0, 0.0, 1240.0, -320.0, 0.0, 0.0, 0.0, 690.0, -320.0, 0.0, 0.0, 0.0, 690.0, -320.0, ...... 0.0] input_[5] = [0.0, 510.0, 0.0, 0.0, 0.0, 320.0, -1150.0, 270.0, 0.0, 0.0, 320.0, -590.0, 270.0, 0.0, 0.0, 320.0, -590.0, ...... 0.0] input_[6] = [0.0, 0.0, 520.0, 0.0, 0.0, 0.0, 270.0, -1060.0, 220.0, 0.0, 0.0, 270.0, -490.0, 220.0, 0.0, 0.0, 270.0, ...... 0.0] input_[7] = [0.0, 0.0, 0.0, 530.0, 0.0, 0.0, 0.0, 220.0, -970.0, 170.0, 0.0, 0.0, 220.0, -390.0, 170.0, 0.0, 0.0, ...... 0.0] values_of_i = None </syntaxhighlight> =====Success===== <syntaxhighlight lang=python> print ('\nSet global variable enable_reduceRow:') enable_reduceRow = 1 values_of_i = solveMbyN (matrix1) </syntaxhighlight> Success: <syntaxhighlight> Set global variable enable_reduceRow: i10 = 1.0000000000000049 ; i11 = 1.643236374952256 ; i12 = 2.316468657232291 ; i13 = 3.0507456069545116 i14 = 3.908085797412319 ; i15 = 0.5970301043016677 ; i16 = 0.8274774533758196; i17 = 1.225283946841065 i18 = 1.5617922630400025 ; i19 = 0.369273540611037 ; i20 = 0.3858385105885722; i21 = 0.6270001063825295 i22 = 0.7040607630623028 ; i23 = 0.6129764173251202 ; i24 = 0.298576896960036 ; i25 = 0.44960726241462035 i26 = 0.7812212615819403 ; i27 = 0.7165761045550649 ; i28 = 0.5186812635664733; i29 = 0.266770119423805 i30 = 0.5896680016803755 ; i31 = 1.475274068751303 ; i32 = 0.9632057010422588; i33 = 0.5801910619990465 i34 = 0.30799558703953794; i35 = 2.4693659910366916 ; i36 = 1.583773707944257 ; i37 = 1.0123878002551232 i38 = 0.6135963601029517 ; i39 = 0.3175434839291887 ; i40 = 2.7147355593758107; i41 = 2.125067557695435 i42 = 1.6754602952808149 ; i43 = 1.2896217846922426 ; i44 = 0.692591680390575 ; i45 = 0.8855922830924343 i46 = 1.7538676385971101 ; i47 = 1.4222536394297902 ; i48 = 1.181092043635833 ; i49 = 0.6432363749522512 i50 = 0.5713859076891339 ; i51 = 1.0834542753981782 ; i52 = 1.1480994324250535; i53 = 1.0710387757452802 i54 = 0.6732322822800348 ; i55 = 0.39879144015217155; i56 = 0.7818060791953839; i57 = 0.9797009201839757 i58 = 1.0707852659211583 ; i59 = 0.7342769497222208 ; i60 = 0.2960528761737631; i61 = 0.6419329634235106 i62 = 0.8938441075661789 ; i63 = 1.2082436279312632 ; i64 = 0.8573401904578074; i65 = 0.2438588716389498 i66 = 0.5518544586784879 ; i67 = 0.8186245781022927 ; i68 = 1.1172014750623287; i69 = 1.4864750156733657 i70 = -0.3074083196094299; i71 = 1.5434221599024214 ; i72 = 1.7538814225756034; i73 = -0.07368461229023889 # Notice that i70, i73 are negative. </syntaxhighlight> =====Check all conditions===== The following conditions are included for testing: <syntaxhighlight lang=python> more_econditions = [ "+ e49 + e70 - e10", "+ e19 + e69 - e71", "+ e35 + e45 - e72", "+ e65 + e73 - e34", ] extra_test_conditions = [ "+ e40 + e41 + e42 + e43 + e44 + e10 - e35 - e45 - e46 - e47 - e48 - e49", "+ e45 + e46 + e47 + e48 + e49 + e11 - e36 - e50 - e51 - e52 - e53 - e54", "+ e50 + e51 + e52 + e53 + e54 + e12 - e37 - e55 - e56 - e57 - e58 - e59", "+ e55 + e56 + e57 + e58 + e59 + e13 - e38 - e60 - e61 - e62 - e63 - e64", "+ e60 + e61 + e62 + e63 + e64 + e14 - e39 - e65 - e66 - e67 - e68 - e69", "+ e44 + e10 + e11 + e12 + e13 + e14 - e69 - e15 - e16 - e17 - e18 - e19", "+ e43 + e15 + e16 + e17 + e18 + e19 - e68 - e20 - e21 - e22 - e23 - e24", "+ e42 + e20 + e21 + e22 + e23 + e24 - e67 - e25 - e26 - e27 - e28 - e29", "+ e41 + e25 + e26 + e27 + e28 + e29 - e66 - e30 - e31 - e32 - e33 - e34", "+ e40 + e30 + e31 + e32 + e33 + e34 - e65 - e35 - e36 - e37 - e38 - e39", "+ i35 + i40 + i72 - i14 - i69 - i71", """+ e40 + e41 + e42 + e43 + e44 + e10 + e11 + e12 + e13 + e14 = e35 + e36 + e37 + e38 + e39 + e65 + e66 + e67 + e68 + e69""", """+ e40 + e41 + e42 + e43 + e15 + e16 + e17 + e18 + e19 + e69 = e35 + e36 + e37 + e38 + e60 + e61 + e62 + e63 + e64 + e14""", """+ e40 + e41 + e42 + e20 + e21 + e22 + e23 + e24 + e68 + e69 = e35 + e36 + e37 + e55 + e56 + e57 + e58 + e59 + e13 + e14""", """+ e40 + e41 + e25 + e26 + e27 + e28 + e29 + e67 + e68 + e69 = e35 + e36 + e50 + e51 + e52 + e53 + e54 + e12 + e13 + e14""", """+ e40 + e30 + e31 + e32 + e33 + e34 + e66 + e67 + e68 + e69 = e35 + e45 + e46 + e47 + e48 + e49 + e11 + e12 + e13 + e14""" ] </syntaxhighlight> Two Auxiliary Functions: <syntaxhighlight lang=python> def sum_zero (values, tolerance = None) : ''' This function calculates sum of all values in input. If sum is very close to zero, sum is returned as zero. For example: sum_zero((2, -1.99999999999999999999999)) is returned as 0. ''' if tolerance == None : tolerance = Tolerance sump = sumn = 0 for v in values : if v > 0 : sump += v elif v < 0 : sumn -= v max = (sumn, sump)[sump > sumn] sum = sump - sumn if abs(sum) < tolerance: return type(sum)(0) if abs(sum) < tolerance*max : return type(sum)(0) return sum def convert_str_to_tuple (input_str) : ''' input is str like "+ i35 + i40 + i72 - i14 - i69 - i71" or "+ i35 + i40 + i72 == i14 + i69 + i71" This function returns tuple : (i35, i40, i72, - i14, - i69, - i71) ''' str0 = ' '.join(input_str.split()) if '=' in str0 : if '==' in str0 : splitter = '==' else : splitter = '=' str1,str2 = str0.split(splitter) t1 = convert_str_to_tuple (str1) t2 = convert_str_to_tuple (str2) return t1 + tuple(-v for v in t2) str1 = ';+'.join(str0.split('+')) str2 = ';-'.join(str1.split('-')) str3 = ','.join([ v for v in str2.split(';') if v.strip() ]) return eval(str3 + ',') </syntaxhighlight> Check 83 conditions: <syntaxhighlight lang=python> all_conditions = (iconditions + econditions + more_econditions + extra_test_conditions) # Following string is executable python code. exc_str_64ei = """ ( i10, i11, i12, i13, i14, i15, i16, i17, i18, i19, i20, i21, i22, i23, i24, i25, i26, i27, i28, i29, i30, i31, i32, i33, i34, i35, i36, i37, i38, i39, i40, i41, i42, i43, i44, i45, i46, i47, i48, i49, i50, i51, i52, i53, i54, i55, i56, i57, i58, i59, i60, i61, i62, i63, i64, i65, i66, i67, i68, i69, i70, i71, i72, i73, ) = values_of_i values_of_e = [ i*R for i,R in zip ( values_of_i, values_of_R ) ] ( e10, e11, e12, e13, e14, e15, e16, e17, e18, e19, e20, e21, e22, e23, e24, e25, e26, e27, e28, e29, e30, e31, e32, e33, e34, e35, e36, e37, e38, e39, e40, e41, e42, e43, e44, e45, e46, e47, e48, e49, e50, e51, e52, e53, e54, e55, e56, e57, e58, e59, e60, e61, e62, e63, e64, e65, e66, e67, e68, e69, e70, e71, e72, e73, ) = values_of_e """ exec(exc_str_64ei) tolerance = 1e-15 count = errors = 0 for condition in all_conditions : t1 = convert_str_to_tuple (condition) sum = sum_zero(t1, tolerance) count += 1 if sum : sx = 'sum, condition' ; print (sx, '=', eval(sx)) errors += 1 print ('Number of tests =', count) print ('Number of errors =', errors) </syntaxhighlight> With tolerance of <math>1e-15</math> there are 21 errors: <syntaxhighlight> sum, condition = (1.2505552149377763e-12, '+ e48 + e16 - e21 - e53') sum, condition = (1.2505552149377763e-12, '+ e49 + e11 - e16 - e54') sum, condition = (7.958078640513122e-13, '+ e52 + e22 - e27 - e57') sum, condition = (1.1368683772161603e-12, '+ e53 + e17 - e22 - e58') sum, condition = (2.2737367544323206e-12, '+ e54 + e12 - e17 - e59') ...... ...... Number of tests = 83 Number of errors = 21 </syntaxhighlight> With tolerance of <math>1e-14</math> there are no errors. <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> ====Calculate R==== =====matrix corrected===== <syntaxhighlight lang=python> matrix1 = [ list(v) for v in matrix ] # Deep copy. # e70, i70 are at position 60 in each row of matrix1. # e73, i73 are at position 63 in each row of matrix1. for row in matrix1 : for p in (60,63) : if row[p] : row[p] *= -1 </syntaxhighlight> <code>matrix1</code> is corrected version of <code>matrix</code>. =====Circuit parameters===== <syntaxhighlight> values_of_circuit_current = ('i40 + i72 + i35', 'i14 + i71 + i69') values_of_circuit_voltage = ( 'e72 + e46 + e47 + e48 + e70 + e10 + e11 + e12 + e13 + e14', 'e35 + e36 + e37 + e38 + e39 + e73 + e61 + e62 + e63 + e71', 'e40 + e41 + e42 + e43 + e44 + e10 + e11 + e12 + e13 + e14', 'e35 + e36 + e37 + e38 + e39 + e65 + e66 + e67 + e68 + e69', 'e40 + e41 + e42 + e43 + e15 + e16 + e17 + e18 + e19 + e69', 'e40 + e41 + e42 + e20 + e21 + e22 + e23 + e24 + e68 + e69', 'e40 + e41 + e25 + e26 + e27 + e28 + e29 + e67 + e68 + e69', 'e40 + e30 + e31 + e32 + e33 + e34 + e66 + e67 + e68 + e69', 'e35 + e45 + e46 + e47 + e48 + e49 + e11 + e12 + e13 + e14', 'e35 + e36 + e50 + e51 + e52 + e53 + e54 + e12 + e13 + e14', 'e35 + e36 + e37 + e55 + e56 + e57 + e58 + e59 + e13 + e14', 'e35 + e36 + e37 + e38 + e60 + e61 + e62 + e63 + e64 + e14', 'e72 + e31 - e50 + e37 + e38 + e39 + e73 + e61 - e28 + e57' + ( '- e22 + e53 - e16 + e70 + e10 + e11 + e12 + e13 + e14') ) </syntaxhighlight> =====Using floating point numbers:===== <syntaxhighlight lang=python> # python code: number_of_columns = 65 one = 1 ; Tolerance = 1e-14 # Following string is executable python code: exc_str1 = """ Values_of_R = [] for I in range(10, 74): new_line = [ 0 ] * number_of_columns place_in_line = I - 10 new_line[place_in_line] = one i = (I)/10 new_line[-1] = -i matrix1[-1] = new_line values_of_i = solveMbyN (matrix1) exec(exc_str_64ei) for Istr in values_of_circuit_current : I = eval(Istr) for Estr in values_of_circuit_voltage : E = eval(Estr) ; R = E/I ; Values_of_R += [R] print ('Number of calculations =', len(Values_of_R)) tmp = sorted(Values_of_R) minR = tmp[0] ; maxR = tmp[-1] s1 = 'minR' ; print(s1,'=',eval(s1)) s1 = 'maxR' ; print(s1,'=',eval(s1)) sum = sum_zero((minR, -maxR)) s1 = 'sum' ; print(s1,'=',eval(s1)) if not sum : print ('With Tolerance of {}, both minR and maxR are equal.'.format(Tolerance)) """ exec(exc_str1) </syntaxhighlight> <syntaxhighlight> Number of calculations = 1664 minR = 723.9285759884408 maxR = 723.9285759884439 sum = 0.0 With Tolerance of 1e-14, both minR and maxR are equal. </syntaxhighlight> This code produced 1664 values of R from minR through maxR, both included. With tolerance of <math>1e-14</math> all values of resistance R = 723.92857598844. =====Using Decimal numbers:===== With <code>enable_reduceRow</code> clear : <syntaxhighlight lang=python> enable_reduceRow = 0 Precision = dgt.prec = 60 Tolerance = dD('1e-' + str(Precision-3)) one = dD(1) try : exec(exc_str1) except : pass </syntaxhighlight> <syntaxhighlight> solveMbyN (input_, level = -52) : <class 'decimal.Overflow'> Overflow([<class 'decimal.Overflow'>]) Length of input = 12 input_[0] = [-inf, inf, -inf, inf, inf, -inf, inf, -inf, inf, -inf, -inf, inf, 0.0] input_[1] = [inf, -inf, -inf, -inf, -inf, inf, -inf, -inf, -inf, -inf, inf, -inf, 0.0] input_[2] = [-inf, inf, inf, inf, -inf, -inf, inf, inf, -inf, inf, inf, inf, 0.0] input_[3] = [inf, -inf, -inf, inf, -inf, inf, -inf, -inf, inf, -inf, -inf, inf, 0.0] input_[4] = [620.0, 0.0, 0.0, 0.0, 290.0, -1200.0, 240.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] input_[5] = [0.0, 630.0, 0.0, 0.0, 0.0, 240.0, -1110.0, 190.0, 0.0, 0.0, 0.0, 0.0, 0.0] input_[6] = [inf, -inf, inf, -inf, -inf, inf, -inf, -inf, inf, -inf, inf, -inf, 0.0] input_[7] = [-inf, inf, inf, inf, inf, -inf, inf, inf, inf, inf, -inf, inf, 0.0] </syntaxhighlight> With <code>enable_reduceRow</code> set : <syntaxhighlight lang=python> enable_reduceRow = 1 exec(exc_str1) </syntaxhighlight> <syntaxhighlight> Number of calculations = 1664 minR = 723.928575988442547699732563335265663515838075102937503680560 maxR = 723.928575988442547699732563335265663515838075102937503680663 sum = 0 With Tolerance of 1E-57, both minR and maxR are equal. </syntaxhighlight> With tolerance of <math>1e-57</math> all values of resistance R = 723.928575988442547699732563335265663515838075102937503681. <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> ==Making the Decimal object== The following function verifies that we are working with Decimal objects. <syntaxhighlight lang=python> import sys import decimal getcontext = decimal.getcontext dD = D = Decimal = decimal.Decimal DT = decimal.DecimalTuple dgt = decimal.getcontext() dgt.prec = 50 def print_error (error, x=None, thisName=None) : """ Prints error derived from sys.exc_info(). """ list1 = error.split(',') v1 = ','.join(list1[1:-1]) if thisName : print (thisName) if x != None : print (' Input =', (str(x))[:60]) print (' ', list1[0]) print (' ', v1) print (' ', list1[-1]) def makeDecimal (x, flag = 0) : ''' output = makeDecimal (x [, flag]) x is a single object convertible to Decimal object. returns Decimal object or returns None on error. ''' thisName = 'makeDecimal (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) if isinstance(x, dD) : return x if isinstance(x, int) : return dD(x) if isinstance(x, float) : return dD(str(x)) if isinstance(x, str) : try : error = '' output = dD(x) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return None return output if isinstance(x, (list,tuple,DT)) : try : error = '' v1,v2,v3 = x if isinstance(v2, (tuple,list)) : output = dD(x) else : output = dD( ( v1, list(v2), v3 ) ) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return None return output if flag : print (' Input not recognized.') return None </syntaxhighlight> ===checkComplex(x)=== This function verifies that the object is a valid complex tuple. <syntaxhighlight lang=python> def checkComplex(x, flag = 0) : """ status = checkComplex(x [, flag]) x must be : (v1,v2,'rectangular') or (v1,v2,'polar') v1,v2 must be type Decimal. """ thisName = 'checkComplex (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) try: error = '' v1,v2,str1 = x isinstance (v1,dD) or ({}['v1 must be type Decimal.']) isinstance (v2,dD) or ({}['v2 must be type Decimal.']) (isinstance (str1,str) and str1) or ({}['str1 must be valid string.']) str1 = str1.lower() if str1 == 'rectangular'[:len(str1)] : pass elif str1 == 'polar'[:len(str1)] : pass else : ({}['str1 must be "rectangular" or "polar".']) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return False return True </syntaxhighlight> ===str_to_complex (input_string)=== <syntaxhighlight lang=python> import re # The re pattern for numbers to be found in string of type complex. # In string like ' 1234567890987654323456E-6 + 987654321234567890987e+2J ' # extracts '1234567890987654323456E-6' and '+987654321234567890987e+2J'. # eval allows ' 12_3456_7890_9876_5432_3456E-6 + 987654321234567890987e+2J '. # Conversion to Decimal allows: '__987_65432123____4567890_987___'. # eval does not allow ' 0123 ' but allows ' 2e04 '. # Conversion to Decimal allows: ' 0123 ' digits = '[_0123456789]' integer = '[_0123456789]{1,}' # Matches 1 23 345 4567 56789 exponent = '[Ee][\+\-]{{0,1}}{}'.format(integer) # Matches e8 e+8 e-8 or E8 E+8 E-8 Exponent = '({}){{0,1}}'.format(exponent) # exponent 0 or 1 times. float1 = '({})\.{{0,1}}'.format(integer) # Matches 123 2345. float2 = '{}{{0,}}\.{}'.format(digits, integer) # Matches 123.345 .345 float_ = '(({})|({}))'.format(float2,float1) rvalue = '{}({})'.format(float_,Exponent) rvalue_signed = '[\+\-]{{0,1}}{}'.format(rvalue) ivalue_signed = '{}[Jj]'.format(rvalue_signed) def str_to_complex (input_string) : """ a,b = str_to_complex (input_string) input_string could be ' 1234567890987654323456E-6 + 987654321234567890987e+2J ' input_string could be ' ' ' ( 12345678909876543234561234567890987.654323456E-6 + 987654321234567890987987654321.23764567890987e+2J ) ' ' ' or ' ' ' - ( ( 12345678_90543123456789054_312345678905431234567890543e-014 + 543123456789054_3123456789054312345_67890543654327453E-1_3J ) ) ' ' ' or ' ' ' - ( ( 12345678_90543123456789054_312345678905431234567890543e-014 + # Note the '_' 543123456789054_3123456789054312345_67890543654327453E-1_3J ) ) ' ' ' or '4', '-4', '(4)', '(-4)', '-(4)', '-(-4)' or '( +3j)', '+(-3J)', '-(3j)', '-(-3J)' or '( 4+3j)', '+(-3 + 4J)','-( 4+3j)', '-(-3 + 4J)', This function retains precision of a,b """ try : status = 0 isinstance(input_string,str) or ({}['input_string not type str.']) str1 = input_string.strip() cx1 = eval(str1) isinstance(cx1,(int,float,complex)) or ({}['cx1 not desired type.']) except : status = 1 if status : return # This code removes white lines and comments, if any, at end of each line. new_line = ''' '''[-1:] lines = [ line for Line in str1.split(new_line) for line in [ Line.rstrip() ] if line ] lines = [ v for line in lines for parts in [ line.split('#') ] for v in [ parts[0]] ] str1 = ''.join(lines) str1 = ''.join(str1.split()) if isinstance (cx1, (int,float)) : resultr = re.search(rvalue_signed, str1) resultr or ({}['rvalue not found.']) dD1 = dD(resultr[0]) v1 = eval(str(dD1)) if v1 == cx1 : return dD1,dD(0) if v1 == -cx1 : return -dD1,dD(0) ({}['dD1 not recognized.']) # cx1 must be complex. It must contain imaginary value. resulti = re.search(ivalue_signed, str1) resulti or ({}['ivalue not found.']) str2j = resulti[0] ; str2 = str2j[:-1] dD2 = dD(str2) str1 = ''.join(str1.split(str2j)) # cx1 may contain real value. resultr = re.search(rvalue_signed, str1) if resultr : dD1 = dD(resultr[0]) else : dD1 = dD(0) cx2 = complex(dD1,dD2) if cx2.real == cx1.real : pass elif cx2.real == -cx1.real : dD1 = dD1.copy_negate() else : ({}['dD1 Not Recognized.']) if cx2.imag == cx1.imag : pass elif cx2.imag == -cx1.imag : dD2 = dD2.copy_negate() else : ({}['dD2 Not Recognized.']) cx3 = complex(dD1, dD2) if cx3 == cx1 : return dD1,dD2 ({}['No match for cx3.']) </syntaxhighlight> ===makeComplex(x)=== <syntaxhighlight lang=python> def makeComplex (x, flag = 0) : ''' result = makeComplex (x[, flag]) Input can be tuple with 1,2 or 3 members. If 1 or 2 members, 'rect' is understood. The one member or single object may be int, float, complex, CompleX or string convertible to int, float or complex. x = makeComplex(4) x = makeComplex((4,)) x = makeComplex(('4',0)) x = makeComplex((4,'0', 'rect')) x = makeComplex(4+0j) x = makeComplex('4+0j') x = makeComplex(('4+0j',)) In all seven cases above x = ( Decimal('4'), Decimal('0'), 'rect' ) output is always (modulus, phase, "polar") or (real_part, imag_part, "rect") modulus, phase, real_part, imag_part are Decimal objects. On error returns None. ''' thisName = 'makeComplex (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) if isinstance(x, CompleX) : # New class CompleX (note the punctuation.) x.check() return (x.r, x.i, 'rect') if isinstance (x,complex) : return makeComplex (( x.real, x.imag )) try : status = 1 a,b = str_to_complex (x) except : status = 0 if status : return a,b,'rect' try : status = 1 result = makeDecimal(x) isinstance(result, Decimal) or ({}['Expecting result to be type Decimal.']) output = result,dD(0),'rect' except : status = 0 if status : return output try : status = 1 v1, = x # Allow for (( 3+4j ),) except : status = 0 if status : return makeComplex (v1) try : status = 1 ; error = '' if len(x) == 2 : v1,v2 = [ makeDecimal (v) for v in x ] str1 = 'rect' elif len(x) == 3 : v1,v2,str1 = x v1,v2 = [ makeDecimal (v) for v in (v1,v2) ] else : ({}['len(x) not in (2,3)']) output = v1,v2,str1 checkComplex(output) or ({}['output not valid complex.']) if str1[0] in 'rR' : output = v1,v2,'rect' else : output = v1,v2,'polar' except : status = 0 ; error = str(sys.exc_info()) if status : return output if flag : print_error (error) return </syntaxhighlight> =Conic sections generally= Within the two dimensional space of Cartesian Coordinate Geometry a conic section may be located anywhere and have any orientation. This section examines the parabola, ellipse and hyperbola, showing how to calculate the equation of the section, and also how to calculate the foci and directrices given the equation. ==Latera recta et cetera== "Latus rectum" is a Latin expression meaning "straight side." According to Google, the Latin plural of "latus rectum" is "latera recta," but English allows "latus rectums" or possibly "lati rectums." The title of this section is poetry to the eyes and music to the ears of a Latin student and this author hopes that the gentle reader will permit such poetic licence in a mathematical topic. The translation of the title is "Latus rectums and other things." This section describes the calculation of interesting items associated with the ellipse: latus rectums, major axis, minor axis, focal chords, directrices and various points on these lines. When given the equation of an ellipse, the first thing is to calculate eccentricity, foci and directrices as shown above. Then verify that the curve is in fact an ellipse. From these values everything about the ellipse may be calculated. For example: {{RoundBoxTop|theme=2}} [[File:0608ellipse01.png|thumb|400px|'''Graph of ellipse <math>1771x^2 + 1204y^2 + 1944xy -44860x - 18520y + 214400 = 0.</math>''' </br> </br> Axis : (-0.8)x + (-0.6)y + (9.4) = 0</br> Eccentricity = 0.9</br> </br> Directrix 2 : (0.6)x + (-0.8)y + (2) = 0</br> Latus rectum RS : (0.6)x + (-0.8)y + (-0.8) = 0</br> Minor axis : (0.6)x + (-0.8)y + (-12.73684210526315789474) = 0</br> Latus rectum PU : (0.6)x + (-0.8)y + (-24.67368421052631578947) = 0</br> Directrix 1 : (0.6)x + (-0.8)y + (-27.47368421052631578947) = 0</br> </br> <math>\text{ID2}</math> = (6.32, 7.24)</br> <math>\text{I2}</math> = (7.204210526315789473684, 6.061052631578947368421)</br> F2 = (8, 5)</br> M = (15.16210526315789473684, -4.54947368421052631579)</br> F1 = (22.32421052631578947368, -14.09894736842105263158)</br> <math>\text{I1}</math> = (23.12, -15.16)</br> <math>\text{ID1}</math> = (24.00421052631578947368, -16.33894736842105263158)</br> </br> P = (20.30821052631578947368, -15.61094736842105263158)</br> Q = (10.53708406832736953616, -8.018239580333420216299)</br> R = (5.984, 3.488)</br> S = (10.016, 6.512)</br> T = (19.78712645798841993752, -1.080707788087632415281)</br> U = (24.34021052631578947368, -12.58694736842105263158)</br> </br> Length of major axis: <math>\text{I1I2}</math> = 26.52631578947368421052</br> Length of minor axis: QT = 11.56255298707631300170</br> Length of latus rectum: RS = PU = 5.04 ]] Consider conic section: <math>1771x^2 + 1204y^2 + 1944xy -44860x - 18520y + 214400 = 0.</math> This curve is ellipse with random orientation. <syntaxhighlight lang=python> # python code ABCDEF = A,B,C,D,E,F = 1771, 1204, 1944, -44860, -18520, 214400 # ellipse result = calculate_abc_epq(ABCDEF) (len(result) == 2) or 1/0 # ellipse or hyperbola (abc1,epq1), (abc2,epq2) = result a1,b1,c1 = abc1 ; e1,p1,q1 = epq1 a2,b2,c2 = abc2 ; e2,p2,q2 = epq2 (e1 == e2) or 2/0 (1 > e1 > 0) or 3/0 print ( '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0'.format(A,B,C,D,E,F) ) A,B,C,D,E,F = ABCDEF_from_abc_epq(abc1,epq1) print ('Equation of ellipse in standard form:') print ( '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0'.format(A,B,C,D,E,F) ) </syntaxhighlight> <syntaxhighlight> (1771)x^2 + (1204)y^2 + (1944)xy + (-44860)x + (-18520)y + (214400) = 0 Equation of ellipse in standard form: (-0.7084)x^2 + (-0.4816)y^2 + (-0.7776)xy + (17.944)x + (7.408)y + (-85.76) = 0 </syntaxhighlight> <syntaxhighlight lang=python> # python code def sum_zero(input) : ''' sum = sum_zero(input) If sum is close to 0 and Tolerance permits, sum is returned as 0. For example: if input contains (2, -1.999999999999999999999) this function returns sum of these 2 values as 0. ''' global Tolerance sump = sumn = 0 for v in input : if v > 0 : sump += v elif v < 0 : sumn -= v sum = sump - sumn if abs(sum) < Tolerance : return (type(Tolerance))(0) min, max = sorted((sumn,sump)) if abs(sum) <= Tolerance*min : return (type(Tolerance))(0) return sum </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ===Major axis=== <syntaxhighlight lang=python> # axis is perpendicular to directrix. ax,bx = b1,-a1 # axis contains foci. ax + by + c = 0 cx = reduce_Decimal_number(-(ax*p1 + bx*q1)) axis = ax,bx,cx print ( ' Axis : ({})x + ({})y + ({}) = 0'.format(ax,bx,cx) ) print ( ' Eccentricity = {}'.format(e1) ) print () print ( ' Directrix 1 : ({})x + ({})y + ({}) = 0'.format(a1,b1,c1) ) print ( ' Directrix 2 : ({})x + ({})y + ({}) = 0'.format(a2,b2,c2) ) F1 = p1,q1 # Focus 1. print ( ' F1 : ({}, {})'.format(p1,q1) ) F2 = p2,q2 # Focus 2. print ( ' F2 : ({}, {})'.format(p2,q2) ) # Direction cosines along axis from F1 towards F2: dx,dy = a1,b1 # p2 = p1 + dx*distance_F1_F2 # q2 = q1 + dy*distance_F1_F2 if dx : distance_F1_F2 = (p2 - p1)/dx else : distance_F1_F2 = (q2 - q1) if distance_F1_F2 < 0 : distance_F1_F2 *= -1 dx *= -1 ; dy *= -1 # Intercept on directrix1 distance_from_F1_to_ID1 = abs(a1*p1 + b1*q1 + c1) ID1 = xID1,yID1 = p1 - dx*distance_from_F1_to_ID1, q1 - dy*distance_from_F1_to_ID1 print ( ' Intercept ID1 : ({}, {})'.format(xID1,yID1) ) # # distance_F1_F2 # -------------------- = e # length_of_major_axis # length_of_major_axis = distance_F1_F2 / e1 # Intercept1 on curve distance_from_F1_to_curve = (length_of_major_axis - distance_F1_F2 )/2 xI1,yI1 = p1 - dx*distance_from_F1_to_curve, q1 - dy*distance_from_F1_to_curve I1 = xI1,yI1 = [ reduce_Decimal_number(v) for v in (xI1,yI1) ] print ( ' Intercept I1 : ({}, {})'.format(xI1,yI1) ) </syntaxhighlight> <syntaxhighlight> Axis : (-0.8)x + (-0.6)y + (9.4) = 0 Eccentricity = 0.9 Directrix 1 : (0.6)x + (-0.8)y + (-27.47368421052631578947) = 0 Directrix 2 : (0.6)x + (-0.8)y + (2) = 0 F1 : (22.32421052631578947368, -14.09894736842105263158) F2 : (8, 5) Intercept ID1 : (24.00421052631578947368, -16.33894736842105263158) Intercept I1 : (23.12, -15.16) </syntaxhighlight> {{RoundBoxTop|theme=2}} Techniques similar to above can be used to calculate points <math>I2, ID2.</math> {{RoundBoxBottom}} ===Latus rectums=== <syntaxhighlight lang=python> # direction cosines along latus rectum. dlx,dly = -dy,dx # # distance from U to F1 half_latus_rectum # ------------------------------ = ----------------------- = e1 # distance from U to directrix 1 distance_from_F1_to_ID1 # half_latus_rectum = reduce_Decimal_number(e1*distance_from_F1_to_ID1) # latus rectum 1 # Focal chord has equation (afc)x + (bfc)y + (cfc) = 0. afc,bfc = a1,b1 cfc = reduce_Decimal_number(-(afc*p1 + bfc*q1)) print ( ' Focal chord PU : ({})x + ({})y + ({}) = 0'.format(afc,bfc,cfc) ) P = xP,yP = p1 + dlx*half_latus_rectum, q1 + dly*half_latus_rectum print ( ' Point P : ({}, {})'.format(xP,yP) ) U = xU,yU = p1 - dlx*half_latus_rectum, q1 - dly*half_latus_rectum print ( ' Point U : ({}, {})'.format(xU,yU) ) distance = reduce_Decimal_number(( (xP - xU)**2 + (yP - yU)**2 ).sqrt()) print (' Length PU =', distance) print (' half_latus_rectum =', half_latus_rectum) </syntaxhighlight> <syntaxhighlight> Focal chord PU : (0.6)x + (-0.8)y + (-24.67368421052631578947) = 0 Point P : (20.30821052631578947368, -15.61094736842105263158) Point U : (24.34021052631578947368, -12.58694736842105263158) Length PU = 5.04 half_latus_rectum = 2.52 </syntaxhighlight> {{RoundBoxTop|theme=2}} Techniques similar to above can be used to calculate points <math>R, S.</math> {{RoundBoxBottom}} ===Minor axis=== <syntaxhighlight lang=python> print () # Mid point between F1, F2: M = xM,yM = (p1 + p2)/2, (q1 + q2)/2 print ( ' Mid point M : ({}, {})'.format(xM,yM) ) half_major = length_of_major_axis / 2 half_distance = distance_F1_F2 / 2 # half_distance**2 + half_minor**2 = half_major**2 half_minor = ( half_major**2 - half_distance**2 ).sqrt() length_of_minor_axis = half_minor * 2 Q = xQ,yQ = xM + dlx*half_minor, yM + dly*half_minor T = xT,yT = xM - dlx*half_minor, yM - dly*half_minor print ( ' Point Q : ({}, {})'.format(xQ,yQ) ) print ( ' Point T : ({}, {})'.format(xT,yT) ) print (' length_of_major_axis =', length_of_major_axis) print (' length_of_minor_axis =', length_of_minor_axis) # # A basic check. # length_of_minor_axis**2 = (length_of_major_axis**2)(1-e**2) # # length_of_minor_axis**2 # ----------------------- = 1-e**2 # length_of_major_axis**2 # # length_of_minor_axis**2 # ----------------------- + (e**2 - 1) = 0 # length_of_major_axis**2 # values = (length_of_minor_axis/length_of_major_axis)**2, e1**2 - 1 sum_zero(values) and 3/0 aM,bM = a1,b1 # Minor axis is parallel to directrix. cM = reduce_Decimal_number(-(aM*xM + bM*yM)) print ( ' Minor axis : ({})x + ({})y + ({}) = 0'.format(aM,bM,cM) ) </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> Mid point M : (15.16210526315789473684, -4.54947368421052631579) Point Q : (10.53708406832736953616, -8.018239580333420216299) Point T : (19.78712645798841993752, -1.080707788087632415281) length_of_major_axis = 26.52631578947368421052 length_of_minor_axis = 11.56255298707631300170 Minor axis : (0.6)x + (-0.8)y + (-12.73684210526315789474) = 0 </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> ===Checking=== {{RoundBoxTop|theme=2}} All interesting points have been calculated without using equations of any of the relevant lines. However, equations of relevant lines are very useful for testing, for example: * Check that points <math>ID2, I2, F2, M, F1, I1, ID1</math> are on axis. * Check that points <math>R, F2, S</math> are on latus rectum through <math>F2.</math> * Check that points <math>Q, M, T</math> are on minor axis through <math>M.</math> * Check that points <math>P, F1, U</math> are on latus rectum through <math>F1.</math> Test below checks that 8 points <math>I1, I2, P, Q, R, S, T, U</math> are on ellipse and satisfy eccentricity <math>e = 0.9.</math> <math></math> <math></math> {{RoundBoxBottom}} <syntaxhighlight lang=python> t1 = ( ('I1'), ('I2'), ('P'), ('Q'), ('R'), ('S'), ('T'), ('U'), ) for name in t1 : value = eval(name) x,y = [ reduce_Decimal_number(v) for v in value ] print ('{} : ({}, {})'.format((name+' ')[:2], x,y)) values = A*x**2, B*y**2, C*x*y, D*x, E*y, F sum_zero(values) and 3/0 # Relative to Directrix 1 and Focus 1: distance_to_F1 = ( (x-p1)**2 + (y-q1)**2 ).sqrt() distance_to_directrix1 = a1*x + b1*y + c1 e1 = distance_to_F1 / distance_to_directrix1 print (' e1 =',e1) # Raw value is printed. # Relative to Directrix 2 and Focus 2: distance_to_F2 = ( (x-p2)**2 + (y-q2)**2 ).sqrt() distance_to_directrix2 = a2*x + b2*y + c2 e2 = distance_to_F2 / distance_to_directrix2 e2 = reduce_Decimal_number(e2) print (' e2 =',e2) # Clean value is printed. </syntaxhighlight> {{RoundBoxTop|theme=2}} Note the differences between "raw" values of <math>e_1</math> and "clean" values of <math>e_2.</math> {{RoundBoxBottom}} <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> I1 : (23.12, -15.16) e1 = -0.9000000000000000000034 e2 = 0.9 I2 : (7.204210526315789473684, 6.061052631578947368421) e1 = -0.9 e2 = 0.9 P : (20.30821052631578947368, -15.61094736842105263158) e1 = -0.9 e2 = 0.9 Q : (10.53708406832736953616, -8.018239580333420216299) e1 = -0.9000000000000000000002 e2 = 0.9 R : (5.984, 3.488) e1 = -0.9000000000000000000003 e2 = 0.9 S : (10.016, 6.512) e1 = -0.9000000000000000000003 e2 = 0.9 T : (19.78712645798841993752, -1.080707788087632415281) e1 = -0.8999999999999999999996 e2 = 0.9 U : (24.34021052631578947368, -12.58694736842105263158) e1 = -0.9 e2 = 0.9 </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> ==Traditional definition of ellipse== {{RoundBoxTop|theme=2}} [[File:0617ellipse01.png|thumb|400px|'''Traditional definition of ellipse.''' </br> Sum of distance <math>F_1G</math> and distance <math>F_2G</math> is constant. ]] Ellipse may be defined as the locus of a point that moves so that the sum of its distances from two fixed points is constant. In the diagram the two fixed points are the foci, Focus 1 or <math>F_1</math> and Focus 2 or <math>F_2.</math> Distance between <math>F_1</math> and <math>F_2</math>, distance <math>F_1F_2</math>, must be non-zero. Point <math>G</math> on perimeter of ellipse moves so that sum of distance <math>F_1G</math> and distance <math>F_2G</math> is constant. Points <math>T_1</math> and <math>T_2</math> are on axis of ellipse and the same rule applies to these points. distance <math>F_1T_1</math> + distance <math>T_1F_2</math> is constant. distance <math>F_1T_1</math> + distance <math>T_1F_2</math> <math>=</math> distance <math>F_1G</math> + distance <math>F_2G</math> <math>=</math> distance <math>F_2T_2</math> + distance <math>T_1F_2</math> <math>= \text{length of major axis.}</math> Therefore the constant is <math>\text{length of major axis}</math> which must be greater than distance <math>F_1F_2.</math> From information given, calculate eccentricity <math>e</math> and equation of one directrix. Choose directrix 1 <math>dx1</math> associated with focus F1. <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> {{RoundBoxBottom}} ==Ellipse at origin== {{RoundBoxTop|theme=2}} [[File:0901ellipse00.png|thumb|400px|'''Traditional definition of ellipse.''' </br> Sum of distance <math>F_1P</math> and distance <math>F_2P</math> is constant. ]] Traditional definition of ellipse states that ellipse is locus of a point that moves so that sum of its distances from two fixed points is constant. By definition distance <math>F_2P</math> + distance <math>F_1P</math> is constant. <math>\sqrt{(x-(-p))^2 + y^2} + \sqrt{(x-p)^2 + y^2} = k\ \dots\ (1)</math> Expand <math>(1)</math> and result is <math>Ax^2 + By^2 + F = 0\ \dots\ (2)</math> where: <math>A = 4k^2 - 16p^2</math> <math>B = 4k^2</math> <math>F = 4k^2p^2 - k^4</math> When <math>y = 0,</math> point <math>B,\ Ax^2 = -F</math> <math>x^2 = \frac{-F}{A}</math> <math>= \frac{k^4 - 4k^2p^2}{4k^2 - 16p^2}</math> <math>=\frac{k^2(k^2-4p^2)}{4(k^2 - 4p^2)} = \frac{k^2}{4}.</math> Therefore: <math>x = \frac{k}{2} = a</math> <math>k = \text{length of major axis.}</math> By definition, distance <math>F_2A</math> + distance <math>F_1A = k.</math> Therefore distance <math>F_1A = a.</math> Intercept form of ellipse at origin: <math>(4k^2 - 16p^2)x^2 + (4k^2)y^2 = k^4 - 4k^2p^2</math> <math>\frac{4(k^2-4p^2)}{k^2(k^2-4p^2)}x^2 + \frac{4k^2}{k^2(k^2 - 4p^2)}y^2 = 1</math> <math>\frac{4}{(2a)^2}x^2 + \frac{4}{(2a)^2 - 4p^2}y^2 = 1</math> <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> <math></math> <math></math> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ==Second definition of ellipse== {{RoundBoxTop|theme=2}} [[File:0901ellipse00.png|thumb|400px|'''Graph of ellipse <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> where <math>a,b = 20,12</math>.''' </br> At point <math>B,\ \frac{u}{v} = e.</math> </br> At point <math>A,\ \frac{a}{t} = e.</math> ]] Ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant. Let <math>\frac{p}{a} = e</math> where: * <math>p</math> is non-zero, * <math>a > p,</math> * <math>a = p + u.</math> Therefore, <math>1 > e > 0.</math> Let directrix have equation <math>x = t</math> where <math>\frac{a}{t} = e.</math> At point <math>B:</math> <math>\frac{p}{p+u} = \frac{p+u}{p+u+v} = e</math> <math>(p+u)^2 = p(p+u+v)</math> <math>pp + pu + pu + uu = pp + pu + pv</math> <math>pu + uu = pv</math> <math>u(p + u) = pv</math> <math>\frac{u}{v} = \frac{p}{p+u} = e</math> <math>\frac{\text{distance to focus}}{\text{distance to directrix}} = e\ \dots\ (3)</math> Statement <math>(3)</math> is true at point <math>A</math> also. Section under "Proof" below proves that statement (3) is true for any point <math>P</math> on ellipse. {{RoundBoxBottom}} ===Proof=== {{RoundBoxTop|theme=2}} [[File:0902ellipse00.png|thumb|400px|'''Proving that <math>\frac{\text{distance from point to focus}}{\text{distance from point to directrix}} = e</math>.''' </br> Graph is part of curve <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1.</math> </br> distance to Directrix1 <math>= t - x = \frac{a}{e} - x = \frac{a - ex}{e}.</math> </br> base = <math>x - p = x - ae</math> </br> <math>\text{(distance to Focus1)}^2 = \text{base}^2 + y^2</math> ]] As expressed above in statement <math>3,</math> second definition of ellipse states that ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant. This section proves that this definition is true for any point <math>P</math> on the ellipse. At point <math>P:</math> <math>(a^2 - p^2)x^2 + a^2y^2 -a^2(a^2 - p^2) = 0</math> <math>y^2 = \frac{-(a^2 - p^2)x^2 + a^2(a^2 - p^2)}{a^2}</math> <math>= \frac{a^2e^2x^2 - a^2x^2 + a^2a^2 - a^2a^2e^2}{a^2}</math> <math>= e^2x^2 - x^2 + a^2 - a^2e^2</math> base <math>= x-p = x-ae</math> <math>(\text{distance}\ F_1P)^2 = y^2 + \text{base}^2 = y^2 + (x-ae)^2</math> <math>= a^2 - 2aex + e^2x^2</math> <math>= (a-ex)^2</math> <math>\text{distance to Focus1} = \text{distance}\ F_1P = a - ex</math> <math>\text{distance to Directrix1} = t - x = \frac{a}{e} - x = \frac{a-ex}{e}</math> <math>\frac{\text{distance to Focus1}}{\text{distance to Directrix1}}</math> <math>= (a - ex)\frac{e}{(a-ex)}</math> <math>= e</math> Similar calculations can be used to prove the case for Focus2 <math>(-p, 0)</math> and Directrix2 <math>(x = -t)</math> in which case: <math>\frac{\text{distance to Focus2}}{\text{distance to Directrix2}}</math> <math>= (a + ex)\frac{e}{(a + ex)}</math> <math>= e</math> Therefore: <math>\frac{\text{distance to focus}}{\text{distance to directrix}} = e</math> where <math>1 > e > 0.</math> Ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant, called eccentricity <math>e.</math> <math></math> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ==Heading== ===Properties of ellipse=== {{RoundBoxTop|theme=2}} [[File:0822ellipse01.png|thumb|400px|'''Graph of ellipse used to illustrate and calculate certain properties of ellipses.''' </br> </br> Traditional definition of ellipse: </br> <math>\text{distance } AF_1 + \text{distance } AF_2 = \text{constant } k.</math> </br> </br> Second definition of ellipse: </br> <math>\frac{\text{distance } AF_1} {\text{distance } AG } = \text{eccentricity } e.</math> </br> </br> Triangle <math>A F_1 G</math> is right triangle. </br> <math>e = \cos \angle O F_1 A = \cos \angle F_1 A G</math> ]] Ellipse in diagram has: * Two foci: <math>F_1\ (p,0),\ F_2\ (-p,0).</math> * Length of major axis <math>= \text{distance } I_2 I_1 = 2a</math> * Length of minor axis <math>= \text{distance } A B = 2b</math> * Equation: <math>\frac {x^2} {a^2} + \frac {y^2} {b^2} = 1</math> * Length of latus rectum <math>= \text{distance } P Q</math> * Distance between directrices <math>= \text{distance } D_2 D_1 = 2t</math> Properties of ellipse: * <math>\frac{\text{length of major axis}} {\text{distance between directrices}} = e</math> * <math>\frac{\text{distance between foci}} {\text{length of major axis}} = e</math> * <math>\frac{\text{distance between foci}} {\text{distance between directrices}}= e^2</math> * <math>(\frac{\text{length of minor axis}} {\text{length of major axis}})^2 + e^2 = 1</math> * <math>\frac{\text{length of latus rectum}} {\text{length of major axis}} + e^2 = 1</math> * line <math>PD_1</math> is tangent to curve at latus rectum, point <math>P.</math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ====Major axis==== From traditional definition of ellipse: Distance <math>AF_2\ +</math> distance <math>AF_1</math> = distance <math>I_1F_1\ +</math> distance <math>I_1F_2</math> = distance <math>I_2F_2\ +</math> distance <math>I_2F_1</math> = <math>k.</math> Therefore: Length of major axis = distance <math>I_2I_1 = 2a = k.</math> Distance <math>AF_1 = \frac{k}{2} = a.</math> From second definition of ellipse: <math>\frac{\text{distance }AF_1}{\text{distance }AG} = \frac{a}{t} = \text{eccentricity }e</math> <math>= \frac{\text{distance }OI_1}{\text{distance }OD_1}.</math> <math>\frac{\text{length of major axis}}{\text{distance between directrices}} = e.</math> ====Foci==== From second definition of ellipse: <math>\frac{\text{distance }I_1F_1}{\text{distance }I_1D_1} = \frac{a-p}{t-a} = e.</math> <math>a - p = te - ae</math> <math>a - p = a - ae</math> Therefore: <math>p = ae</math> or <math>\frac{p}{a} = e.</math> <math>\frac{\text{distance between foci}}{\text{length of major axis}} = e.</math> <math>\frac{\text{distance between foci}}{\text{distance between directrices}} = e^2.</math> ====Minor axis==== Triangle <math>AOF_1</math> is right triangle. <math>\cos ^2 \angle OAF_1 + \sin ^2 \angle OAF_1</math> <math>= (\frac{b}{a})^2 + (\frac{p}{a})^2 </math> <math>= (\frac{b}{a})^2 + (\frac{ae}{a})^2 </math> <math>= (\frac{b}{a})^2 + e^2 = 1</math> <math>( \frac{\text{length of minor axis}} {\text{length of major axis}} )^2 + e^2 = 1</math> Triangles <math>AOF_1,\ AF_1G</math> are similar. Triangle <math>AF_1G</math> is right triangle. <math>e = \cos \angle OF_1A = \cos \angle F_1AG.</math> ====Latus rectum==== From second definition of ellipse: <math>\frac{\text{distance }PF_1} {\text{distance }F_1D_1} = \frac{\text{distance }PF_1}{t-p} = e</math> <math>\text{distance }PF_1 = te - pe = a - (ae)e = a(1-e^2).</math> <math>\frac{\text{distance }PF_1} {a} = 1 - e^2.</math> <math> \frac{\text{length of latus rectum}} {\text{length of major axis}} + e^2 = 1</math> ====Slope of curve==== Curve has equation: <math>b^2x^2 + a^2y^2 = a^2b^2</math> Derivative of both sides: <math>b^22x + a^22yy' = 0</math> <math>y' = \frac{-xb^2}{ya^2}</math><math></math> <math>= \frac{-x(1-e^2)}{y}</math><math></math> At point <math>P:\ m_1 = y' = \frac{-p(1-e^2)}{-a(1-e^2)}</math> <math>= \frac{ae}{a} = e.</math><math></math> Slope of line <math>PD_1:\ m_2 = \frac{\text{distance }PF_1}{\text{distance }F_1D_1} = e.</math><math></math><math></math> <math>m_1 = m_2.</math> Therefore line <math>PD_1</math> is tangent to curve at latus rectum, point <math>P.</math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> ===Intercept form of equation=== <math>\frac{x^2}{20^2} + \frac{y^2}{12^2} = 1</math> <math></math> <math></math> {{RoundBoxTop|theme=2}} [[File:0625ellipse01.png|thumb|400px|'''Ellipse at origin with major axis on X axis.''' </br> </br> </br> </br> Equation of ellipse has format <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> where: </br> </br> <math>\text{Length of major axis} = 2a = \text{distance}\ I_2I_1 = 40</math> </br> <math>\text{Length of minor axis} = 2b = \text{distance}\ BA = 24</math> </br> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> </br> <math>\frac{\text{Length of minor axis}}{\text{Length of major axis}} = \sqrt{1 - e^2}</math> </br> </br> <math>e = \sqrt{1 - \frac{b^2}{a^2}} = 0.8.</math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> ]] In diagram: Intercept <math>I_1</math> has coordinates <math>(a,0).</math> Intercept <math>I_2</math> has coordinates <math>(-a,0).</math> Intercept <math>A</math> has coordinates <math>(0,b).</math> Intercept <math>B</math> has coordinates <math>(0,-b).</math> Focus <math>F_1</math> has coordinates <math>(f,0)</math> where <math>f = ea.</math> Focus <math>F_2</math> has coordinates <math>(-f,0).</math> Curve has equation <math>\frac{x^2}{20^2} + \frac{y^2}{12^2} = 1,</math> called intercept form of equation of ellipse because intercepts are apparent as the fractional value of each coefficient. Standard form of this equation is: <math>(-0.36)x^2 + (-1)y^2 + (0)xy + (0)x + (0)y + (144) = 0.</math> While the standard form is valuable as input to a computer program, the intercept form is still attractive to the human eye because center of ellipse and intercepts are neatly contained within the equation. Slope of curve: <math>b^2x^2 + a^2y^2 = a^2b^2</math> Derivative of both sides: <math>b^22x + a^22yy' = 0</math> <math>y' = \frac{-xb^2}{ya^2}</math> <math>= \frac{-x(1-e^2)}{y}</math> At point <math>P</math> on latus rectum <math>PQ:</math> <math>m_1 = y' = \frac{-(ea)(1-e^2)}{-(a(1-e^2))} = e</math> Slope of line <math>PD = m_2 = \frac{PF_1}{F_1D} = e</math> <math>m_1 = m_2.</math> Line <math>PD</math> is tangent to curve at latus rectum, point <math>P.</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ===Example=== {{RoundBoxTop|theme=2}} [[File:0618ellipse01.png|thumb|400px|'''Traditional definition of ellipse uses abc, epq.''' </br> M is mid-point between F1 and F2. </br> Point R is on minor axis. </br> </br> <math>\frac{\text{distance from R to F1}}{\text{distance from R to directrix 1}}</math> <math>= e</math> </br> </br> <math>= \frac{\text{half major axis}}{\text{distance from M to directrix 1}}</math> </br> </br> <math>\text{distance from M to directrix 1} = \frac{\text{half major axis}}{e}</math> </br> </br> <math>\text{F1:}\ (1, -7)</math> </br> <math>\text{F2:}\ (-1.24, 0.68)</math> </br> length_of_major_axis = 10 </br> <math>\text{M:}\ (-0.12, -3.16)</math> </br> length_of_minor_axis = 6 </br> <math>\text{R:}\ (2.76, -2.32)</math> </br> <math>e = 0.8</math> </br> <math>\text{D1:}\ (1.63, -9.16)</math> </br> <math>\text{Directrix 1:}\ (-0.28)x + (0.96)y + (9.25) = 0</math> </br> <math>\text{abc}\ =\ (-0.28,\ 0.96,\ 9.25)</math> </br> <math>\text{epq}\ =\ (0.8,\ 1,\ -7)</math> ]] Given: <syntaxhighlight lang=python> # python code F1 = 1, -7 # Focus 1 F2 = -1.24, 0.68 # Focus 2 length_of_major_axis = 10 </syntaxhighlight> Calculate equation of ellipse. <syntaxhighlight lang=python> F1 = p1,q1 = [ dD(str(v)) for v in F1 ] # Focus 1 F2 = p2,q2 = [ dD(str(v)) for v in F2 ] # Focus 2 length_of_major_axis = dD(length_of_major_axis) half_major_axis = length_of_major_axis / 2 # Direction cosines from F1 to F2 dx = p2-p1 ; dy = q2-q1 divider = (dx**2 + dy**2).sqrt() dx,dy = [ (v/divider) for v in (dx,dy) ] # F2 # p2 = p1 + dx*distance_F1_F2 # q2 = q1 + dy*distance_F1_F2 distance_F1_F2 = (q2-q1)/dy half_distance_F1_F2 = distance_F1_F2 / 2 # The mid-point M = xM,ym = p1 + dx*half_distance_F1_F2, q1 + dy*half_distance_F1_F2 # Eccentricity: e = distance_F1_F2 / length_of_major_axis # distance from point R to F1 half_major_axis # ------------------------------------ = e = ----------------------------------------- # distance from point R to Directrix 1 distance from point M to Directrix 1 distance_from_point_M_to_dx1 = half_major_axis / e # Intersection of axis and directrix 1 D1 = xM-dx*distance_from_point_M_to_dx1, yM-dy*distance_from_point_M_to_dx1 D1 = xD1, yD1 = [ reduce_Decimal_number(v) for v in D1 ] # Equation of Directrix 1 # dx1 = adx1,bdx1,cdx1 adx1,bdx1 = dx, dy # Perpendicular to axis. # adx1*x + bdx1*y + cdx1 = 0 # Directrix 1 contains point D1 cdx1 = reduce_Decimal_number( -( adx1*xD1 + bdx1*yD1 ) ) abc = adx1,bdx1,cdx1 epq = e,p1,q1 ABCDEF = ABCDEF_from_abc_epq (abc,epq, 1) </syntaxhighlight> Equation of ellipse in standard form: <math>(-0.949824)x^2 + (-0.410176)y^2 + (-0.344064)xy + (-1.3152)x + (-2.6336)y + (4.76) = 0</math> For more insight into method of calculation and proof: <syntaxhighlight lang=python> if 1 : print ('F1: ({}, {})'.format(p1,q1)) print ('F1: (x - ({}))^2 + (y - ({}))^2 = 1'.format(p1,q1)) print ('F2: ({}, {})'.format(p2,q2)) print ('F2: (x - ({}))^2 + (y - ({}))^2 = 1'.format(p2,q2)) print ('length_of_major_axis =', length_of_major_axis) print ('M: ({}, {})'.format(xM,yM)) print ('M: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xM,yM)) # half_minor_axis**2 + half_distance_F1_F2**2 = half_major_axis**2 half_minor_axis = (half_major_axis**2 - half_distance_F1_F2**2).sqrt() length_of_minor_axis = half_minor_axis * 2 s1 = 'length_of_minor_axis' ; print (s1, '=', eval(s1)) # Direction cosines on major axis: print ('dx,dy =', dx,dy) # Direction cosines on minor axis: dnx,dny = dy,-dx print ('dnx,dny =', dnx,dny) # One point on minor axis: R = xR,yR = xM + dnx*half_minor_axis, yM + dny*half_minor_axis print ('R: ({}, {})'.format(xR,yR)) print ('R: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xR,yR)) # Verify that point R is on ellipse: sum_zero((A*xR**2, B*yR**2, C*xR*yR, D*xR, E*yR, F)) and 1/0 s1 = 'e' ; print (s1, '=', eval(s1)) print ('D1: ({}, {})'.format(xD1,yD1)) print ('D1: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xD1,yD1)) print ('Directrix 1: ({})x + ({})y + ({}) = 0'.format(adx1, bdx1, cdx1)) print() # For proof, reverse the process: (abc1,epq1), (abc2,epq2) = calculate_abc_epq (ABCDEF) a1,b1,c1 = abc1 ; e1,p1,q1 = epq1 print ('Directrix 1: ({})x + ({})y + ({}) = 0'.format(a1, b1, c1)) print ('Eccentricity e1: {}'.format(e1)) print ('F1: ({}, {})'.format(p1,q1)) print() a2,b2,c2 = abc2 ; e2,p2,q2 = epq2 print ('Directrix 2: ({})x + ({})y + ({}) = 0'.format(a2, b2, c2)) print ('Eccentricity e2: {}'.format(e2)) print ('F2: ({}, {})'.format(p2,q2)) print ('\nEquation of ellipse with integer coefficients:') A,B,C,D,E,F = [ reduce_Decimal_number(-v*1000000/64) for v in ABCDEF ] str1 = '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0' print (str1.format(A,B,C,D,E,F)) </syntaxhighlight> <syntaxhighlight> F1: (1, -7) F1: (x - (1))^2 + (y - (-7))^2 = 1 F2: (-1.24, 0.68) F2: (x - (-1.24))^2 + (y - (0.68))^2 = 1 length_of_major_axis = 10 M: (-0.12, -3.16) M: (x - (-0.12))^2 + (y - (-3.16))^2 = 1 length_of_minor_axis = 6 dx,dy = -0.28 0.96 dnx,dny = 0.96 0.28 R: (2.76, -2.32) R: (x - (2.76))^2 + (y - (-2.32))^2 = 1 e = 0.8 D1: (1.63, -9.16) D1: (x - (1.63))^2 + (y - (-9.16))^2 = 1 Directrix 1: (-0.28)x + (0.96)y + (9.25) = 0 Directrix 1: (0.28)x + (-0.96)y + (-9.25) = 0 Eccentricity e1: 0.8 F1: (1, -7) Directrix 2: (0.28)x + (-0.96)y + (3.25) = 0 Eccentricity e2: 0.8 F2: (-1.24, 0.68) Equation of ellipse with integer coefficients: </syntaxhighlight> <math>(14841)x^2 + (6409)y^2 + (5376)xy + (20550)x + (41150)y + (-74375) = 0</math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} =allEqual= {{Robelbox|title=[[Wikiversity:Welcome|Welcome]]|theme={{{theme|9}}}}} <div style="padding-top:0.25em; 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To learn more about Wikiversity, try a [[Help:Guides|guided tour]], learn about [[Wikiversity:Adding content|adding content]], or [[Wikiversity:Introduction|start editing now]]. </div> <syntaxhighlight lang=python> # python code. if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 : pass </syntaxhighlight> {{Robelbox/close}} {{Robelbox/close}} {{Robelbox/close}} <noinclude> [[Category: main page templates]] </noinclude> {| class="wikitable" |- ! <math>x</math> !! <math>x^2 - N</math> |- | <code></code><code>6</code> || <code>-221</code> |- | <code></code><code>7</code> || <code>-208</code> |- |- | <code>10</code> || <code>-157</code> |- | <code>11</code> || <code>-136</code> |- | <code>12</code> || <code>-113</code> |- | <code>13</code> || <code></code><code>-88</code> |- | <code>26</code> || <code></code><code>419</code> |} =Testing= ======table1====== {|style="border-left:solid 3px blue;border-right:solid 3px blue;border-top:solid 3px blue;border-bottom:solid 3px blue;" align="center" | Hello As <math>abs(x)</math> increases, the value of <math>f(x)</math> is dominated by the term <math>-ax^3.</math> When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large positive value, <math>f(x)</math> is always negative. <syntaxhighlight> 1.4142135623730950488016887242096980785696718753769480731766797379907324784621070388503875343276415727 3501384623091229702492483605585073721264412149709993583141322266592750559275579995050115278206057147 0109559971605970274534596862014728517418640889198609552329230484308714321450839762603627995251407989 </syntaxhighlight> |} {{RoundBoxTop|theme=2}} [[File:0410cubic01.png|thumb|400px|''' Graph of cubic function with coefficient a negative.''' </br> There is no absolute maximum or absolute minimum. ]] Coefficient <math>a</math> may be negative as shown in diagram. As <math>abs(x)</math> increases, the value of <math>f(x)</math> is dominated by the term <math>-ax^3.</math> When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large positive value, <math>f(x)</math> is always negative. Unless stated otherwise, any reference to "cubic function" on this page will assume coefficient <math>a</math> positive. {{RoundBoxBottom}} <math>x_{poi} = -1</math> <math></math> <math></math> <math></math> <math></math> =====Various planes in 3 dimensions===== {{RoundBoxTop|theme=2}} <gallery> File:0713x=4.png|<small>plane x=4.</small> File:0713y=3.png|<small>plane y=3.</small> File:0713z=-2.png|<small>plane z=-2.</small> </gallery> {{RoundBoxBottom}} <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> 1.4142135623730950488016887242096980785696718753769480731766797379907324784621070388503875343276415727 3501384623091229702492483605585073721264412149709993583141322266592750559275579995050115278206057147 0109559971605970274534596862014728517418640889198609552329230484308714321450839762603627995251407989 6872533965463318088296406206152583523950547457502877599617298355752203375318570113543746034084988471 6038689997069900481503054402779031645424782306849293691862158057846311159666871301301561856898723723 5288509264861249497715421833420428568606014682472077143585487415565706967765372022648544701585880162 0758474922657226002085584466521458398893944370926591800311388246468157082630100594858704003186480342 1948972782906410450726368813137398552561173220402450912277002269411275736272804957381089675040183698 6836845072579936472906076299694138047565482372899718032680247442062926912485905218100445984215059112 0249441341728531478105803603371077309182869314710171111683916581726889419758716582152128229518488472 </syntaxhighlight> <math>\theta_1</math> {{RoundBoxTop|theme=2}} [[File:0422xx_x_2.png|thumb|400px|''' Figure 1: Diagram illustrating relationship between <math>f(x) = x^2 - x - 2</math> and <math>f'(x) = 2x - 1.</math>''' </br> ]] {{RoundBoxBottom}} <math>O\ (0,0,0)</math> <math>M\ (A_1,B_1,C_1)</math> <math>N\ (A_2,B_2,C_2)</math> <math>\theta</math> <math>\ \ \ \ \ \ \ \ </math> :<math>\begin{align} (6) - (7),\ 4Apq + 2Bq =&\ 0\\ 2Ap + B =&\ 0\\ 2Ap =&\ - B\\ \\ p =&\ \frac{-B}{2A}\ \dots\ (8) \end{align}</math> <math>\ \ \ \ \ \ \ \ </math> :<math>\begin{align} 1.&4141475869yugh\\ &2645er3423231sgdtrf\\ &dhcgfyrt45erwesd \end{align}</math> <math>\ \ \ \ \ \ \ \ </math> :<math> 4\sin 18^\circ = \sqrt{2(3 - \sqrt 5)} = \sqrt 5 - 1 </math> mnzjxpg5563k31gbh8wdx3l36eathyd 2835180 2835156 2026-09-30T12:58:36Z ThaniosAkro 2805358 /* matrix corrected */ 2835180 wikitext text/x-wiki ==Table== {| class="wikitable" |- | From <math>(3):</math> || <math>p^3</math>|| || <math>+Ap</math> || <math>+B</math>|| <math>= 0</math> || <math>\dots (5)</math> |- | From <math>(4):</math> || || <math>Cp^2</math>|| <math></math> || <math>+D</math>|| <math>= 0</math> || <math>\dots (6)</math> |- | <math>(5)*D</math> || <math>Dp^3</math>|| || <math>+DAp</math> || <math>+DB</math>|| <math>= 0</math> || <math>\dots (7)</math> |- | <math>(6)*B</math> || || <math>BCp^2</math>|| <math></math> || <math>+BD</math>|| <math>= 0</math> || <math>\dots (8)</math> |- | <math>(7)-(8)</math> || <math>Dp^3</math>||<math>-BCp^2</math> || <math>+DAp</math> || <math></math>|| <math>= 0</math> || <math>\dots (9)</math> |- | Simplify <math>(9)</math> || <math></math>||<math>Dp^2</math> || <math>-BCp</math> || <math>+DA</math>|| <math>= 0</math> || <math>\dots (10)</math> |- | <math>(6)*A</math> || || <math>ACp^2</math>|| <math></math> || <math>+AD</math>|| <math>= 0</math> || <math>\dots (11)</math> |- | <math>(10)-(11)</math> || <math></math>||<math>Dp^2-ACp^2</math> || <math>-BCp</math> || <math></math>|| <math>= 0</math> || <math>\dots (12)</math> |- | Simplify <math>(12)</math> || <math></math>|| || <math>Dp-ACp</math> || <math>-BC</math> || <math>= 0</math> || <math>\dots (13)</math> |} ====First result==== <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> Calculate values_of_i : <syntaxhighlight lang=python> print ('\nWhen ints become huge:') values_of_i = solveMbyN (matrix) sx = 'values_of_i' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> When ints become huge: solveMbyN (input_, level = -41) : <class 'OverflowError'> OverflowError('int too large to convert to float') Length of input = 23 input_[0] = Error in this row. input_[1] = Error in this row. input_[2] = Error in this row. input_[3] = [-7.048390979785929e+176, 1.1003906499643917e+176, 1.5070856217200028e+174, 1.955699032422673e+173, ...... 0.0] input_[4] = [510.0, 0.0, 0.0, 0.0, 320.0, -1150.0, 270.0, 0.0, 0.0, 320.0, -590.0, 270.0, 0.0, 0.0, 320.0, -590.0, ...... 0.0] input_[5] = [0.0, 520.0, 0.0, 0.0, 0.0, 270.0, -1060.0, 220.0, 0.0, 0.0, 270.0, -490.0, 220.0, 0.0, 0.0, 270.0, ...... 0.0] input_[6] = [0.0, 0.0, 530.0, 0.0, 0.0, 0.0, 220.0, -970.0, 170.0, 0.0, 0.0, 220.0, -390.0, 170.0, 0.0, 0.0, 220.0, ...... 0.0] input_[7] = Error in this row. values_of_i = None </syntaxhighlight> <syntaxhighlight lang=python> print ('\nConvert input to floats:') matrix1 = [ list(v) for v in matrix ] matrix1[0][0] = float(matrix1[0][0]) values_of_i = solveMbyN (matrix1) sx = 'values_of_i' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> Convert input to floats: solveMbyN (input_, level = -40) : <class 'KeyError'> KeyError('Internal error. input[1][0] = nan, should be 0.') Length of input = 24 input_[0] = [-1.7360455505275518e+174, 1.4096781959571856e+174, -2.2007812999287836e+173, -3.014171243439967e+171, ...... 0.0] input_[1] = [-3.7974175914221006e+162, 3.309163202261842e+161, 2.4114748810711523e+162, -4.426635506031073e+161, ...... 0.0] input_[2] = [-2.4975968400753463e+139, 5.704494025143264e+138, -2.7146889822895123e+138, 1.4057733058789272e+139, ...... 0.0] input_[3] = [7.667237322891148e+182, -1.7692205437935546e+182, -2.341735229706114e+180, 4.1615580570562045e+181, ...... -0.0] input_[4] = [-500.0, 0.0, 0.0, 0.0, 0.0, 1240.0, -320.0, 0.0, 0.0, 0.0, 690.0, -320.0, 0.0, 0.0, 0.0, 690.0, -320.0, ...... 0.0] input_[5] = [0.0, 510.0, 0.0, 0.0, 0.0, 320.0, -1150.0, 270.0, 0.0, 0.0, 320.0, -590.0, 270.0, 0.0, 0.0, 320.0, -590.0, ...... 0.0] input_[6] = [0.0, 0.0, 520.0, 0.0, 0.0, 0.0, 270.0, -1060.0, 220.0, 0.0, 0.0, 270.0, -490.0, 220.0, 0.0, 0.0, 270.0, ...... 0.0] input_[7] = [0.0, 0.0, 0.0, 530.0, 0.0, 0.0, 0.0, 220.0, -970.0, 170.0, 0.0, 0.0, 220.0, -390.0, 170.0, 0.0, 0.0, ...... 0.0] values_of_i = None </syntaxhighlight> =====Success===== <syntaxhighlight lang=python> print ('\nSet global variable enable_reduceRow:') enable_reduceRow = 1 values_of_i = solveMbyN (matrix1) </syntaxhighlight> Success: <syntaxhighlight> Set global variable enable_reduceRow: i10 = 1.0000000000000049 ; i11 = 1.643236374952256 ; i12 = 2.316468657232291 ; i13 = 3.0507456069545116 i14 = 3.908085797412319 ; i15 = 0.5970301043016677 ; i16 = 0.8274774533758196; i17 = 1.225283946841065 i18 = 1.5617922630400025 ; i19 = 0.369273540611037 ; i20 = 0.3858385105885722; i21 = 0.6270001063825295 i22 = 0.7040607630623028 ; i23 = 0.6129764173251202 ; i24 = 0.298576896960036 ; i25 = 0.44960726241462035 i26 = 0.7812212615819403 ; i27 = 0.7165761045550649 ; i28 = 0.5186812635664733; i29 = 0.266770119423805 i30 = 0.5896680016803755 ; i31 = 1.475274068751303 ; i32 = 0.9632057010422588; i33 = 0.5801910619990465 i34 = 0.30799558703953794; i35 = 2.4693659910366916 ; i36 = 1.583773707944257 ; i37 = 1.0123878002551232 i38 = 0.6135963601029517 ; i39 = 0.3175434839291887 ; i40 = 2.7147355593758107; i41 = 2.125067557695435 i42 = 1.6754602952808149 ; i43 = 1.2896217846922426 ; i44 = 0.692591680390575 ; i45 = 0.8855922830924343 i46 = 1.7538676385971101 ; i47 = 1.4222536394297902 ; i48 = 1.181092043635833 ; i49 = 0.6432363749522512 i50 = 0.5713859076891339 ; i51 = 1.0834542753981782 ; i52 = 1.1480994324250535; i53 = 1.0710387757452802 i54 = 0.6732322822800348 ; i55 = 0.39879144015217155; i56 = 0.7818060791953839; i57 = 0.9797009201839757 i58 = 1.0707852659211583 ; i59 = 0.7342769497222208 ; i60 = 0.2960528761737631; i61 = 0.6419329634235106 i62 = 0.8938441075661789 ; i63 = 1.2082436279312632 ; i64 = 0.8573401904578074; i65 = 0.2438588716389498 i66 = 0.5518544586784879 ; i67 = 0.8186245781022927 ; i68 = 1.1172014750623287; i69 = 1.4864750156733657 i70 = -0.3074083196094299; i71 = 1.5434221599024214 ; i72 = 1.7538814225756034; i73 = -0.07368461229023889 # Notice that i70, i73 are negative. </syntaxhighlight> =====Check all conditions===== The following conditions are included for testing: <syntaxhighlight lang=python> more_econditions = [ "+ e49 + e70 - e10", "+ e19 + e69 - e71", "+ e35 + e45 - e72", "+ e65 + e73 - e34", ] extra_test_conditions = [ "+ e40 + e41 + e42 + e43 + e44 + e10 - e35 - e45 - e46 - e47 - e48 - e49", "+ e45 + e46 + e47 + e48 + e49 + e11 - e36 - e50 - e51 - e52 - e53 - e54", "+ e50 + e51 + e52 + e53 + e54 + e12 - e37 - e55 - e56 - e57 - e58 - e59", "+ e55 + e56 + e57 + e58 + e59 + e13 - e38 - e60 - e61 - e62 - e63 - e64", "+ e60 + e61 + e62 + e63 + e64 + e14 - e39 - e65 - e66 - e67 - e68 - e69", "+ e44 + e10 + e11 + e12 + e13 + e14 - e69 - e15 - e16 - e17 - e18 - e19", "+ e43 + e15 + e16 + e17 + e18 + e19 - e68 - e20 - e21 - e22 - e23 - e24", "+ e42 + e20 + e21 + e22 + e23 + e24 - e67 - e25 - e26 - e27 - e28 - e29", "+ e41 + e25 + e26 + e27 + e28 + e29 - e66 - e30 - e31 - e32 - e33 - e34", "+ e40 + e30 + e31 + e32 + e33 + e34 - e65 - e35 - e36 - e37 - e38 - e39", "+ i35 + i40 + i72 - i14 - i69 - i71", """+ e40 + e41 + e42 + e43 + e44 + e10 + e11 + e12 + e13 + e14 = e35 + e36 + e37 + e38 + e39 + e65 + e66 + e67 + e68 + e69""", """+ e40 + e41 + e42 + e43 + e15 + e16 + e17 + e18 + e19 + e69 = e35 + e36 + e37 + e38 + e60 + e61 + e62 + e63 + e64 + e14""", """+ e40 + e41 + e42 + e20 + e21 + e22 + e23 + e24 + e68 + e69 = e35 + e36 + e37 + e55 + e56 + e57 + e58 + e59 + e13 + e14""", """+ e40 + e41 + e25 + e26 + e27 + e28 + e29 + e67 + e68 + e69 = e35 + e36 + e50 + e51 + e52 + e53 + e54 + e12 + e13 + e14""", """+ e40 + e30 + e31 + e32 + e33 + e34 + e66 + e67 + e68 + e69 = e35 + e45 + e46 + e47 + e48 + e49 + e11 + e12 + e13 + e14""" ] </syntaxhighlight> Two Auxiliary Functions: <syntaxhighlight lang=python> def sum_zero (values, tolerance = None) : ''' This function calculates sum of all values in input. If sum is very close to zero, sum is returned as zero. For example: sum_zero((2, -1.99999999999999999999999)) is returned as 0. ''' if tolerance == None : tolerance = Tolerance sump = sumn = 0 for v in values : if v > 0 : sump += v elif v < 0 : sumn -= v max = (sumn, sump)[sump > sumn] sum = sump - sumn if abs(sum) < tolerance: return type(sum)(0) if abs(sum) < tolerance*max : return type(sum)(0) return sum def convert_str_to_tuple (input_str) : ''' input is str like "+ i35 + i40 + i72 - i14 - i69 - i71" or "+ i35 + i40 + i72 == i14 + i69 + i71" This function returns tuple : (i35, i40, i72, - i14, - i69, - i71) ''' str0 = ' '.join(input_str.split()) if '=' in str0 : if '==' in str0 : splitter = '==' else : splitter = '=' str1,str2 = str0.split(splitter) t1 = convert_str_to_tuple (str1) t2 = convert_str_to_tuple (str2) return t1 + tuple(-v for v in t2) str1 = ';+'.join(str0.split('+')) str2 = ';-'.join(str1.split('-')) str3 = ','.join([ v for v in str2.split(';') if v.strip() ]) return eval(str3 + ',') </syntaxhighlight> Check 83 conditions: <syntaxhighlight lang=python> all_conditions = (iconditions + econditions + more_econditions + extra_test_conditions) # Following string is executable python code. exc_str_64ei = """ ( i10, i11, i12, i13, i14, i15, i16, i17, i18, i19, i20, i21, i22, i23, i24, i25, i26, i27, i28, i29, i30, i31, i32, i33, i34, i35, i36, i37, i38, i39, i40, i41, i42, i43, i44, i45, i46, i47, i48, i49, i50, i51, i52, i53, i54, i55, i56, i57, i58, i59, i60, i61, i62, i63, i64, i65, i66, i67, i68, i69, i70, i71, i72, i73, ) = values_of_i values_of_e = [ i*R for i,R in zip ( values_of_i, values_of_R ) ] ( e10, e11, e12, e13, e14, e15, e16, e17, e18, e19, e20, e21, e22, e23, e24, e25, e26, e27, e28, e29, e30, e31, e32, e33, e34, e35, e36, e37, e38, e39, e40, e41, e42, e43, e44, e45, e46, e47, e48, e49, e50, e51, e52, e53, e54, e55, e56, e57, e58, e59, e60, e61, e62, e63, e64, e65, e66, e67, e68, e69, e70, e71, e72, e73, ) = values_of_e """ exec(exc_str_64ei) tolerance = 1e-15 count = errors = 0 for condition in all_conditions : t1 = convert_str_to_tuple (condition) sum = sum_zero(t1, tolerance) count += 1 if sum : sx = 'sum, condition' ; print (sx, '=', eval(sx)) errors += 1 print ('Number of tests =', count) print ('Number of errors =', errors) </syntaxhighlight> With tolerance of <math>1e-15</math> there are 21 errors: <syntaxhighlight> sum, condition = (1.2505552149377763e-12, '+ e48 + e16 - e21 - e53') sum, condition = (1.2505552149377763e-12, '+ e49 + e11 - e16 - e54') sum, condition = (7.958078640513122e-13, '+ e52 + e22 - e27 - e57') sum, condition = (1.1368683772161603e-12, '+ e53 + e17 - e22 - e58') sum, condition = (2.2737367544323206e-12, '+ e54 + e12 - e17 - e59') ...... ...... Number of tests = 83 Number of errors = 21 </syntaxhighlight> With tolerance of <math>1e-14</math> there are no errors. <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> ====Calculate R==== =====matrix corrected===== {{RoundBoxTop|theme=2}} [[File:0710matrix64_01.png|thumb|400px|'''Diagram of network containing 64 resistors''' </br> Diagram has been corrected to show positive direction of current through R70, R73. ]] Original assumptions were that currrent flow through 64 resistors would be from bottom to top or from left to right. Examination of results shows that flow through R70, R73 is from right to left. Corrected diagram conforms to assumption that all current flow is from bottom towards top or from left to right. <syntaxhighlight lang=python> matrix1 = [ list(v) for v in matrix ] # Deep copy. # e70, i70 are at position 60 in each row of matrix1. # e73, i73 are at position 63 in each row of matrix1. for row in matrix1 : for p in (60,63) : if row[p] : row[p] *= -1 </syntaxhighlight> <code>matrix1</code> is corrected version of <code>matrix</code>. {{RoundBoxBottom}} =====Circuit parameters===== <syntaxhighlight> values_of_circuit_current = ('i40 + i72 + i35', 'i14 + i71 + i69') values_of_circuit_voltage = ( 'e72 + e46 + e47 + e48 + e70 + e10 + e11 + e12 + e13 + e14', 'e35 + e36 + e37 + e38 + e39 + e73 + e61 + e62 + e63 + e71', 'e40 + e41 + e42 + e43 + e44 + e10 + e11 + e12 + e13 + e14', 'e35 + e36 + e37 + e38 + e39 + e65 + e66 + e67 + e68 + e69', 'e40 + e41 + e42 + e43 + e15 + e16 + e17 + e18 + e19 + e69', 'e40 + e41 + e42 + e20 + e21 + e22 + e23 + e24 + e68 + e69', 'e40 + e41 + e25 + e26 + e27 + e28 + e29 + e67 + e68 + e69', 'e40 + e30 + e31 + e32 + e33 + e34 + e66 + e67 + e68 + e69', 'e35 + e45 + e46 + e47 + e48 + e49 + e11 + e12 + e13 + e14', 'e35 + e36 + e50 + e51 + e52 + e53 + e54 + e12 + e13 + e14', 'e35 + e36 + e37 + e55 + e56 + e57 + e58 + e59 + e13 + e14', 'e35 + e36 + e37 + e38 + e60 + e61 + e62 + e63 + e64 + e14', 'e72 + e31 - e50 + e37 + e38 + e39 + e73 + e61 - e28 + e57' + ( '- e22 + e53 - e16 + e70 + e10 + e11 + e12 + e13 + e14') ) </syntaxhighlight> =====Using floating point numbers:===== <syntaxhighlight lang=python> # python code: number_of_columns = 65 one = 1 ; Tolerance = 1e-14 # Following string is executable python code: exc_str1 = """ Values_of_R = [] for I in range(10, 74): new_line = [ 0 ] * number_of_columns place_in_line = I - 10 new_line[place_in_line] = one i = (I)/10 new_line[-1] = -i matrix1[-1] = new_line values_of_i = solveMbyN (matrix1) exec(exc_str_64ei) for Istr in values_of_circuit_current : I = eval(Istr) for Estr in values_of_circuit_voltage : E = eval(Estr) ; R = E/I ; Values_of_R += [R] print ('Number of calculations =', len(Values_of_R)) tmp = sorted(Values_of_R) minR = tmp[0] ; maxR = tmp[-1] s1 = 'minR' ; print(s1,'=',eval(s1)) s1 = 'maxR' ; print(s1,'=',eval(s1)) sum = sum_zero((minR, -maxR)) s1 = 'sum' ; print(s1,'=',eval(s1)) if not sum : print ('With Tolerance of {}, both minR and maxR are equal.'.format(Tolerance)) """ exec(exc_str1) </syntaxhighlight> <syntaxhighlight> Number of calculations = 1664 minR = 723.9285759884408 maxR = 723.9285759884439 sum = 0.0 With Tolerance of 1e-14, both minR and maxR are equal. </syntaxhighlight> This code produced 1664 values of R from minR through maxR, both included. With tolerance of <math>1e-14</math> all values of resistance R = 723.92857598844. =====Using Decimal numbers:===== With <code>enable_reduceRow</code> clear : <syntaxhighlight lang=python> enable_reduceRow = 0 Precision = dgt.prec = 60 Tolerance = dD('1e-' + str(Precision-3)) one = dD(1) try : exec(exc_str1) except : pass </syntaxhighlight> <syntaxhighlight> solveMbyN (input_, level = -52) : <class 'decimal.Overflow'> Overflow([<class 'decimal.Overflow'>]) Length of input = 12 input_[0] = [-inf, inf, -inf, inf, inf, -inf, inf, -inf, inf, -inf, -inf, inf, 0.0] input_[1] = [inf, -inf, -inf, -inf, -inf, inf, -inf, -inf, -inf, -inf, inf, -inf, 0.0] input_[2] = [-inf, inf, inf, inf, -inf, -inf, inf, inf, -inf, inf, inf, inf, 0.0] input_[3] = [inf, -inf, -inf, inf, -inf, inf, -inf, -inf, inf, -inf, -inf, inf, 0.0] input_[4] = [620.0, 0.0, 0.0, 0.0, 290.0, -1200.0, 240.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] input_[5] = [0.0, 630.0, 0.0, 0.0, 0.0, 240.0, -1110.0, 190.0, 0.0, 0.0, 0.0, 0.0, 0.0] input_[6] = [inf, -inf, inf, -inf, -inf, inf, -inf, -inf, inf, -inf, inf, -inf, 0.0] input_[7] = [-inf, inf, inf, inf, inf, -inf, inf, inf, inf, inf, -inf, inf, 0.0] </syntaxhighlight> With <code>enable_reduceRow</code> set : <syntaxhighlight lang=python> enable_reduceRow = 1 exec(exc_str1) </syntaxhighlight> <syntaxhighlight> Number of calculations = 1664 minR = 723.928575988442547699732563335265663515838075102937503680560 maxR = 723.928575988442547699732563335265663515838075102937503680663 sum = 0 With Tolerance of 1E-57, both minR and maxR are equal. </syntaxhighlight> With tolerance of <math>1e-57</math> all values of resistance R = 723.928575988442547699732563335265663515838075102937503681. <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> ==Making the Decimal object== The following function verifies that we are working with Decimal objects. <syntaxhighlight lang=python> import sys import decimal getcontext = decimal.getcontext dD = D = Decimal = decimal.Decimal DT = decimal.DecimalTuple dgt = decimal.getcontext() dgt.prec = 50 def print_error (error, x=None, thisName=None) : """ Prints error derived from sys.exc_info(). """ list1 = error.split(',') v1 = ','.join(list1[1:-1]) if thisName : print (thisName) if x != None : print (' Input =', (str(x))[:60]) print (' ', list1[0]) print (' ', v1) print (' ', list1[-1]) def makeDecimal (x, flag = 0) : ''' output = makeDecimal (x [, flag]) x is a single object convertible to Decimal object. returns Decimal object or returns None on error. ''' thisName = 'makeDecimal (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) if isinstance(x, dD) : return x if isinstance(x, int) : return dD(x) if isinstance(x, float) : return dD(str(x)) if isinstance(x, str) : try : error = '' output = dD(x) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return None return output if isinstance(x, (list,tuple,DT)) : try : error = '' v1,v2,v3 = x if isinstance(v2, (tuple,list)) : output = dD(x) else : output = dD( ( v1, list(v2), v3 ) ) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return None return output if flag : print (' Input not recognized.') return None </syntaxhighlight> ===checkComplex(x)=== This function verifies that the object is a valid complex tuple. <syntaxhighlight lang=python> def checkComplex(x, flag = 0) : """ status = checkComplex(x [, flag]) x must be : (v1,v2,'rectangular') or (v1,v2,'polar') v1,v2 must be type Decimal. """ thisName = 'checkComplex (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) try: error = '' v1,v2,str1 = x isinstance (v1,dD) or ({}['v1 must be type Decimal.']) isinstance (v2,dD) or ({}['v2 must be type Decimal.']) (isinstance (str1,str) and str1) or ({}['str1 must be valid string.']) str1 = str1.lower() if str1 == 'rectangular'[:len(str1)] : pass elif str1 == 'polar'[:len(str1)] : pass else : ({}['str1 must be "rectangular" or "polar".']) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return False return True </syntaxhighlight> ===str_to_complex (input_string)=== <syntaxhighlight lang=python> import re # The re pattern for numbers to be found in string of type complex. # In string like ' 1234567890987654323456E-6 + 987654321234567890987e+2J ' # extracts '1234567890987654323456E-6' and '+987654321234567890987e+2J'. # eval allows ' 12_3456_7890_9876_5432_3456E-6 + 987654321234567890987e+2J '. # Conversion to Decimal allows: '__987_65432123____4567890_987___'. # eval does not allow ' 0123 ' but allows ' 2e04 '. # Conversion to Decimal allows: ' 0123 ' digits = '[_0123456789]' integer = '[_0123456789]{1,}' # Matches 1 23 345 4567 56789 exponent = '[Ee][\+\-]{{0,1}}{}'.format(integer) # Matches e8 e+8 e-8 or E8 E+8 E-8 Exponent = '({}){{0,1}}'.format(exponent) # exponent 0 or 1 times. float1 = '({})\.{{0,1}}'.format(integer) # Matches 123 2345. float2 = '{}{{0,}}\.{}'.format(digits, integer) # Matches 123.345 .345 float_ = '(({})|({}))'.format(float2,float1) rvalue = '{}({})'.format(float_,Exponent) rvalue_signed = '[\+\-]{{0,1}}{}'.format(rvalue) ivalue_signed = '{}[Jj]'.format(rvalue_signed) def str_to_complex (input_string) : """ a,b = str_to_complex (input_string) input_string could be ' 1234567890987654323456E-6 + 987654321234567890987e+2J ' input_string could be ' ' ' ( 12345678909876543234561234567890987.654323456E-6 + 987654321234567890987987654321.23764567890987e+2J ) ' ' ' or ' ' ' - ( ( 12345678_90543123456789054_312345678905431234567890543e-014 + 543123456789054_3123456789054312345_67890543654327453E-1_3J ) ) ' ' ' or ' ' ' - ( ( 12345678_90543123456789054_312345678905431234567890543e-014 + # Note the '_' 543123456789054_3123456789054312345_67890543654327453E-1_3J ) ) ' ' ' or '4', '-4', '(4)', '(-4)', '-(4)', '-(-4)' or '( +3j)', '+(-3J)', '-(3j)', '-(-3J)' or '( 4+3j)', '+(-3 + 4J)','-( 4+3j)', '-(-3 + 4J)', This function retains precision of a,b """ try : status = 0 isinstance(input_string,str) or ({}['input_string not type str.']) str1 = input_string.strip() cx1 = eval(str1) isinstance(cx1,(int,float,complex)) or ({}['cx1 not desired type.']) except : status = 1 if status : return # This code removes white lines and comments, if any, at end of each line. new_line = ''' '''[-1:] lines = [ line for Line in str1.split(new_line) for line in [ Line.rstrip() ] if line ] lines = [ v for line in lines for parts in [ line.split('#') ] for v in [ parts[0]] ] str1 = ''.join(lines) str1 = ''.join(str1.split()) if isinstance (cx1, (int,float)) : resultr = re.search(rvalue_signed, str1) resultr or ({}['rvalue not found.']) dD1 = dD(resultr[0]) v1 = eval(str(dD1)) if v1 == cx1 : return dD1,dD(0) if v1 == -cx1 : return -dD1,dD(0) ({}['dD1 not recognized.']) # cx1 must be complex. It must contain imaginary value. resulti = re.search(ivalue_signed, str1) resulti or ({}['ivalue not found.']) str2j = resulti[0] ; str2 = str2j[:-1] dD2 = dD(str2) str1 = ''.join(str1.split(str2j)) # cx1 may contain real value. resultr = re.search(rvalue_signed, str1) if resultr : dD1 = dD(resultr[0]) else : dD1 = dD(0) cx2 = complex(dD1,dD2) if cx2.real == cx1.real : pass elif cx2.real == -cx1.real : dD1 = dD1.copy_negate() else : ({}['dD1 Not Recognized.']) if cx2.imag == cx1.imag : pass elif cx2.imag == -cx1.imag : dD2 = dD2.copy_negate() else : ({}['dD2 Not Recognized.']) cx3 = complex(dD1, dD2) if cx3 == cx1 : return dD1,dD2 ({}['No match for cx3.']) </syntaxhighlight> ===makeComplex(x)=== <syntaxhighlight lang=python> def makeComplex (x, flag = 0) : ''' result = makeComplex (x[, flag]) Input can be tuple with 1,2 or 3 members. If 1 or 2 members, 'rect' is understood. The one member or single object may be int, float, complex, CompleX or string convertible to int, float or complex. x = makeComplex(4) x = makeComplex((4,)) x = makeComplex(('4',0)) x = makeComplex((4,'0', 'rect')) x = makeComplex(4+0j) x = makeComplex('4+0j') x = makeComplex(('4+0j',)) In all seven cases above x = ( Decimal('4'), Decimal('0'), 'rect' ) output is always (modulus, phase, "polar") or (real_part, imag_part, "rect") modulus, phase, real_part, imag_part are Decimal objects. On error returns None. ''' thisName = 'makeComplex (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) if isinstance(x, CompleX) : # New class CompleX (note the punctuation.) x.check() return (x.r, x.i, 'rect') if isinstance (x,complex) : return makeComplex (( x.real, x.imag )) try : status = 1 a,b = str_to_complex (x) except : status = 0 if status : return a,b,'rect' try : status = 1 result = makeDecimal(x) isinstance(result, Decimal) or ({}['Expecting result to be type Decimal.']) output = result,dD(0),'rect' except : status = 0 if status : return output try : status = 1 v1, = x # Allow for (( 3+4j ),) except : status = 0 if status : return makeComplex (v1) try : status = 1 ; error = '' if len(x) == 2 : v1,v2 = [ makeDecimal (v) for v in x ] str1 = 'rect' elif len(x) == 3 : v1,v2,str1 = x v1,v2 = [ makeDecimal (v) for v in (v1,v2) ] else : ({}['len(x) not in (2,3)']) output = v1,v2,str1 checkComplex(output) or ({}['output not valid complex.']) if str1[0] in 'rR' : output = v1,v2,'rect' else : output = v1,v2,'polar' except : status = 0 ; error = str(sys.exc_info()) if status : return output if flag : print_error (error) return </syntaxhighlight> =Conic sections generally= Within the two dimensional space of Cartesian Coordinate Geometry a conic section may be located anywhere and have any orientation. This section examines the parabola, ellipse and hyperbola, showing how to calculate the equation of the section, and also how to calculate the foci and directrices given the equation. ==Latera recta et cetera== "Latus rectum" is a Latin expression meaning "straight side." According to Google, the Latin plural of "latus rectum" is "latera recta," but English allows "latus rectums" or possibly "lati rectums." The title of this section is poetry to the eyes and music to the ears of a Latin student and this author hopes that the gentle reader will permit such poetic licence in a mathematical topic. The translation of the title is "Latus rectums and other things." This section describes the calculation of interesting items associated with the ellipse: latus rectums, major axis, minor axis, focal chords, directrices and various points on these lines. When given the equation of an ellipse, the first thing is to calculate eccentricity, foci and directrices as shown above. Then verify that the curve is in fact an ellipse. From these values everything about the ellipse may be calculated. For example: {{RoundBoxTop|theme=2}} [[File:0608ellipse01.png|thumb|400px|'''Graph of ellipse <math>1771x^2 + 1204y^2 + 1944xy -44860x - 18520y + 214400 = 0.</math>''' </br> </br> Axis : (-0.8)x + (-0.6)y + (9.4) = 0</br> Eccentricity = 0.9</br> </br> Directrix 2 : (0.6)x + (-0.8)y + (2) = 0</br> Latus rectum RS : (0.6)x + (-0.8)y + (-0.8) = 0</br> Minor axis : (0.6)x + (-0.8)y + (-12.73684210526315789474) = 0</br> Latus rectum PU : (0.6)x + (-0.8)y + (-24.67368421052631578947) = 0</br> Directrix 1 : (0.6)x + (-0.8)y + (-27.47368421052631578947) = 0</br> </br> <math>\text{ID2}</math> = (6.32, 7.24)</br> <math>\text{I2}</math> = (7.204210526315789473684, 6.061052631578947368421)</br> F2 = (8, 5)</br> M = (15.16210526315789473684, -4.54947368421052631579)</br> F1 = (22.32421052631578947368, -14.09894736842105263158)</br> <math>\text{I1}</math> = (23.12, -15.16)</br> <math>\text{ID1}</math> = (24.00421052631578947368, -16.33894736842105263158)</br> </br> P = (20.30821052631578947368, -15.61094736842105263158)</br> Q = (10.53708406832736953616, -8.018239580333420216299)</br> R = (5.984, 3.488)</br> S = (10.016, 6.512)</br> T = (19.78712645798841993752, -1.080707788087632415281)</br> U = (24.34021052631578947368, -12.58694736842105263158)</br> </br> Length of major axis: <math>\text{I1I2}</math> = 26.52631578947368421052</br> Length of minor axis: QT = 11.56255298707631300170</br> Length of latus rectum: RS = PU = 5.04 ]] Consider conic section: <math>1771x^2 + 1204y^2 + 1944xy -44860x - 18520y + 214400 = 0.</math> This curve is ellipse with random orientation. <syntaxhighlight lang=python> # python code ABCDEF = A,B,C,D,E,F = 1771, 1204, 1944, -44860, -18520, 214400 # ellipse result = calculate_abc_epq(ABCDEF) (len(result) == 2) or 1/0 # ellipse or hyperbola (abc1,epq1), (abc2,epq2) = result a1,b1,c1 = abc1 ; e1,p1,q1 = epq1 a2,b2,c2 = abc2 ; e2,p2,q2 = epq2 (e1 == e2) or 2/0 (1 > e1 > 0) or 3/0 print ( '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0'.format(A,B,C,D,E,F) ) A,B,C,D,E,F = ABCDEF_from_abc_epq(abc1,epq1) print ('Equation of ellipse in standard form:') print ( '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0'.format(A,B,C,D,E,F) ) </syntaxhighlight> <syntaxhighlight> (1771)x^2 + (1204)y^2 + (1944)xy + (-44860)x + (-18520)y + (214400) = 0 Equation of ellipse in standard form: (-0.7084)x^2 + (-0.4816)y^2 + (-0.7776)xy + (17.944)x + (7.408)y + (-85.76) = 0 </syntaxhighlight> <syntaxhighlight lang=python> # python code def sum_zero(input) : ''' sum = sum_zero(input) If sum is close to 0 and Tolerance permits, sum is returned as 0. For example: if input contains (2, -1.999999999999999999999) this function returns sum of these 2 values as 0. ''' global Tolerance sump = sumn = 0 for v in input : if v > 0 : sump += v elif v < 0 : sumn -= v sum = sump - sumn if abs(sum) < Tolerance : return (type(Tolerance))(0) min, max = sorted((sumn,sump)) if abs(sum) <= Tolerance*min : return (type(Tolerance))(0) return sum </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ===Major axis=== <syntaxhighlight lang=python> # axis is perpendicular to directrix. ax,bx = b1,-a1 # axis contains foci. ax + by + c = 0 cx = reduce_Decimal_number(-(ax*p1 + bx*q1)) axis = ax,bx,cx print ( ' Axis : ({})x + ({})y + ({}) = 0'.format(ax,bx,cx) ) print ( ' Eccentricity = {}'.format(e1) ) print () print ( ' Directrix 1 : ({})x + ({})y + ({}) = 0'.format(a1,b1,c1) ) print ( ' Directrix 2 : ({})x + ({})y + ({}) = 0'.format(a2,b2,c2) ) F1 = p1,q1 # Focus 1. print ( ' F1 : ({}, {})'.format(p1,q1) ) F2 = p2,q2 # Focus 2. print ( ' F2 : ({}, {})'.format(p2,q2) ) # Direction cosines along axis from F1 towards F2: dx,dy = a1,b1 # p2 = p1 + dx*distance_F1_F2 # q2 = q1 + dy*distance_F1_F2 if dx : distance_F1_F2 = (p2 - p1)/dx else : distance_F1_F2 = (q2 - q1) if distance_F1_F2 < 0 : distance_F1_F2 *= -1 dx *= -1 ; dy *= -1 # Intercept on directrix1 distance_from_F1_to_ID1 = abs(a1*p1 + b1*q1 + c1) ID1 = xID1,yID1 = p1 - dx*distance_from_F1_to_ID1, q1 - dy*distance_from_F1_to_ID1 print ( ' Intercept ID1 : ({}, {})'.format(xID1,yID1) ) # # distance_F1_F2 # -------------------- = e # length_of_major_axis # length_of_major_axis = distance_F1_F2 / e1 # Intercept1 on curve distance_from_F1_to_curve = (length_of_major_axis - distance_F1_F2 )/2 xI1,yI1 = p1 - dx*distance_from_F1_to_curve, q1 - dy*distance_from_F1_to_curve I1 = xI1,yI1 = [ reduce_Decimal_number(v) for v in (xI1,yI1) ] print ( ' Intercept I1 : ({}, {})'.format(xI1,yI1) ) </syntaxhighlight> <syntaxhighlight> Axis : (-0.8)x + (-0.6)y + (9.4) = 0 Eccentricity = 0.9 Directrix 1 : (0.6)x + (-0.8)y + (-27.47368421052631578947) = 0 Directrix 2 : (0.6)x + (-0.8)y + (2) = 0 F1 : (22.32421052631578947368, -14.09894736842105263158) F2 : (8, 5) Intercept ID1 : (24.00421052631578947368, -16.33894736842105263158) Intercept I1 : (23.12, -15.16) </syntaxhighlight> {{RoundBoxTop|theme=2}} Techniques similar to above can be used to calculate points <math>I2, ID2.</math> {{RoundBoxBottom}} ===Latus rectums=== <syntaxhighlight lang=python> # direction cosines along latus rectum. dlx,dly = -dy,dx # # distance from U to F1 half_latus_rectum # ------------------------------ = ----------------------- = e1 # distance from U to directrix 1 distance_from_F1_to_ID1 # half_latus_rectum = reduce_Decimal_number(e1*distance_from_F1_to_ID1) # latus rectum 1 # Focal chord has equation (afc)x + (bfc)y + (cfc) = 0. afc,bfc = a1,b1 cfc = reduce_Decimal_number(-(afc*p1 + bfc*q1)) print ( ' Focal chord PU : ({})x + ({})y + ({}) = 0'.format(afc,bfc,cfc) ) P = xP,yP = p1 + dlx*half_latus_rectum, q1 + dly*half_latus_rectum print ( ' Point P : ({}, {})'.format(xP,yP) ) U = xU,yU = p1 - dlx*half_latus_rectum, q1 - dly*half_latus_rectum print ( ' Point U : ({}, {})'.format(xU,yU) ) distance = reduce_Decimal_number(( (xP - xU)**2 + (yP - yU)**2 ).sqrt()) print (' Length PU =', distance) print (' half_latus_rectum =', half_latus_rectum) </syntaxhighlight> <syntaxhighlight> Focal chord PU : (0.6)x + (-0.8)y + (-24.67368421052631578947) = 0 Point P : (20.30821052631578947368, -15.61094736842105263158) Point U : (24.34021052631578947368, -12.58694736842105263158) Length PU = 5.04 half_latus_rectum = 2.52 </syntaxhighlight> {{RoundBoxTop|theme=2}} Techniques similar to above can be used to calculate points <math>R, S.</math> {{RoundBoxBottom}} ===Minor axis=== <syntaxhighlight lang=python> print () # Mid point between F1, F2: M = xM,yM = (p1 + p2)/2, (q1 + q2)/2 print ( ' Mid point M : ({}, {})'.format(xM,yM) ) half_major = length_of_major_axis / 2 half_distance = distance_F1_F2 / 2 # half_distance**2 + half_minor**2 = half_major**2 half_minor = ( half_major**2 - half_distance**2 ).sqrt() length_of_minor_axis = half_minor * 2 Q = xQ,yQ = xM + dlx*half_minor, yM + dly*half_minor T = xT,yT = xM - dlx*half_minor, yM - dly*half_minor print ( ' Point Q : ({}, {})'.format(xQ,yQ) ) print ( ' Point T : ({}, {})'.format(xT,yT) ) print (' length_of_major_axis =', length_of_major_axis) print (' length_of_minor_axis =', length_of_minor_axis) # # A basic check. # length_of_minor_axis**2 = (length_of_major_axis**2)(1-e**2) # # length_of_minor_axis**2 # ----------------------- = 1-e**2 # length_of_major_axis**2 # # length_of_minor_axis**2 # ----------------------- + (e**2 - 1) = 0 # length_of_major_axis**2 # values = (length_of_minor_axis/length_of_major_axis)**2, e1**2 - 1 sum_zero(values) and 3/0 aM,bM = a1,b1 # Minor axis is parallel to directrix. cM = reduce_Decimal_number(-(aM*xM + bM*yM)) print ( ' Minor axis : ({})x + ({})y + ({}) = 0'.format(aM,bM,cM) ) </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> Mid point M : (15.16210526315789473684, -4.54947368421052631579) Point Q : (10.53708406832736953616, -8.018239580333420216299) Point T : (19.78712645798841993752, -1.080707788087632415281) length_of_major_axis = 26.52631578947368421052 length_of_minor_axis = 11.56255298707631300170 Minor axis : (0.6)x + (-0.8)y + (-12.73684210526315789474) = 0 </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> ===Checking=== {{RoundBoxTop|theme=2}} All interesting points have been calculated without using equations of any of the relevant lines. However, equations of relevant lines are very useful for testing, for example: * Check that points <math>ID2, I2, F2, M, F1, I1, ID1</math> are on axis. * Check that points <math>R, F2, S</math> are on latus rectum through <math>F2.</math> * Check that points <math>Q, M, T</math> are on minor axis through <math>M.</math> * Check that points <math>P, F1, U</math> are on latus rectum through <math>F1.</math> Test below checks that 8 points <math>I1, I2, P, Q, R, S, T, U</math> are on ellipse and satisfy eccentricity <math>e = 0.9.</math> <math></math> <math></math> {{RoundBoxBottom}} <syntaxhighlight lang=python> t1 = ( ('I1'), ('I2'), ('P'), ('Q'), ('R'), ('S'), ('T'), ('U'), ) for name in t1 : value = eval(name) x,y = [ reduce_Decimal_number(v) for v in value ] print ('{} : ({}, {})'.format((name+' ')[:2], x,y)) values = A*x**2, B*y**2, C*x*y, D*x, E*y, F sum_zero(values) and 3/0 # Relative to Directrix 1 and Focus 1: distance_to_F1 = ( (x-p1)**2 + (y-q1)**2 ).sqrt() distance_to_directrix1 = a1*x + b1*y + c1 e1 = distance_to_F1 / distance_to_directrix1 print (' e1 =',e1) # Raw value is printed. # Relative to Directrix 2 and Focus 2: distance_to_F2 = ( (x-p2)**2 + (y-q2)**2 ).sqrt() distance_to_directrix2 = a2*x + b2*y + c2 e2 = distance_to_F2 / distance_to_directrix2 e2 = reduce_Decimal_number(e2) print (' e2 =',e2) # Clean value is printed. </syntaxhighlight> {{RoundBoxTop|theme=2}} Note the differences between "raw" values of <math>e_1</math> and "clean" values of <math>e_2.</math> {{RoundBoxBottom}} <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> I1 : (23.12, -15.16) e1 = -0.9000000000000000000034 e2 = 0.9 I2 : (7.204210526315789473684, 6.061052631578947368421) e1 = -0.9 e2 = 0.9 P : (20.30821052631578947368, -15.61094736842105263158) e1 = -0.9 e2 = 0.9 Q : (10.53708406832736953616, -8.018239580333420216299) e1 = -0.9000000000000000000002 e2 = 0.9 R : (5.984, 3.488) e1 = -0.9000000000000000000003 e2 = 0.9 S : (10.016, 6.512) e1 = -0.9000000000000000000003 e2 = 0.9 T : (19.78712645798841993752, -1.080707788087632415281) e1 = -0.8999999999999999999996 e2 = 0.9 U : (24.34021052631578947368, -12.58694736842105263158) e1 = -0.9 e2 = 0.9 </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> ==Traditional definition of ellipse== {{RoundBoxTop|theme=2}} [[File:0617ellipse01.png|thumb|400px|'''Traditional definition of ellipse.''' </br> Sum of distance <math>F_1G</math> and distance <math>F_2G</math> is constant. ]] Ellipse may be defined as the locus of a point that moves so that the sum of its distances from two fixed points is constant. In the diagram the two fixed points are the foci, Focus 1 or <math>F_1</math> and Focus 2 or <math>F_2.</math> Distance between <math>F_1</math> and <math>F_2</math>, distance <math>F_1F_2</math>, must be non-zero. Point <math>G</math> on perimeter of ellipse moves so that sum of distance <math>F_1G</math> and distance <math>F_2G</math> is constant. Points <math>T_1</math> and <math>T_2</math> are on axis of ellipse and the same rule applies to these points. distance <math>F_1T_1</math> + distance <math>T_1F_2</math> is constant. distance <math>F_1T_1</math> + distance <math>T_1F_2</math> <math>=</math> distance <math>F_1G</math> + distance <math>F_2G</math> <math>=</math> distance <math>F_2T_2</math> + distance <math>T_1F_2</math> <math>= \text{length of major axis.}</math> Therefore the constant is <math>\text{length of major axis}</math> which must be greater than distance <math>F_1F_2.</math> From information given, calculate eccentricity <math>e</math> and equation of one directrix. Choose directrix 1 <math>dx1</math> associated with focus F1. <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> {{RoundBoxBottom}} ==Ellipse at origin== {{RoundBoxTop|theme=2}} [[File:0901ellipse00.png|thumb|400px|'''Traditional definition of ellipse.''' </br> Sum of distance <math>F_1P</math> and distance <math>F_2P</math> is constant. ]] Traditional definition of ellipse states that ellipse is locus of a point that moves so that sum of its distances from two fixed points is constant. By definition distance <math>F_2P</math> + distance <math>F_1P</math> is constant. <math>\sqrt{(x-(-p))^2 + y^2} + \sqrt{(x-p)^2 + y^2} = k\ \dots\ (1)</math> Expand <math>(1)</math> and result is <math>Ax^2 + By^2 + F = 0\ \dots\ (2)</math> where: <math>A = 4k^2 - 16p^2</math> <math>B = 4k^2</math> <math>F = 4k^2p^2 - k^4</math> When <math>y = 0,</math> point <math>B,\ Ax^2 = -F</math> <math>x^2 = \frac{-F}{A}</math> <math>= \frac{k^4 - 4k^2p^2}{4k^2 - 16p^2}</math> <math>=\frac{k^2(k^2-4p^2)}{4(k^2 - 4p^2)} = \frac{k^2}{4}.</math> Therefore: <math>x = \frac{k}{2} = a</math> <math>k = \text{length of major axis.}</math> By definition, distance <math>F_2A</math> + distance <math>F_1A = k.</math> Therefore distance <math>F_1A = a.</math> Intercept form of ellipse at origin: <math>(4k^2 - 16p^2)x^2 + (4k^2)y^2 = k^4 - 4k^2p^2</math> <math>\frac{4(k^2-4p^2)}{k^2(k^2-4p^2)}x^2 + \frac{4k^2}{k^2(k^2 - 4p^2)}y^2 = 1</math> <math>\frac{4}{(2a)^2}x^2 + \frac{4}{(2a)^2 - 4p^2}y^2 = 1</math> <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> <math></math> <math></math> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ==Second definition of ellipse== {{RoundBoxTop|theme=2}} [[File:0901ellipse00.png|thumb|400px|'''Graph of ellipse <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> where <math>a,b = 20,12</math>.''' </br> At point <math>B,\ \frac{u}{v} = e.</math> </br> At point <math>A,\ \frac{a}{t} = e.</math> ]] Ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant. Let <math>\frac{p}{a} = e</math> where: * <math>p</math> is non-zero, * <math>a > p,</math> * <math>a = p + u.</math> Therefore, <math>1 > e > 0.</math> Let directrix have equation <math>x = t</math> where <math>\frac{a}{t} = e.</math> At point <math>B:</math> <math>\frac{p}{p+u} = \frac{p+u}{p+u+v} = e</math> <math>(p+u)^2 = p(p+u+v)</math> <math>pp + pu + pu + uu = pp + pu + pv</math> <math>pu + uu = pv</math> <math>u(p + u) = pv</math> <math>\frac{u}{v} = \frac{p}{p+u} = e</math> <math>\frac{\text{distance to focus}}{\text{distance to directrix}} = e\ \dots\ (3)</math> Statement <math>(3)</math> is true at point <math>A</math> also. Section under "Proof" below proves that statement (3) is true for any point <math>P</math> on ellipse. {{RoundBoxBottom}} ===Proof=== {{RoundBoxTop|theme=2}} [[File:0902ellipse00.png|thumb|400px|'''Proving that <math>\frac{\text{distance from point to focus}}{\text{distance from point to directrix}} = e</math>.''' </br> Graph is part of curve <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1.</math> </br> distance to Directrix1 <math>= t - x = \frac{a}{e} - x = \frac{a - ex}{e}.</math> </br> base = <math>x - p = x - ae</math> </br> <math>\text{(distance to Focus1)}^2 = \text{base}^2 + y^2</math> ]] As expressed above in statement <math>3,</math> second definition of ellipse states that ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant. This section proves that this definition is true for any point <math>P</math> on the ellipse. At point <math>P:</math> <math>(a^2 - p^2)x^2 + a^2y^2 -a^2(a^2 - p^2) = 0</math> <math>y^2 = \frac{-(a^2 - p^2)x^2 + a^2(a^2 - p^2)}{a^2}</math> <math>= \frac{a^2e^2x^2 - a^2x^2 + a^2a^2 - a^2a^2e^2}{a^2}</math> <math>= e^2x^2 - x^2 + a^2 - a^2e^2</math> base <math>= x-p = x-ae</math> <math>(\text{distance}\ F_1P)^2 = y^2 + \text{base}^2 = y^2 + (x-ae)^2</math> <math>= a^2 - 2aex + e^2x^2</math> <math>= (a-ex)^2</math> <math>\text{distance to Focus1} = \text{distance}\ F_1P = a - ex</math> <math>\text{distance to Directrix1} = t - x = \frac{a}{e} - x = \frac{a-ex}{e}</math> <math>\frac{\text{distance to Focus1}}{\text{distance to Directrix1}}</math> <math>= (a - ex)\frac{e}{(a-ex)}</math> <math>= e</math> Similar calculations can be used to prove the case for Focus2 <math>(-p, 0)</math> and Directrix2 <math>(x = -t)</math> in which case: <math>\frac{\text{distance to Focus2}}{\text{distance to Directrix2}}</math> <math>= (a + ex)\frac{e}{(a + ex)}</math> <math>= e</math> Therefore: <math>\frac{\text{distance to focus}}{\text{distance to directrix}} = e</math> where <math>1 > e > 0.</math> Ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant, called eccentricity <math>e.</math> <math></math> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ==Heading== ===Properties of ellipse=== {{RoundBoxTop|theme=2}} [[File:0822ellipse01.png|thumb|400px|'''Graph of ellipse used to illustrate and calculate certain properties of ellipses.''' </br> </br> Traditional definition of ellipse: </br> <math>\text{distance } AF_1 + \text{distance } AF_2 = \text{constant } k.</math> </br> </br> Second definition of ellipse: </br> <math>\frac{\text{distance } AF_1} {\text{distance } AG } = \text{eccentricity } e.</math> </br> </br> Triangle <math>A F_1 G</math> is right triangle. </br> <math>e = \cos \angle O F_1 A = \cos \angle F_1 A G</math> ]] Ellipse in diagram has: * Two foci: <math>F_1\ (p,0),\ F_2\ (-p,0).</math> * Length of major axis <math>= \text{distance } I_2 I_1 = 2a</math> * Length of minor axis <math>= \text{distance } A B = 2b</math> * Equation: <math>\frac {x^2} {a^2} + \frac {y^2} {b^2} = 1</math> * Length of latus rectum <math>= \text{distance } P Q</math> * Distance between directrices <math>= \text{distance } D_2 D_1 = 2t</math> Properties of ellipse: * <math>\frac{\text{length of major axis}} {\text{distance between directrices}} = e</math> * <math>\frac{\text{distance between foci}} {\text{length of major axis}} = e</math> * <math>\frac{\text{distance between foci}} {\text{distance between directrices}}= e^2</math> * <math>(\frac{\text{length of minor axis}} {\text{length of major axis}})^2 + e^2 = 1</math> * <math>\frac{\text{length of latus rectum}} {\text{length of major axis}} + e^2 = 1</math> * line <math>PD_1</math> is tangent to curve at latus rectum, point <math>P.</math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ====Major axis==== From traditional definition of ellipse: Distance <math>AF_2\ +</math> distance <math>AF_1</math> = distance <math>I_1F_1\ +</math> distance <math>I_1F_2</math> = distance <math>I_2F_2\ +</math> distance <math>I_2F_1</math> = <math>k.</math> Therefore: Length of major axis = distance <math>I_2I_1 = 2a = k.</math> Distance <math>AF_1 = \frac{k}{2} = a.</math> From second definition of ellipse: <math>\frac{\text{distance }AF_1}{\text{distance }AG} = \frac{a}{t} = \text{eccentricity }e</math> <math>= \frac{\text{distance }OI_1}{\text{distance }OD_1}.</math> <math>\frac{\text{length of major axis}}{\text{distance between directrices}} = e.</math> ====Foci==== From second definition of ellipse: <math>\frac{\text{distance }I_1F_1}{\text{distance }I_1D_1} = \frac{a-p}{t-a} = e.</math> <math>a - p = te - ae</math> <math>a - p = a - ae</math> Therefore: <math>p = ae</math> or <math>\frac{p}{a} = e.</math> <math>\frac{\text{distance between foci}}{\text{length of major axis}} = e.</math> <math>\frac{\text{distance between foci}}{\text{distance between directrices}} = e^2.</math> ====Minor axis==== Triangle <math>AOF_1</math> is right triangle. <math>\cos ^2 \angle OAF_1 + \sin ^2 \angle OAF_1</math> <math>= (\frac{b}{a})^2 + (\frac{p}{a})^2 </math> <math>= (\frac{b}{a})^2 + (\frac{ae}{a})^2 </math> <math>= (\frac{b}{a})^2 + e^2 = 1</math> <math>( \frac{\text{length of minor axis}} {\text{length of major axis}} )^2 + e^2 = 1</math> Triangles <math>AOF_1,\ AF_1G</math> are similar. Triangle <math>AF_1G</math> is right triangle. <math>e = \cos \angle OF_1A = \cos \angle F_1AG.</math> ====Latus rectum==== From second definition of ellipse: <math>\frac{\text{distance }PF_1} {\text{distance }F_1D_1} = \frac{\text{distance }PF_1}{t-p} = e</math> <math>\text{distance }PF_1 = te - pe = a - (ae)e = a(1-e^2).</math> <math>\frac{\text{distance }PF_1} {a} = 1 - e^2.</math> <math> \frac{\text{length of latus rectum}} {\text{length of major axis}} + e^2 = 1</math> ====Slope of curve==== Curve has equation: <math>b^2x^2 + a^2y^2 = a^2b^2</math> Derivative of both sides: <math>b^22x + a^22yy' = 0</math> <math>y' = \frac{-xb^2}{ya^2}</math><math></math> <math>= \frac{-x(1-e^2)}{y}</math><math></math> At point <math>P:\ m_1 = y' = \frac{-p(1-e^2)}{-a(1-e^2)}</math> <math>= \frac{ae}{a} = e.</math><math></math> Slope of line <math>PD_1:\ m_2 = \frac{\text{distance }PF_1}{\text{distance }F_1D_1} = e.</math><math></math><math></math> <math>m_1 = m_2.</math> Therefore line <math>PD_1</math> is tangent to curve at latus rectum, point <math>P.</math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> ===Intercept form of equation=== <math>\frac{x^2}{20^2} + \frac{y^2}{12^2} = 1</math> <math></math> <math></math> {{RoundBoxTop|theme=2}} [[File:0625ellipse01.png|thumb|400px|'''Ellipse at origin with major axis on X axis.''' </br> </br> </br> </br> Equation of ellipse has format <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> where: </br> </br> <math>\text{Length of major axis} = 2a = \text{distance}\ I_2I_1 = 40</math> </br> <math>\text{Length of minor axis} = 2b = \text{distance}\ BA = 24</math> </br> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> </br> <math>\frac{\text{Length of minor axis}}{\text{Length of major axis}} = \sqrt{1 - e^2}</math> </br> </br> <math>e = \sqrt{1 - \frac{b^2}{a^2}} = 0.8.</math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> ]] In diagram: Intercept <math>I_1</math> has coordinates <math>(a,0).</math> Intercept <math>I_2</math> has coordinates <math>(-a,0).</math> Intercept <math>A</math> has coordinates <math>(0,b).</math> Intercept <math>B</math> has coordinates <math>(0,-b).</math> Focus <math>F_1</math> has coordinates <math>(f,0)</math> where <math>f = ea.</math> Focus <math>F_2</math> has coordinates <math>(-f,0).</math> Curve has equation <math>\frac{x^2}{20^2} + \frac{y^2}{12^2} = 1,</math> called intercept form of equation of ellipse because intercepts are apparent as the fractional value of each coefficient. Standard form of this equation is: <math>(-0.36)x^2 + (-1)y^2 + (0)xy + (0)x + (0)y + (144) = 0.</math> While the standard form is valuable as input to a computer program, the intercept form is still attractive to the human eye because center of ellipse and intercepts are neatly contained within the equation. Slope of curve: <math>b^2x^2 + a^2y^2 = a^2b^2</math> Derivative of both sides: <math>b^22x + a^22yy' = 0</math> <math>y' = \frac{-xb^2}{ya^2}</math> <math>= \frac{-x(1-e^2)}{y}</math> At point <math>P</math> on latus rectum <math>PQ:</math> <math>m_1 = y' = \frac{-(ea)(1-e^2)}{-(a(1-e^2))} = e</math> Slope of line <math>PD = m_2 = \frac{PF_1}{F_1D} = e</math> <math>m_1 = m_2.</math> Line <math>PD</math> is tangent to curve at latus rectum, point <math>P.</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ===Example=== {{RoundBoxTop|theme=2}} [[File:0618ellipse01.png|thumb|400px|'''Traditional definition of ellipse uses abc, epq.''' </br> M is mid-point between F1 and F2. </br> Point R is on minor axis. </br> </br> <math>\frac{\text{distance from R to F1}}{\text{distance from R to directrix 1}}</math> <math>= e</math> </br> </br> <math>= \frac{\text{half major axis}}{\text{distance from M to directrix 1}}</math> </br> </br> <math>\text{distance from M to directrix 1} = \frac{\text{half major axis}}{e}</math> </br> </br> <math>\text{F1:}\ (1, -7)</math> </br> <math>\text{F2:}\ (-1.24, 0.68)</math> </br> length_of_major_axis = 10 </br> <math>\text{M:}\ (-0.12, -3.16)</math> </br> length_of_minor_axis = 6 </br> <math>\text{R:}\ (2.76, -2.32)</math> </br> <math>e = 0.8</math> </br> <math>\text{D1:}\ (1.63, -9.16)</math> </br> <math>\text{Directrix 1:}\ (-0.28)x + (0.96)y + (9.25) = 0</math> </br> <math>\text{abc}\ =\ (-0.28,\ 0.96,\ 9.25)</math> </br> <math>\text{epq}\ =\ (0.8,\ 1,\ -7)</math> ]] Given: <syntaxhighlight lang=python> # python code F1 = 1, -7 # Focus 1 F2 = -1.24, 0.68 # Focus 2 length_of_major_axis = 10 </syntaxhighlight> Calculate equation of ellipse. <syntaxhighlight lang=python> F1 = p1,q1 = [ dD(str(v)) for v in F1 ] # Focus 1 F2 = p2,q2 = [ dD(str(v)) for v in F2 ] # Focus 2 length_of_major_axis = dD(length_of_major_axis) half_major_axis = length_of_major_axis / 2 # Direction cosines from F1 to F2 dx = p2-p1 ; dy = q2-q1 divider = (dx**2 + dy**2).sqrt() dx,dy = [ (v/divider) for v in (dx,dy) ] # F2 # p2 = p1 + dx*distance_F1_F2 # q2 = q1 + dy*distance_F1_F2 distance_F1_F2 = (q2-q1)/dy half_distance_F1_F2 = distance_F1_F2 / 2 # The mid-point M = xM,ym = p1 + dx*half_distance_F1_F2, q1 + dy*half_distance_F1_F2 # Eccentricity: e = distance_F1_F2 / length_of_major_axis # distance from point R to F1 half_major_axis # ------------------------------------ = e = ----------------------------------------- # distance from point R to Directrix 1 distance from point M to Directrix 1 distance_from_point_M_to_dx1 = half_major_axis / e # Intersection of axis and directrix 1 D1 = xM-dx*distance_from_point_M_to_dx1, yM-dy*distance_from_point_M_to_dx1 D1 = xD1, yD1 = [ reduce_Decimal_number(v) for v in D1 ] # Equation of Directrix 1 # dx1 = adx1,bdx1,cdx1 adx1,bdx1 = dx, dy # Perpendicular to axis. # adx1*x + bdx1*y + cdx1 = 0 # Directrix 1 contains point D1 cdx1 = reduce_Decimal_number( -( adx1*xD1 + bdx1*yD1 ) ) abc = adx1,bdx1,cdx1 epq = e,p1,q1 ABCDEF = ABCDEF_from_abc_epq (abc,epq, 1) </syntaxhighlight> Equation of ellipse in standard form: <math>(-0.949824)x^2 + (-0.410176)y^2 + (-0.344064)xy + (-1.3152)x + (-2.6336)y + (4.76) = 0</math> For more insight into method of calculation and proof: <syntaxhighlight lang=python> if 1 : print ('F1: ({}, {})'.format(p1,q1)) print ('F1: (x - ({}))^2 + (y - ({}))^2 = 1'.format(p1,q1)) print ('F2: ({}, {})'.format(p2,q2)) print ('F2: (x - ({}))^2 + (y - ({}))^2 = 1'.format(p2,q2)) print ('length_of_major_axis =', length_of_major_axis) print ('M: ({}, {})'.format(xM,yM)) print ('M: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xM,yM)) # half_minor_axis**2 + half_distance_F1_F2**2 = half_major_axis**2 half_minor_axis = (half_major_axis**2 - half_distance_F1_F2**2).sqrt() length_of_minor_axis = half_minor_axis * 2 s1 = 'length_of_minor_axis' ; print (s1, '=', eval(s1)) # Direction cosines on major axis: print ('dx,dy =', dx,dy) # Direction cosines on minor axis: dnx,dny = dy,-dx print ('dnx,dny =', dnx,dny) # One point on minor axis: R = xR,yR = xM + dnx*half_minor_axis, yM + dny*half_minor_axis print ('R: ({}, {})'.format(xR,yR)) print ('R: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xR,yR)) # Verify that point R is on ellipse: sum_zero((A*xR**2, B*yR**2, C*xR*yR, D*xR, E*yR, F)) and 1/0 s1 = 'e' ; print (s1, '=', eval(s1)) print ('D1: ({}, {})'.format(xD1,yD1)) print ('D1: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xD1,yD1)) print ('Directrix 1: ({})x + ({})y + ({}) = 0'.format(adx1, bdx1, cdx1)) print() # For proof, reverse the process: (abc1,epq1), (abc2,epq2) = calculate_abc_epq (ABCDEF) a1,b1,c1 = abc1 ; e1,p1,q1 = epq1 print ('Directrix 1: ({})x + ({})y + ({}) = 0'.format(a1, b1, c1)) print ('Eccentricity e1: {}'.format(e1)) print ('F1: ({}, {})'.format(p1,q1)) print() a2,b2,c2 = abc2 ; e2,p2,q2 = epq2 print ('Directrix 2: ({})x + ({})y + ({}) = 0'.format(a2, b2, c2)) print ('Eccentricity e2: {}'.format(e2)) print ('F2: ({}, {})'.format(p2,q2)) print ('\nEquation of ellipse with integer coefficients:') A,B,C,D,E,F = [ reduce_Decimal_number(-v*1000000/64) for v in ABCDEF ] str1 = '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0' print (str1.format(A,B,C,D,E,F)) </syntaxhighlight> <syntaxhighlight> F1: (1, -7) F1: (x - (1))^2 + (y - (-7))^2 = 1 F2: (-1.24, 0.68) F2: (x - (-1.24))^2 + (y - (0.68))^2 = 1 length_of_major_axis = 10 M: (-0.12, -3.16) M: (x - (-0.12))^2 + (y - (-3.16))^2 = 1 length_of_minor_axis = 6 dx,dy = -0.28 0.96 dnx,dny = 0.96 0.28 R: (2.76, -2.32) R: (x - (2.76))^2 + (y - (-2.32))^2 = 1 e = 0.8 D1: (1.63, -9.16) D1: (x - (1.63))^2 + (y - (-9.16))^2 = 1 Directrix 1: (-0.28)x + (0.96)y + (9.25) = 0 Directrix 1: (0.28)x + (-0.96)y + (-9.25) = 0 Eccentricity e1: 0.8 F1: (1, -7) Directrix 2: (0.28)x + (-0.96)y + (3.25) = 0 Eccentricity e2: 0.8 F2: (-1.24, 0.68) Equation of ellipse with integer coefficients: </syntaxhighlight> <math>(14841)x^2 + (6409)y^2 + (5376)xy + (20550)x + (41150)y + (-74375) = 0</math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} =allEqual= {{Robelbox|title=[[Wikiversity:Welcome|Welcome]]|theme={{{theme|9}}}}} <div style="padding-top:0.25em; padding-bottom:0.2em; padding-left:0.5em; padding-right:0.75em;"> [[Wikiversity:Welcome|Wikiversity]] is a [[Wikiversity:Sister projects|Wikimedia Foundation]] project devoted to [[learning resource]]s, [[learning projects]], and [[Portal:Research|research]] for use in all [[:Category:Resources by level|levels]], types, and styles of education from pre-school to university, including professional training and informal learning. We invite [[Wikiversity:Wikiversity teachers|teachers]], [[Wikiversity:Learning goals|students]], and [[Portal:Research|researchers]] to join us in creating [[open educational resources]] and collaborative [[Wikiversity:Learning community|learning communities]]. To learn more about Wikiversity, try a [[Help:Guides|guided tour]], learn about [[Wikiversity:Adding content|adding content]], or [[Wikiversity:Introduction|start editing now]]. </div> ====Welcomee==== {{Robelbox|title=[[Wikiversity:Welcome|Welcome]]|theme={{{theme|9}}}}} <div style="padding-top:0.25em; padding-bottom:0.2em; padding-left:0.5em; padding-right:0.75em; background-color: #FFF800; "> [[Wikiversity:Welcome|Wikiversity]] is a [[Wikiversity:Sister projects|Wikimedia Foundation]] project devoted to [[learning resource]]s, [[learning projects]], and [[Portal:Research|research]] for use in all [[:Category:Resources by level|levels]], types, and styles of education from pre-school to university, including professional training and informal learning. We invite [[Wikiversity:Wikiversity teachers|teachers]], [[Wikiversity:Learning goals|students]], and [[Portal:Research|researchers]] to join us in creating [[open educational resources]] and collaborative [[Wikiversity:Learning community|learning communities]]. To learn more about Wikiversity, try a [[Help:Guides|guided tour]], learn about [[Wikiversity:Adding content|adding content]], or [[Wikiversity:Introduction|start editing now]]. </div> =====Welcomen===== {{Robelbox|title=|theme={{{theme|9}}}}} <div style="padding-top:0.25em; padding-bottom:0.2em; padding-left:0.5em; padding-right:0.75em; background-color: #FFFFFF; "> [[Wikiversity:Welcome|Wikiversity]] is a [[Wikiversity:Sister projects|Wikimedia Foundation]] project devoted to [[learning resource]]s, [[learning projects]], and [[Portal:Research|research]] for use in all [[:Category:Resources by level|levels]], types, and styles of education from pre-school to university, including professional training and informal learning. We invite [[Wikiversity:Wikiversity teachers|teachers]], [[Wikiversity:Learning goals|students]], and [[Portal:Research|researchers]] to join us in creating [[open educational resources]] and collaborative [[Wikiversity:Learning community|learning communities]]. To learn more about Wikiversity, try a [[Help:Guides|guided tour]], learn about [[Wikiversity:Adding content|adding content]], or [[Wikiversity:Introduction|start editing now]]. </div> <syntaxhighlight lang=python> # python code. if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 : pass </syntaxhighlight> {{Robelbox/close}} {{Robelbox/close}} {{Robelbox/close}} <noinclude> [[Category: main page templates]] </noinclude> {| class="wikitable" |- ! <math>x</math> !! <math>x^2 - N</math> |- | <code></code><code>6</code> || <code>-221</code> |- | <code></code><code>7</code> || <code>-208</code> |- |- | <code>10</code> || <code>-157</code> |- | <code>11</code> || <code>-136</code> |- | <code>12</code> || <code>-113</code> |- | <code>13</code> || <code></code><code>-88</code> |- | <code>26</code> || <code></code><code>419</code> |} =Testing= ======table1====== {|style="border-left:solid 3px blue;border-right:solid 3px blue;border-top:solid 3px blue;border-bottom:solid 3px blue;" align="center" | Hello As <math>abs(x)</math> increases, the value of <math>f(x)</math> is dominated by the term <math>-ax^3.</math> When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large positive value, <math>f(x)</math> is always negative. <syntaxhighlight> 1.4142135623730950488016887242096980785696718753769480731766797379907324784621070388503875343276415727 3501384623091229702492483605585073721264412149709993583141322266592750559275579995050115278206057147 0109559971605970274534596862014728517418640889198609552329230484308714321450839762603627995251407989 </syntaxhighlight> |} {{RoundBoxTop|theme=2}} [[File:0410cubic01.png|thumb|400px|''' Graph of cubic function with coefficient a negative.''' </br> There is no absolute maximum or absolute minimum. ]] Coefficient <math>a</math> may be negative as shown in diagram. As <math>abs(x)</math> increases, the value of <math>f(x)</math> is dominated by the term <math>-ax^3.</math> When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large positive value, <math>f(x)</math> is always negative. Unless stated otherwise, any reference to "cubic function" on this page will assume coefficient <math>a</math> positive. {{RoundBoxBottom}} <math>x_{poi} = -1</math> <math></math> <math></math> <math></math> <math></math> =====Various planes in 3 dimensions===== {{RoundBoxTop|theme=2}} <gallery> File:0713x=4.png|<small>plane x=4.</small> File:0713y=3.png|<small>plane y=3.</small> File:0713z=-2.png|<small>plane z=-2.</small> </gallery> {{RoundBoxBottom}} <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> 1.4142135623730950488016887242096980785696718753769480731766797379907324784621070388503875343276415727 3501384623091229702492483605585073721264412149709993583141322266592750559275579995050115278206057147 0109559971605970274534596862014728517418640889198609552329230484308714321450839762603627995251407989 6872533965463318088296406206152583523950547457502877599617298355752203375318570113543746034084988471 6038689997069900481503054402779031645424782306849293691862158057846311159666871301301561856898723723 5288509264861249497715421833420428568606014682472077143585487415565706967765372022648544701585880162 0758474922657226002085584466521458398893944370926591800311388246468157082630100594858704003186480342 1948972782906410450726368813137398552561173220402450912277002269411275736272804957381089675040183698 6836845072579936472906076299694138047565482372899718032680247442062926912485905218100445984215059112 0249441341728531478105803603371077309182869314710171111683916581726889419758716582152128229518488472 </syntaxhighlight> <math>\theta_1</math> {{RoundBoxTop|theme=2}} [[File:0422xx_x_2.png|thumb|400px|''' Figure 1: Diagram illustrating relationship between <math>f(x) = x^2 - x - 2</math> and <math>f'(x) = 2x - 1.</math>''' </br> ]] {{RoundBoxBottom}} <math>O\ (0,0,0)</math> <math>M\ (A_1,B_1,C_1)</math> <math>N\ (A_2,B_2,C_2)</math> <math>\theta</math> <math>\ \ \ \ \ \ \ \ </math> :<math>\begin{align} (6) - (7),\ 4Apq + 2Bq =&\ 0\\ 2Ap + B =&\ 0\\ 2Ap =&\ - B\\ \\ p =&\ \frac{-B}{2A}\ \dots\ (8) \end{align}</math> <math>\ \ \ \ \ \ \ \ </math> :<math>\begin{align} 1.&4141475869yugh\\ &2645er3423231sgdtrf\\ &dhcgfyrt45erwesd \end{align}</math> <math>\ \ \ \ \ \ \ \ </math> :<math> 4\sin 18^\circ = \sqrt{2(3 - \sqrt 5)} = \sqrt 5 - 1 </math> nk73re2mr1jts5yap02mh4tb7jcgpjo 0 235131 2835224 2832079 2026-09-30T20:12:08Z The Citer 3110681 /* Ctenophora */ 2835224 wikitext text/x-wiki [[Image:Animalia diversity.jpg|thumb|300px|right|Some examples of animal diversity.]] A Phylum (pl. Phyla) is the largest formal major grouping within animal taxonomy. This list is presented in alphabetical order, and not in any systematic/evolutionary arrangement. This list is also available in [[/Table/|table form]]. Science is by no means static. There are arguments of all sizes and shapes about the taxonomy of the Animal Phyla. Other sources may combine or split these listed Phyla. However, at this time, the list presented here should stand in good stead for an introduction to the topic of animal diversity. There are approximately 1.9 million animal species that have been described by science. This list tries to give the following information on each Phylum: *Phyllum Name *A link to a sub-page discussing that Phylum in more detail (if it yet exists) *Name Meaning (in English) *An English Common Name, where one is in regular use *Distinguishing characteristics of animals within the Phylum *An approximate number of species described within that Phylum. Since zoology fortunately refuses to stand still, this number can change. Oh! And there's a quiz at the end. See also [[/Lesson Plan for Animal Phyla/]]. Or head to [[Introduction to Taxonomy]] for more on that topic. You can also visit [[Plant Divisions (Phyla)]], the equivalent page for plants. ==Acanthocephalae== [[Image:Macracanthorhynchus_hirudinaceus_adult_BAM1.jpg|thumb|100px|left|An Acanthocephalan, ''Macracanthorhynchus hirudinaceus'', adult.]] [[/Acanthocephala/]] Name Meaning: horny head English Common Name: Horny-headed worms Major distinguishing characteristics: Reversible spiny proboscis Approximate number of species described: 1,151 ==Acoelomorpha== [[File:Acoelomorpha.jpg|thumb|100px|left|Acoelomorpha]] [[/Acoelomorpha/]] Name Meaning: Without gut English Common Name: Acoels Major distinguishing characteristics: No mouth or alimentary canal Approximate number of species described: 50,000 == Annelida == <div id="Annelida"></div> [[Image:Reef0200.jpg|thumb|100px|left|An feather duster worm of the family Sabellidae in parchment tube.]] [[/Annelida/]] Name Meaning: Little ring English Common Name: Segmented worms, annelids Major distinguishing characteristics: Multiple circular segments Approximate number of species described: 22,000 modern ==Arthropoda== [[Image:Chelicerae_%26_pedipalps_%288689230685%29.jpg|thumb|100px|left|A scorpion, an example of an Arthropod]] [[/Arthropoda/]] Name Meaning: Jointed foot English Common Name: Arthropods Major distinguishing characteristics: Chitin exoskeleton Approximate number of species described: 1,134,000+ ==Brachiopoda== [[Image:Isocrania_costata_Sowerby_1823.jpg|thumb|100px|left|Brachiopod ''Isocrania costata''.]] [[/Brachiopoda/]] Name Meaning: Arm foot English Common Name: Lamp shells, brachiopod Major distinguishing characteristics: Lophophore and pedicle Approximate number of species described: between 300 and 500 extant ==Bryozoa== [[Image:Freshwater_Bryozoan234.JPG|thumb|100px|left|A freshwater Bryozoan, species unknown.]] [[/Bryozoa/]] Name Meaning: Moss animals English Common Name: Moss animals, sea mats, bryozoans Major distinguishing characteristics: Lophophore, no pedicle, ciliated tentacles Approximate number of species described: about 5,000 living species ==Chaetognatha== [[Image:Chaetognatha.PNG|thumb|100px|left|Chaetognathans.]] [[/Chaetognatha/]] Name Meaning: Longhair jaw English Common Name: Arrow worms Major distinguishing characteristics: Chitinous spines either side of head, fins Approximate number of species described: about 100 modern species ==Chordata== [[Image:Clavelina lepadiformis (Müller, 1776) - Banyuls-sur-Mer - 04.83.jpg|thumb|100px|left|''Clavelina lepadiformis'', a non-vertebrate chordates.]] [[/Chordata/]] Name Meaning: Cord English Common Name: Chordates Major distinguishing characteristics: Hollow dorsal nervous chord Approximate number of species described: about 100,000+ ==Cnidaria== [[Image:Cynarina_lacrymalis.jpeg|thumb|100px|left|''Cynarina lacrymalis'' an anthozoan member of the Phylum Cnidaria.]] [[/Cnidaria/]] Name Meaning: Stinging nettle English Common Name: Coelenterates, cnidarians, sea anemones, jellies, hydra Major distinguishing characteristics: Cnidocytes (stinging cells) Approximate number of species described: about 11,000 ==Ctenophora== [[Image:LightRefractsOf comb-rows of ctenophore Mertensia ovum.jpg|thumb|100px|left|''Mertensia'', a Ctenophore.]] [[/Ctenophora/]] Name Meaning: Comb bearer English Common Name: Comb jellies, Ctenophores Major distinguishing characteristics: Eight "comb rows" of fused cilia Approximate number of species described: about 200 modern species ==Cycliophora== [[Image:Cycliophora - Symbion pandora.png|thumb|100px|left|''Symbion pandora'', a Cycliphoran.]] [[/Cycliophora/]] Name Meaning: Wheel carrying English Common Name: Symbion Major distinguishing characteristics: Circular mouth surrounded by small cilia Approximate number of species described: at least 3 ==Echinodermata== [[Image:Crinoideos.jpg|thumb|100px|left|''Crinoideos'', an example of Ecinoderms.]] [[/Echinodermata/]] Name Meaning: Spiny skin(Body) English Common Name: Echinoderms Major distinguishing characteristics: Five-fold radial symmetry, mesodermal layer, calcified spines Approximate number of species described: about 7,000 living species and 13,000 extinct ones ==Entoprocta== [[Image:Barentsa discreta suzukokemusi01.JPG|thumb|100px|left|''Barentsa discreta suzukokemusi'', a species of goblet worm.]] [[/Entoprocta/]] Name Meaning: Inside anus English Common Name: Goblet worm Major distinguishing characteristics: Anus inside ring of cilia Approximate number of species described: about 150 ==Gastrotricha== [[Image:Chaetonotus (Chaetonotus) polyspinosus.jpg|thumb|100px|left|''Chaetonotus polyspinosus'' a species of meiofauna.]] [[/Gastrotricha/]] Name Meaning: Hair stomach English Common Name: Hairybellies, hairybacks Major Distinguishing Characteristics: Two terminal adhesive tubes Approximate number of species described: about 690 ==Gnathostomulida== [[Image:Gnathostomula paradoxa Sylt.tif|thumb|100px|left|''Gnathostomula paradoxa'', a jaw worm.]] [[/Gnathostomulida/]] Name Meaning: Jaw orifice English Common Name: Jaw worms Major distinguishing characteristics: Approximate number of species described: about 100 ==Hemichordata== [[Image:Glossograptus whitfieldii 01.jpg|thumb|100px|left|Glossograptus whitfieldii, a fossil hemichordate.]] [[/Hemichordata/]] Name Meaning: Half cord English Common Name: Acorn worms Major distinguishing characteristics: Stomochord in collar Approximate number of species described: about 100 living species ==Kinorhyncha== [[Image:Paracentrophyes quadridentatus.jpg|thumb|100px|left|''Paracentrophyes quadridentatus'', a mud dragon.]] [[/Kinorhyncha/]] Name Meaning: Motion snout English Common Name: Mud dragons Major distinguishing characteristics: Eleven segments, each with a dorsal plate Approximate number of species described: about 150 ==Loricifera== [[Image:Pliciloricus enigmatus.jpg|thumb|100px|left|A member of the Phylum Loricifera, ''Pliciloricus enigmatus''.]] [[/Loricifera/]] Name Meaning: Corset bearer English Common Name: Loriciferans Major distinguishing characteristics: Umbrella-like scales at each end Approximate number of species described: about 122 ==Micrognathozoa== [[Image:Limnonathia, drawing.tif|thumb|100px|left|''Limnonathia'', drawing, a Micrognathozoan.]] [[/Micrognathozoa/]] (sometimes called Phylum Gnathifera) Name Meaning: Tiny jaw animals English Common Name: Micrognathozoans Major distinguishing characteristics: Accordion like extensible thorax Approximate number of species described: 1 ==Mollusca== [[Image:Shells01.jpg|thumb|100px|left|A group of Gastropod shells, Phylum Mollusca.]] [[/Mollusca/]] Name Meaning: Thin shell English Common Name: Mollusks or molluscs Major distinguishing characteristics: Muscular foot and Mantle, round shell Approximate number of species described: 85,000 ==Nematoda== [[Image:Mermis nigrescens beentree.jpg|thumb|100px|left|''Mermis nigrescens beentree'', a nematode worm.]] [[/Nematoda/]] Name Meaning: Thread like English Common Name: Round worms, Nematodes Major distinguishing characteristics: Round cross section, keratin, cuticle Approximate number of species described: 80 000 - 1 million ==Nematomorpha== [[Image:Gordiidae A MRKVICKA.JPG|thumb|100px|left|A Gordian worm, Phylum Nematomorpha.]] [[/Nematomorpha/]] Name Meaning: Thread form English Common Name: Horsehair worms Major distinguishing characteristics: Approximate number of species described: about 320 ==Nemertea== [[Image:Micrura alaskensis.png|thumb|100px|left|Micrura alaskensis, a ribbon worm.]] [[/Nemertea/]] Name Meaning: A sea nymph English Common Name: Ribbon worms Major distinguishing characteristics: Approximate number of species described: about 1200 ==Onychophora== [[Image:Euperipatoides kanangrensis crop.jpg|thumb|100px|left|''Euperipatoides kanangrensis'', a velvet worm.]] [[/Onychophora/]] Name Meaning: Claw bearer English Common Name: Velvet worms Major distinguishing characteristics: Legs tipped by chitinous claws Approximate number of species described: about 200 modern ==Orthonectida== <div id="Orthonectida"></div> [[Image:Orthonetida dict flat and cylinder.png|thumb|100px|left|Orthonetida, an Orthonectidan.]] [[/Orthonectida/]] Name Meaning: Straight swim English Common Name: Orthonectida Major distinguishing characteristics: Approximate number of species described: about 20 ==Phoronida== [[Image:Phoronis Maria Grazia Montanucci2.jpg|thumb|100px|left|'' Phoronis hippocrepis'', a species of horseshoe worm.]] [[/Phoronida/]] Name Meaning: Zeus' mistress English Common Name: Horseshoe worms Major distinguishing characteristics: U-shaped gut Approximate number of species described: 20 ==Placozoa== [[Image:Trichoplax adhaerens photograph.png|thumb|100px|left|''Trichoplax adhaerens'', the only Placozoan.]] [[/Placozoa/]] Name Meaning: Plate animals English Common Name: none Major distinguishing characteristics: Approximate number of species described: 1 ==Platyhelminthes== [[Image:Gigantolina.elongata.in.vivo.png|thumb|100px|left|''Gigantolina elongata'', a flat worm.]] [[/Platyhelminthes/]] Name Meaning: Flat worms English Common Name: Flat worms Major distinguishing characteristics: Approximate number of species described: about 25,000 ==Porifera== [[Image:Eponge à déterminer (1).jpg|thumb|100px|left|An unidentified sponge.]] [[/Porifera/]] Name Meaning: Pore bearer English Common Name: Sponges Major distinguishing characteristics: Perforated interior wall Approximate number of species described: over 5,000 modern ==Priapulida== [[Image:Adult priapulid.jpg|thumb|100px|left|''Priapulus caudatus'', a Priapulid worm.]] [[/Priapulida/]] Name Meaning: Penis English Common Name: Priapulid worms Major distinguishing characteristics: Retractable proboscis surrounded by papillae Approximate number of species described: 17 ==Rhombozoa== <div id="Rhombozoa"></div> [[Image:Dicyema japonicum.png |thumb|100px|left|''Dicyema japonicum'', a rhombozoan.]] [[/Rhombozoa/]] Name Meaning: Rhombus animal English Common Name: Rhombozoans Major distinguishing characteristics: Single axial cell surrounded by ciliated cells Approximate number of species described: 75 ==Rotifera== [[Image:20090730 020239 Rotifer.jpg|thumb|100px|left|An unidentified rotifer.]] [[/Rotifera/]] Name Meaning: Wheel bearer English Common Name: Rotifers Major distinguishing characteristics: Anterior crown of cilia Approximate number of species described: about 2000 ==Tardigrada== [[Image:SEM image of Milnesium tardigradum in active state - journal.pone.0045682.g001-2.png|thumb|100px|left|Tardigrade ''Milnesium tardigradum'' in active state.]] [[/Tardigrada/]] Name Meaning: Slow step English Common Name: Water bears Major distinguishing characteristics: Four segmented body and head Approximate number of species described: 1,000+ ==Xenacoelomorpha== [[Image:Xenoturbella bockii longitudinal section.svg|thumb|100px|left|''Xenoturbella bockii'' longitudinal section.]] [[Xenacoelomorpha]] Name Meaning: Strange hollow form English Common Name: none Major distinguishing characteristics: Ciliated deuterostome Approximate number of species described: 435 ==Quizzes== * [[/Quiz/|Animal Phyla Quiz]] ==References== {{reflist}} *Brusca, Richard C., Wendy Moore, Stephen M. Shuster. Invertebrate Zoology 3rd ed. 2016. Sinauer. 1104 pp. *[https://en.wikipedia.org/wiki/Phylum Phylum] on Wikipedia [[Category:Lists]] [[Category:Taxonomy]] [[Category:Zoology]] [[Category:Animals]] {{science}} {{biology}} h29508tusteow03nm8zi85y14o593yo 0 235224 2835266 2388725 2026-10-01T03:31:23Z ~2026-52982-32 3111917 Wikipedia gives 4 species 2835266 wikitext text/x-wiki [[Image:Trichoplax adhaerens photograph.png|thumb|300px|right|''Trichoplax adhaerens'', a species within the Phylum Placozoa.]] *Placozoa *Name Meaning: Plate animals *English Common Name: none *Major distinguishing characteristics: *Approximate number of species described: 4 ==Natural History== ==Taxonomy== ==Anatomy== ==The Fossil Record== ==Quiz== * [[/Placozoa Quiz/]] ==References== *[https://en.wikipedia.org/wiki/Placozoa Placozoa] at Wikipedia *[http://tolweb.org/Placozoa Placozoa] at Tree of Life *[http://eol.org/pages/8773/overview Placozoa] at Encyclopedia of Life {{Animalia}} [[Category:Animals]] [[Category:Biology]] [[Category:Taxonomy]] [[Category:Zoology]] ml7c965n6ozwbb7k2occ0vi0re44bf2 0 264277 2835231 2834268 2026-09-30T22:19:29Z Scogdill 1331941 /* 1890 January 29, Wednesday */ 2835231 wikitext text/x-wiki [[Social Victorians/Timeline/1840s|1840s]] [[Social Victorians/Timeline/1850s |1850s]] [[Social Victorians/Timeline/1860s | 1860s]] [[Social Victorians/Timeline/1870s | 1870s]] [[Social Victorians/Timeline/1880s | 1880s Headlines]] [[Social Victorians/Timeline/1890s | 1890s Headlines]] 1890 [[Social Victorians/Timeline/1891 | 1891]] [[Social Victorians/Timeline/1892 | 1892]] [[Social Victorians/Timeline/1893 | 1893]] [[Social Victorians/Timeline/1894 | 1894]] [[Social Victorians/Timeline/1895 | 1895]] [[Social Victorians/Timeline/1896 | 1896]] [[Social Victorians/Timeline/1897 | 1897]] [[Social Victorians/Timeline/1898 | 1898]] [[Social Victorians/Timeline/1899 | 1899]] [[Social Victorians/Timeline/1900s|1900s]] [[Social Victorians/Timeline/1910s|1910s]] [[Social Victorians/Timeline/1920s-30s|1920s-30s]] ==January 1890== Sometime in January 1890, [[Social Victorians/People/Horniman|Annie Horniman]] was initiated into the Golden Dawn (Gilbert 86 144). Sometime in 1890 Annie Besant and [[Social Victorians/People/Helena Blavatsky|Helena Blavatsky]] founded the Working Women's Club in the East End (Besant Chronology.pdf). Maye Dilke was a member (Crawford 170). [[Social Victorians/People/Frank Harris|Frank Harris]] says,<blockquote>One day in 1890 I had George Meredith, Walter Pater and [[Social Victorians/People/Oscar Wilde|Oscar Wilde]] dining with me in Park Lane and the time of sex-awakening was discussed. Both Pater and Wilde spoke of it as a sign of puberty. Pater thought it began about thirteen or fourteen and Wilde to my amazement set it as late as sixteen. Meredith alone was inclined to put it earlier.<ref>Harris, Frank. ''My Life and Loves''.</ref></blockquote> ===1 January 1890, Wednesday, New Year's Day=== <blockquote>Sharp frost was experienced over the East of England yesterday morning, and in South London the thermometer had been as low as 27deg., and 28deg. in Hyde-park. It rose during the day to 41deg., but in the evening frost again set in. Later the thermometer rose again to 32deg., and there was an appearance as of coming rain.<ref><cite>The Morning Post. 1 January 1890 (No. 36,675): P. 4, Col. F.</cite></ref></blockquote>Influenza is spreading all over Europe. According to the "Court Circular: Orders for Court Mourning" in the Morning Post,<blockquote>A second supplement to the Gazette, issued last night, contains the following: — "Lord Chamberlain's Office, January 1. "Orders for the Court's going into mourning on Thursday next, the 2d instant, for her late Majesty the Empress of Brazil, viz." — "The ladies to wear black dresses, white gloves, black or white shoes, feathers, and fans, pearls, diamonds, or plain gold or silver ornaments. The gentlemen to wear black Court dress, with black swords and buckles. "The Court to change the mourning on Thursday, the 16th instant, viz.: — [new paragraph] The ladies to wear black dresses, with coloured ribbons, flowers, feathers, and ornaments, or grey or white dresses, with black ribbons, flowers, feathers, and ornaments. The gentlemen to continue the same mourning. "And on Thursday, the 23d instant, the Court to go out of mourning."<ref><cite>"Court Circular: Orders for Court Mourning." The Morning Post, 2 January 1890 (No. 36,676): page 5 Col. G.</cite></ref></blockquote> ===9 January 1890, Thursday=== ==== The York Hunt Ball ==== This account is from the ''Irish Society'', which explains which women's costumes are the focus:<blockquote>The fashionable world and his wife are out of town just now, having good times at country houses. They shed the light of their brilliant presence on those annual functions known as county balls, and enjoy themselves also at those popular and picturesque entertainments to which they are bidden by the masters and members of the various hunts. One of the smartest dances of last week took place at York on Thursday evening. It was in fancy costume, and was in aid of funds for the York County Hospital. Once upon a time the journey from London to the Minster City of the North was a far cry, and one not lightly undertaken. Now it is luxurious and short. In consequence this hall presented the appearance of one in town in mid-season. There was conspicuous for height and handsomeness the familiar figure and face of Countess de Grey. Lady Helen Duncombe, too, who shares with her Grace of Leinster, and Lady Cynthia Graham, the family beauty of the House of Feversham, was seen in the marvellously becoming (to her) costume of the Empire period. Lady Lilian Wemyss, a lady "divinely tall,” and appropriately fair, was garbed in pink and white of a fashion hailing from the Empire. A "square;” in which the lady dancers were all gowned empirically, was the event of the evening. An event worth remembering it was. The costumes were superb, but their attractions were nowhere in comparison with the charms the [Col. 1c–2a] wearers. These were all tall and each one handsome. Lady de Trafford’s pretty face and fine figure showed to great advantage in her gown of white satin, veiled with gold-bordered ''chiffon'', and with an Empire trained cloak from her shoulders of Rose du Barri velvet lined with white satin, and bordered with gold galon. The colour of the velvet in what is seen in the half-yellow, half-scarlet petals of the soft textured nasturtium bloom. [[Social Victorians/People/Bourke|Mrs Algernon Bourke]] looked a picture in a Gainsborough gown. The white satin skirt was flounced with sable and veiled with ''chiffon'', the setuage of which was left to show without being hemmed up. There was a broad sash of rose-pink silk and each buttonhole was filled round with crimped lisse. One might go on for long enough describing costume after costume, and then leave them half out. Therefore, we shall, like the judge "sum up” and "charge” for a verdict of the utmost brilliancy.<ref>"Our London Letter." ''Irish Society'' (Dublin) 11 January 1890, Saturday: 17 [of 24], Col. 1b–2a [of 3]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.co.uk/viewer/bl/0001939/18900111/042/0017. Same print title, p. 29.</ref></blockquote> ===16 January 1890, Thursday=== <blockquote>About two hundred members of the newly formed Dulwich Literary and Scientific Association attended the conversazione given on Jan. 16 at Surrey House Museum, Forest Hill, when Mr. Horniman, F.R.G.S., acted as cicerone round the rooms, richly stored with historical relics, ornithological curiosities, and art treasures.<ref>''Illustrated London News'' (London, England), Saturday, January 25, 1890; pg. 120; Issue 2649, Col. 3.</ref></blockquote> === 1890 January 29, Wednesday === [[Social Victorians/Santurce Murrieta Wedding 1890-01-29|Santurce Murrieta Wedding 1890-01-29]] ==February 1890== === 1890 February 6, Thursday === Before 6 February but not long before. The prize-fighter Pete Jackson fought a match at the New Pelican Club.<blockquote>It is always well to hear that distinguished visitors have enjoyed the hospitality which we have extended to them. This satisfaction is afforded us in full measure by the eminent "Parson" Davis, manager of Pete Jackson, the prize-fighter, who has just been regaling an American interviewer with an account of his experiences in England :— He had been treated in splendid style, and Jackson was received well everywhere. Nothing would give him greater pleasure than to revisit England, and he hoped soon to do so. "I shook a paw with the Prince,” said the parson. "We had a high old time with Albert E. His Royal Highness was exceptionally friendly with Jackson, and actually made a pump handle of his arm. He shook hands with him again and again. The Prince is in capital  health, and" —— But at this point the interviewer mysteriously breaks off. The Prince, however, was not the only British notable to whom Parson Davis referred. He explained that the cause of the trouble with Smith at the New Pelican Club was that the gloves furnished Jackson were too small in the fingers, and when he closed his hand he almost split them, and could not fight. The matter was explained to the officers of the Club, where the fight took place, and other gloves were procured for Jackson :— Fair play was given, and the audience, which included [[Social Victorians/People/Mandeville|Lords Mandeville]] and Lonsdale, were loud in their admiration of Jackson's skill.<ref>"The Tittle Tattle of the Week." ''Pall Mall Budget'' 6 February 1890, Thursday: 4 [of 36], Col. 1b [of 2]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0005967%2F18900206&page=4. Same print title, p. 162.</ref></blockquote> === 1890 February 8, Saturday === Recent arrivals in Brighton are listed:<blockquote>Though a good many people have left Brighton, still fresh visitors arrive, and the front is crowded when the weather is a little kind. Amongst the most recent arrivals may be mentioned the Countess of Strafford, Lady Susan Byng, Lady Chelmsford, Lord and Lady Seaton, Lady Jane Grimston, [[Social Victorians/People/Mandeville|Lord Mandeville]], Lord Romilly and the Hon. John Romilly, Viscount and Viscountess Hampden, the Hon. R. Somerset, the Hon.  Thomas Dundas, the Hon. Sidney Greville, the Hon. A. W. Verney Cave, Lady Elizabeth Cartwright, Colonel Sir Alfred and Lady Kirby, Mr. Bazley White, M.P., and Lady Bazley White, Sir Hugh Montgomery, Sir Frederick and Lady Perkins, Lady Ellis, General Seymour, &c., &c.<ref>Dorothy. "Brighton Notes." ''Lady's Pictorial'' 8 February 1890, Saturday: 51 [of 60], Col. 3a [of 3]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0005980%2F18900208&page=51&article=671&stringtohighlight=mandeville+viscount. Same print title, p. 203.</ref></blockquote> === 12 February 1890, Wednesday === ==== Lady Constance Leslie's Reception ==== <blockquote>On Wednesday last Lady Constance Leslie had an evening party at her residence in Stratford-place. The numerous guests included Prince Ernest of Hohenlohe, Princess Victor of Hohenlohe, and the Countesses Gleichen, the Austro-Hungarian Ambassador, Count Mensdorf, Count and Countess Henry Lützow, Mr. and Mrs. Henry White, Baroness de Brienen and Mdlles de Brienen, the Duke of Abercorn, the Duchess of Cleveland, the Marchioness of Blandford and Lady Frances Spencer Churchill, Earl and Countess of Portarlington, Earl Stanhope, the Earl of Northbrook, the Earl and Countess of Arran, the Earl and Countess of Erne and the Ladies Cole, Julia Countess of Jersey and Mr. Brandling, Viscount Clifden, Viscountess Bary, Viscount Torrington, Viscount and Viscountess Castlerosse and Lady Louisa Beauclerk, Viscount and Viscountess de Vesci and Lady Sarah Spencer, Viscountess Galway, and Mr Caryl Ramsden, Lord de L'Isle and Dudley, Lord Alcester, Lord and Lady Wantage, Lord Ashbourne, Lady Henry Grosvenor and Lady G. Ogilvy, Lady Cloncurry, Lord Morris and Mr. M. Morris, Lady Charles Beresford, Lord Rowton, Lady Blanche Hozier, Lady Colville, Lady Rayleigh, Lady Constance Lytton and Mr. Charles Earle, Lady Evelyn Sutton, Lady Ernest Seymour and Ladies Fortescue, Lord and Lady Sandhurst, Lady Mary Lloyd, Lady Tweedmouth, Lady Windsor, Lord and Lady William Seymour, Lady Guy Campbell, Lady Egerton, Lady Fitzgerald, Baron d'Erlanger and Mr. Charles Derenberg, Hon. R. C. Spencer, M.P., and Mrs. Spencer, Hon. Evelyn Ashley, Hon. W. Mansfield, Hon. Lionel Ashley, Hon. A. Hood, Hon. William Lowther and Miss Lowther, Hon. Sydney Greville, Hon. Fitzroy and Mrs. Stewart, Hon. Frederick Leveson Gower, Hon. Kenneth Howard, Hon. Francis Villiers, Hon. Francis Bertie, Hon. Arthur Walsh, Colonel the Hon. Charles Edgcumbe, General Hon. John Bourke, General and Hon. Mrs. Ellis and Mrs. R. Sneyd and Miss Ellis, [[Social Victorians/People/Bourke|Hon. Algernon and Mrs. Bourke]], Hon. Alan and Hon. Evan Charteris, Hon. Alexander Yorke, Hon. Derek Keppel, General Sir Dighton Probyn, Hon. Percy Wyndham, Hon. Everard Baring and Hon. Susan Baring, Hon. Mrs. Brett, Hon. Claud Hay, the Right Hon. Henry Matthews, Sir George Arthur, Sir George Maude, Sir Philip Currie, C.B., Sir Redvers and Lady Audrey Buller, Sir Charles Grant, Sir Mackenzie Wallace, Sir Herbert Maxwell, M.P., Sir Oscar Clayton, Sir Robert Gresley, Sir Algernon West and Mr. Horace West, Sir George and Lady Russell and Miss Brackenbury, Sir Henry and Lady Longley, the Sub-Dean of the Chapels Royal, General Crealock, General Charles Fraser, Colonel Saunderson, M.P., and Hon. Mrs. Saunderson, Colonel and Mrs. Stewart and Miss Streatfeild [siv], Colonel and Miss Balfour, Colonel and Mrs. Stanley Clarke and Miss Clarke, Colonel R. Baring, Captain and Mrs. Jekyll, Captain and Mrs. J. Bagot, Captain Lambert Ward, Captain A. Bagot, Mr. Charles Hall, Q.C, M.P., Mr[.] Hussey Walsh, M.P., Mr and Mrs. W. Hartpole Lecky, Mr. and Mrs. Richard Combe, Mr Henry Foley, Mrs. Arbuthnot and Miss Guthrie, Mr. and Mrs. Heseltine and Miss Dorothy Heseltine and Lord Cantelupe, the Miss Stopford Brooke, Mr. and Mrs. Thackeray Ritchie, Mr Edmund Byng, Mr. and Mrs. Wilton Phipps, Professor Sidney Colvin, Mr. and Miss Tennant, Mr. Godfrey Webb, Mr. and Mrs. Turton and Mr. Sidney Ponsonby, Mrs. Adare, Mrs Cecil Paget and Mr. Hugo Wemyss, Mrs. L. Drummond, Mr. and Mrs E. Hope, Mrs. L. Seymour and Miss Seymour, Mr. Guy Repton, Mr. and Mrs. Julian Sturgis and Miss Beresford, Mr. Poynter, R.A., Mrs. Daniel Cooper, Mr. Hamilton Aïdé, Mr. Alwyne Maude, Mrs. C. Bentinck, Mrs. Bingham Mildmay, Mr. Philip Habord, Mr. and Mrs. George Bulteel, Mrs. Beerbohm Tree and Miss Julia Neilson, Mr. Hallé [Halle?], Mr. Rudolph Lehmann and Miss Lehmann, [[Social Victorians/People/Fanny Ronalds|Mr. R. Ronalds]], Mr. Ellice, Mr. Arthur, Madame Blumenthal, Miss Julia Leslie, Mr. and Mrs. Jeune, Mr and Mrs. Charles Stuart-Wortley and Misses Millais, Mrs. Arkwright, Mr Joachim, Mr. Gillett, Mr. Pulteney (Scots Guards), Colone| Cuthbert Larking, Mr. Harry Higgins, M. Tividar Nachez, Mr. G. Ross, Herr Johannes Woolff, Mrs. Charles Bagot and Miss Bagot, Mrs. Bischoffsheim, Mr. Henry Petre, Miss Balch, Mr. and Lady Maud Ramsden, Mr. Adolphus Liddell, Mr Knowles, Mr. Grenfell, Mr. Edward Hamilton, Mrs. Henry Gordon and Miss Gordon, Mr. Henry James, Mr. St. Leger, Mrs. Dacre Hamilton and the Misses Nugent, Mr. Harbord, Mr Somerset, Mr. Ruggles-Brise, Mr. and Miss Hughes of Kinmel, Mr. and Mrs Douglas Freshfield, Mrs. Homer, Mr. W. H. Mallock, Mr. and Mrs. Robert Benson, Mr. H. Seymour, Mr. Ernest Law, Mr. Hugh Grimston, Mr. Lionel Cust, Mr. Chappell, Mr. and Mrs. Du Maurier, Mr. Boughton, R.A., and Mrs. Boughton, Mr. R. Roche, Mr. Montagu Wilson, Mr. Herbert Hope, &c.<ref>"Lady Constance Leslie's Reception." ''Morning Post'' 15 February 1890, Saturday: 2 [of 8], Col. 5c [of 7]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.co.uk/viewer/bl/0000174/18900215/008/0002. Same print title and p.</ref></blockquote> === 24 February 1890, Monday === Lilly Langtry starred in Shakespeare's ''As You Like It'' at the St. James's Theatre. The Daily Telegraph had a long review and mentioned more names:<blockquote> The motto of Petronius, which is said to have adorned the Globe Theatre in Shakespeare's time, "Totus mundus agit histrionem," and which is reproduced in Jaques' famous speech, may be said to have received a novel illustration in the brilliant audience which completely filled the St. James's Theatre last evening. A very distinguished section of the world "played the actor" in the stalls, boxes, and dress-circle, and evinced the keenest dramatic interest in the long-deferred production of "As You Like It." The Prince and Princess of Wales, with the Duchess of Fife, surveyed the scene from the Royal box, while amongst the many who secured seats for the first were the Austrian Ambassador, the [[Social Victorians/People/Louisa Montagu Cavendish|Duchess of Manchester]], Countess de Grey, [[Social Victorians/People/Mandeville|Viscountess Mandeville]], Lady Colin Campbell, Lord Wolverton, Lord and Lady Coleridge, Sir Charles Russell, Sir Edward and Lady Guinness, Baroness de Stern, and Mr. Alfred Rothschild. Naturally enough there was much curiosity in seeing once more on the London stage an actress who has since her last appearance devoted so much serious study to her profession, and gained so much success both before American and provincial audiences; while the sympathy evoked by her recent severe illness, delaying for four weeks the production of the comedy, added an almost pathetic note to the general excitement and enthusiasm. In the second scene of the first act, when the tenderly attached cousins make their earliest appearance on the stage, Celia's first words, "| pray thee, Rosalind, sweet, my coz, be merry," answered by Rosalind’s "Dear Celia, I show more mirth than I am mistress of," were almost drowned in the applause which accompanied the recognition of Mrs. Langtry. From time to time, whenever opportunity served, enthusiasm broke out anew, culminating in the triumph of plaudits which formed the fit ending to the gracefully-delivered epilogue with which Rosalind takes her farewell of her audience. There can be no doubt that, with all due allowance for the inevitable nervousness which accompanied a first production before a critical though sympathetic house, the revival of the immortal comedy was generally pronoanced to be a success. The fancifally-named "As You Like It" — where even in nomenclature the author confesses his indebtedness to the romance of Thomas Lodge — with greater dullness than is usually the case with Shakespeare's plays. Indeed interest is hardly aroused till the scene before the Duke's Palace, where Rosalind and Celia witness the wrestling — which after a few more performances will probably go less stagily than it did last night — between Charles and Orlando. It is only when we are transported to the Forest of Arden that Shakespeare's romantic fancy allows itself full course, and it was only when she was accoutred in the doublet and hose that Mrs. Langtry exercised her full charm upon the audience. The difficulty for the actress in the character of Rosalind is the contrast between the early abandon of her frankly-expressed love for the son of Rowland de Bois and the subsequent archness and reserve with which she plays with her lover in the forest. Orlando goes through precisely an opposite change. From the careless desperateness of a man who is out of favour with fortune in the opening scene, he changes to the sentimental devotion of a "love-shaked fancy-monger" in the sylvan glades. If that interchange of parts be missed much is lost in the sprightly  contrasts of the drama. Unfortunately, no sooner did Orlando enter on the wrestling-ground last night, than he started and caught at his heart in obvious suggestion of love at first sight. Much is lost of the utter wonderment at Rosalind’s unexpected graciousness in giving him her chain, which keeps him tongue-tied later, if he betrays so early the fatal ravages of Cupid — a betrayal which is hardly likely in a man whom neglect and misery have driven to the last stage of reckless hardihood. Rosalind must love her champion before her winning thanks for his prowess have made the starred younger brother first marvel at and then adore the frank and generous advances of his benefactress. In the fine words, "My father was no traitor," Mrs. Langtry rose to the full height of the character she was depicting. Throughout the greater part of the first act there was grace, loveableness, charm, but also a kind of flatness, or, at all events, an even and somewhat uninteresting level of characterisation which did not convey the promise of all that this loveliest creation in Shakespeare's gallery could do, when the Court life was exchanged for the freer and less conventional existence in the woods. All the more praise, therefore, is Mrs. Langtry’s due, that when she finds herself in the Forest of Arden, she brings before us a truer Rosalind. The beautiful first scene between the disguised Ganymede and her amorous swain showed Mrs. Langtry at her best. The quick and nimble wit, the archness and pretty coquetry of a girl who is sick at heart with love and feeds her passion in a playful and adorable tyrannising over the unconscious lover, were depicted with a reality which won instant recognition from the spectators. For the rest, however, Mrs. Langtry’s Rosalind was an unequal performance, now rising with unexpected force into the regions of pure comedy, now sinking to an ordinary level of  uncomfortably-disguised womanishness. There were bright patches of power in the midst of a somewhat dull and colourless expanse. Much of this was, no doubt, due to the excitement and fatigue of a first night, to which also may be attributed possibly the sameness of some of her gestures and a restlessness which was something more than Rosalind's anxiety to win in her own incomparable way the happiness of which she was in search. A few nights hence firmness of carriage and self-control of manner will fill in the details of a character which was most graphically and sympathetically sketched in outline at the St. James’s last night. Mr Laurence Cautley as Orlando made most favourable impression on his audience. Through all the earlier scenes — with the exception of that wholly unnecessary lapse into amorousness on the lawn of Duke Frederick, which has been already noted — he sustained the character of a picturesque and youthful gallant with considerable success, though, possibly, a stronger dash of manly independence might not have come amiss to the Shakespearean hero. Touchstone is a more difficult part to play. Indeed, in some respects, he is the most difficult of all Shakespeare's clowns. He is on the borderland between the earlier, more conventional style of Costard, Launce, and Launcelot, and the far more elaborate and important clowns in "Twelfth Night" and "King Lear." He is not so clever as Feste, not so human and real as that inimitable and tender-hearted Edgar who tries to solace the wild ravings of his discrowned king. He is halfway between such farcical beings as Kempe and Tarlton probably depicted, and that witty, self-conscious, irresponsible Jester, which Shakespeare ultimately made an entirely new creation on Elizabethan boards. It is no discredit to Mr. Sugden that he failed to realise so ingenious a conception. He presented a Touchstone who was full of amusing quips, and he went through all the catalogue of points in the Book of Honour in the fifth act with admirable skill; the Touchstone of "As You Like It" we are probably not likely to see often on the modern stage. Mr. Bourchier’s Jaques was a far higher piece of portraiture, grave and bitter and cynical as that early disciple of Schopenhauer should be, with touches of humour which only serve to show the depths of a naturally perverse and misanthropical nature. The celebrated "Seven Ages" speech  was capitally delivered, with a conscientious care and easy mastery which are rare enough in an actor who has so lately left the ranks of the amateurs. For the rest, the Adam of Mr Everill, and the Andrey of Miss Marion Lea seemed to give most pleasure to the audience, though she was sometimes — espectally in the pronunciation of the word "poetry" — inclined to represent the boorishness of the wench with an accent  which reproduced simulated inebriation rather than native clumsiness. Miss Armbruster as Hymen also deserves a word of praise. The piece was produced under the direction of the Hon. Lewis Wingfield, and the scenery, which in the Forest Glade of Acts II., III., and IV., formed a beautiful stage picture, was designed by Messrs. Perkins and Bruce Smith. After all, was any one ever wholly satisfied with the representaton of one of Shakespeare's comedies? No thing is further from the truth as a general statement than the pedant’s theory that Shakespeare is for the study, and not for the boards. If ever, however, the paradox be true that a great dramatic artist suffers when his plays gain a dramatic representation, it is when "As You Like It," "Twelfth Night" and "Midsummer Night's Dream" are brought face to face with a modern audience and amid nineteenth century surroundings. It ts not with impunity that the light that never was on sea and land is parodied by the glare of the footlights. For, honest stage-craftsman as Shakespeare was, in the full spring-tide of his poetic genius there was a divine and masterful intolerance of the real and the commonplace, a reckless flight into an ideal world, peopled by beings coined in the mint of his dainty imagination — aerial and disembodied creations whose actions and characters refuse to submit themselves to the narrow rules of the every-day world. In such a sphere banished lovers shall be predestined to meet and cement their happy unions, and lions and snakes shall be the habitual denizens of a forest where shepherds and shepherdesses prattle their erotic strains, and even a crafty Oliver shall repent of his past sins and fall in love with gentle Celia, owing to the poetic exigencies of Cloud Cuckoo Land. How can one  see all these things with the cynical eye of the modern ''Fin de Siècle'' and not feel an inevitable shock of dissatisfaction and surprise? How is it possible to avoid the jarring sense of discord when the dream picture is realised in the setting of prosaic reality? For Shakespeare's comedy is a romantic work of the mind, a refuge for all those delightful improbabilities which an indolent or whimsical fancy strings together to construct a series of complications and incidents which interest us, while they elude the sober tests of reason and judgment. But we must not carry this vein of thought too far. It is true that we have in such plays comedies of incident rather than of character. Yet Shakespeare is too and heart-whole to linger only at the Ivory gate. He throws even into these merry plots the force of that instinctive knowledge of human nature which produces real personages, tricked out in witty and imaginative guise. Shakespeare was able to pour everything into his comedies which he did into his tragedies, though in the one there is only suggestion, while in the other there is the elaboration of that is deep and tragic as well as humorous in life. Rosalid, Orlando, Touchstone, and Jaques are none the less real because they are ideal; and it is on these grounds that we can praise the conscientious and capable artists who presented these characters in flesh and blood on the St. James's stage. Nor does Shakespeare, as some have thought, intend in this play to preach [Col. 1c–2a]  any polemic against the life of the town, or compose any passionate encomium for the simple graces of the country. He is too great to be didactic on such narrow issues. Wherever men and women live, there they can be happy; or, as Touchstone says to Corin, when he expresses ignorance of the Court, one-sided enthusiasts for either streets or hedge-rows are truly damned, "like an ill-roasted egg, all on one side." Equanimity, such that of the Duke and old Adam, carries with it, wherever it be, the gracious gentleness of an eternal Eden.<ref>"St. James's Theatre." ''Daily Telegraph & Courier'' (London) 25 February 1890, Tuesday: 5 [of 12], Col. 6a–7a [of 7]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0001112%2F18900225&page=5&article=048&stringtohighlight=mandeville+viscount. Print title: ''The Daily Telegraph'', p. 5. </ref></blockquote> The ''St. James's Gazette'' reported:<blockquote> We came intending to like it very much, and we succeeded in our intention. Indeed, we spent a really pleasant evening at the St. James's Theatre, Many of us knew one another to nod to, and some of us had bowing acquaintance with the author of the play; so it was all very sociable and comfortable. There were just enough shop-window celebrities to give an air of distinction to the rest of the audience, and everybody had a right to hope that his neighbours were wondering who he was. The critics were quite at their ease, having nothing to criticise except the acting; not being expected to suggest any slight alterations in the play (such as cutting out Acts I., III., and V., and rewriting Acts II. and IV.), but just to accept it as it stood, without even tracing it back to the French vaudeville from which it was, no doubt, originally adapted. The performance had many individual merits, but it also had two general faults. The first and least striking fault was that the interludes were  slurred over instead of being played up to. Now, the plot of "As You Like It" is so loose that a lengthy interlude (provided it be pretty) does not check the flow of interest; indeed, it gives a welcome rest and allows you to pick up your thoughts again. The other fault is one which may be, and is likely to be, remedied the play goes on. But at present it is neither smart nor spontaneous: the parts do not hang well together, and there is none of the enthusiasm which helps to pass off the interior performances of less skilful actors. The deficiency which we have noted was probably due to the serious illness from which Mrs. Langtry had been suffering and from which it was evident last night that she had not made a complete recovery. She worked very hard as Rosalind, and worked very well, and several times she made a really good hit; she was, perhaps, at her best in her indignant appeal to the usurper Duke against his unexpected and unjust decree of banishment. She was charming, again, in her embarrassment (as Miss Litton was charming before her) when she had her first meeting with her unconscious lover and she suggested very cleverly the absence of her skirts. She did her love-making archly and merrily; but though the pretended pretence gave her a right to go beyond the limits of maiden coyness, she seemed occasionally to assume the masculine Initiative when the feminine Suggestive would have been prettier. it was a pleasant though uneven performance, with plenty of grace in it and plenty of brains. The Touchstone of Mr. Sugden was in every way admirable — crisp, humorous, and distinctive. That his clowning was occasionally tedious was no fault of his. The palate of a modern audience does not relish these long-drawn pedantries of buffoonery. Our sense of humour is not more refined — it is different, and that's the end of it. But in the scenes with Audrey (and Miss Marion Lea made a capital Audrey — open-mouthed and innocently wicked or wickedly innocent) Mr. Sugden had a better opportunity and he made the most of it. There the humour was not conventional, and the audience enjoyed a laugh which was not scholarly. A word of praise must given to Mr. Brodie for his conscientious and effective rendering of the difficult and ungrateful part of the moonstruck lover of the wayward Phoebe. The first appearance of Mr. Bourchier in London attracted much interest. As an amateur at Oxford and elsewhere he was believed Iikely to to great things upon the stage, and his performance of Jaques was by no means a disappointment. The fault of it was that he did not suggest either the melancholy or the sententiousness which we associate with the character. The melancholy was but skin-deep, and the sententiousness simply was not there. But every actor has a right to read a part in his own way if it is a good way. And there is much to said for Mr. Bourchier's interpretation of Jaques. The temptation is to be stagy; Mr. Bourchier's tendency is to be natural. And he carried it out with great success in speaking the lines of the Seven Ages of Man. He caught up the Duke's phrase just as if it had dropped in the course of an ordinary conversation; and he played with it for a time until it seemed of itself to suggest to his mind the famous soliloquy. Certainly Mr. Bourchier’s method was effective, as it drew one of the heartiest rounds of applause in the whole evening. Among the company were noticed the following well known persons:— His  Royal Highness the Prince of Wales, the Duke and Duchess of Fife, [[Social Victorians/People/Mandeville|Lady Mandeville]], Lord De Grey, Mr. Alfred De Rothschild, Lord Lurgan, Sir Charles Russell, Sir Edward Guinness, Lady Colin Campbell, Lady Curzon, Lady Londonderry, Lady Hothfield, Hon. Alan Charteris, Mr. Oscar Wilde, Mr. Akers Douglas, M.P., Mr. Justin McCarthy, M.P., Sir Allen Young, Lord and Lady Coleridge, the Austrian Ambassador, the Spanish Ambassador, Lady Hozier, Mr. George Lewis, Mr. Whistler, Lady Greville [<nowiki/>[[Social Victorians/People/Lady Violet Greville|Lady Violet Greville]]?].<ref>"As You Like It."  ''St James's Gazette'' 25 February 1890, Tuesday: 5 [of 16], Col. 1b–c [of 2]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0001485%2F18900225&page=5&article=027&stringtohighlight=mandeville+viscount. Same print title and p. </ref></blockquote> This report is from ''Blalud, The Bath Society Paper'':<blockquote>Happily, there was no disappointment in store for the friends and admirers of Mrs. Langtry, who gathered on Monday night at the St. James’s Theatre in great force, to welcome this popular lady back to London and receive her with an extra warmth of cordiality in token of satisfaction at her recovery from her recent severe illness. Eight years have elapsed since she last played Rosalind in London. Since then she has travelled much, both at home and abroad, and followed the study and practice of her art with unfailing spirit and determination. She returns to the character which all leading actresses aspire to play in Shakespeare’s glorious dream of the Court of Duke Frederick and the forest of Arden a far riper artist, and, says the ''Daily News'', she presented us on Monday with an impersonation which compared to her former efforts is as the finished portrait to the crude sketch. Her performance may lack the great high tide of girlish impulsiveness, but first nights before an exceptionally critical audience and some remains of the languor of her recent indisposition doubtless contributed to rob her acting of something of its force and impulse. But her ''Rosalind'' remains a most winning and beautiful performance. A handsomer ''Rosalind'', or one that has worn the doublet and hose with more grace and picturesqueness (Mrs, Langtry, we may here note, scorns the modern heresy of boots, and appears in the more orthodox hose cross-gartered), has certainly not been seen in our time. The performance is full of good points; as when at the words, "here on the skirts of this forest like the fringe of a petticoat," she remembers with a momentary touch of maidenly shyness that petticoats no longer form part of her attire. Again, when in bantering her lover, who exhibits so strange an inability to recognize the voice and features of the woman whom he passionately loves, she pauses at "a beard neglected," and pointing at ''Orlando’s'' smooth chin bursts into uncontrollable laughter; again, when in the mock marriage scene, with ''Celia'' for the priest, her mind for the moment seems to wander away into such a dream as this mockery might suggest to one so deeply in love. The distinguishing feature of the impersonation, indeed, is the subtle suggestion of serious passion that underlies the frolicsome and bantering moods, and exhibits itself again and again in many subtle forms. The play is beautifully put on the stage, and if some of the performers fall a long way short of ideal excellence there are several impersonations that stand forth in strong relief and are of far more than common excellence. The ''Phœbe'' and ''Silvius'' of Miss Beatrice Lamb and Mr. Matthew Brodie deserve special note: but the most brilliant success of all in the case of the minor characters was undoubtedly the ''Audrey'' of Miss Marion Lee, whose hoydenish, but not ungraceful antics, whose happy, contented ignorance, whose mingled wonderment and admiration at ''Touchstone's'' philosophical utterances were admirable. Everything that taste can suggest has been done to embellish the play; the musical features are strengthened by an efficient chorus, and the costumes designed by the Hon. Lewis Wingfield are rich and handsome. Perhaps it might be objected that Mrs. Langtry’s beautiful green velvet doublet, with its slashes, tags, and laces, her cinnamon jerkin, her black cap and jewelled buckle, and her rich and massive cloak were hardly suited to her daring enterprise on the highways and in the forests of the Duke’s dominions. The restoration of Hymen, gracefully represented by Miss Violet Armbruster, and the final morris dance in honour of the nuptials, gave the crowning fanciful touch to the performance, and prepared the spectators for the playful epilogue, which was spoken by Mrs. Langtry, in her simple nuptial white robe and leopard skin, with rare elocutionary grace and effect,. [sic] The audience which greeted Mrs. Langtry was at once distinguished and interesting. The Royal box was occupied by the Prince and Princess of Wales, the Duchess of Fife, the Princesses Victoria and Maud of Wales, and the Duke of Fife. Among the representatives of "Society" were Lady Londonderry, [[Social Victorians/People/Mandeville|Lady Mandeville]], Lord de Grey, Lord and Lady Coleridge, Lady Curzon, Lady Hothfield, Lord Lurgan, Lady Greville [<nowiki/>[[Social Victorians/People/Lady Violet Greville|Lady Violet Greville]]?], Lady Hozier, Mr. Alfred de Rothschild, Sir Charles Russell, Sir Edward Guinness, Mr. Coningsby Disraeli, Mr. Akers Douglas, M.P., Mr. Justin M‘Carthy, M.P., Sir Allen Young, Lady Colin Campbell, Lady Monckton, Mrs. Labouchere, and the Austrian and Spanish Ambassadors. Pictorial art was represented by Mr. Whistler; music by Mdme. Antoinette Sterling; dramatic writing by Mr. H. A. Jones; and theatrical interests by Mrs. Bancroft, Miss Genevieve Ward, Mr. and Mrs. John Lart, Mrs. John Hare, Mr. M. L. Mayer, Mr. Augustus Harris, &c.<ref>"Mrs. Langtry." ''Bladud'' 26 February 1890, Wednesday: 9 [of 16], Col. 2b–c [of 3]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0005771%2F18900226&page=9&article=055&stringtohighlight=mandeville+viscount. Print title: ''Blalud, The Bath Society Paper'', p. 9.</ref></blockquote> === 25 February 1890, Tuesday === On 5 March, the ''World'' reports on a party hosted by Mrs. Adair that must have been held the week before:<blockquote>Many smart people were present at Mrs. Adair's party in Curzon Street on Tuesday night. The rooms, lighted by electricity, looked their prettiest with floral decorations consisting entirely of tulips, the hostess appearing in a gown of terra-cotta velvet trimmed with dark fur. The Austrian Ambassador and Madame Waddington were among those who listened to Miss Damian’s rendering of a new song by Tosti, and to the glees sung by Mr. Avon Saxon's American quartet; and among others present were Lady Charles Beresford, [[Social Victorians/People/Mandeville|Lady Mandeville]], the Duchess of Marlborough, Lady Fanny Marjoribanks, who brought her sister, Lady Sarah Churchill, Sir Arthur Sullivan (just back from his annual sojourn at Monte Carlo), Lord and Lady Wharncliffe, Lady Howe and Lady Edith Curzon, Lord and Lady William Nevill, Mrs. Cavendish-Bentinck, General Charles Fraser, Lady Conyers, Madame de Brienen, and Sir Philip Currie.<ref>"What the World Says." ''The World'' 5 March 1890, Wednesday: 19 [of 44], Col. 2a [of 2]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0006339%2F18900305&page=19&article=061&stringtohighlight=mandeville+viscount. Same print title and p.</ref></blockquote>The ''Daily Telegraph'' covered the party with a few additional names:<blockquote>A casual passer-by in Curzon-street last night might almost have imagined from the long string of carriages assembled there that, in spite of the cold east wind blowing, the London season had already begun. Mrs. Adair had together to hear some beautiful music, including a celebrated quartette of American singers, a large and fashionable crowd, composed of the ''élite'' of London society, comprising among many others, the Austrian Ambassador, the French Ambassadress, the Marquis and Marchioness of Tweeddale, Lady Charles Beresford, Lady Fanny Marjoribanks and Lady Sarah Spencer-Churchill, Earl and Countess of Wharncliffe, Countess Howe and Lady Edith Curzon, Lord and Lady William Nevill, Lord George Nevill, Viscount and Viscountess Curzon, Countess of Sefton and Lady Rose Molyneux, Viscountess Mandeville, Julia Countess of Jersey and Mr Brandling, Viscount and Viscountess Bury and the Hon. Mary Keppel, the Countess of Crawford, the Earl of Clonmell, the Countess of Antrim and Lady Louisa Beauclerk, Viscountess Melgund, Lady Conyers, Hon. Lady Cotterell and Miss Cotterell, Lord Alington, Lord Alcester, Lord Greenock, Viscount de Vesci, Lady Hilda Brodrick, Hon. W. Lowther, M.P., and Mrs. Lowther, Hon. Mrs. Bampfylde, Hon. Hallyburton Campbell, Mrs. and Miss Campbell, Hon. Kenneth Howard, Hon. Derek Keppel, Hon. FitzRoy and Mrs. Stewart, Lady FitzGerald, Mrs. Bischoffsheim, Madame de Brienen, Lieutenant-General Sir Seymour Blane, General C. Fraser, M.P., Mr. Chamberlain, M.P., Mr. Howard Vincent, M.P., and Mrs Vincent, Mr. Charles Hall, M.P., Mrs. Cavendish-Bentinck, Sir C. Rivers Wilson, Sir Arthur Sullivan, Sir Philp Currie.<ref>"London Day by Day." ''Daily Telegraph & Courier'' (London) 26 February 1890, Wednesday: 5 [of 8], Col. 4a [of 8]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0001112%2F18900226&page=5&article=094&stringtohighlight=mandeville+viscount. Print title: ''The Daily Telegraph'', p. 5. </ref></blockquote>The ''Sporting Gazette'' also had a report, on 1 March:<blockquote>Mrs. Adair's party in Curzon-street on Tuesday night was, as usual, exceedingly smart and dressy. The "smarties" turned out strong for this Anglo-American function, and wore their best frocks and jewels. Lady Tweeddale, Lady Howe, with Lady Edith Curzon, Lady Fanny Majoribanks chaperoning her younger sister, Lady Sarah Churchill, Lady Curzon, Lady Antrim with Lady Louisa Beauclerk, Lady William Nevill with some lovely diamonds, [[Social Victorians/People/Mandeville|Lady Mandeville]], Lord Alington, Sir Arthur Sullivan, Mrs Cavendish Bentinck, and others. The singing of an American quartette was ''the'' feature of the evening.<ref>"The Man About Town." "The County Gentleman." ''Sporting Gazette'' 1 March 1890, Saturday: 6 [of 38], Col. 2b [of 3]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0002525%2F18900301&page=6&article=053&stringtohighlight=mandeville+viscount. Same print title, p. 274.</ref></blockquote> ==March 1890== === 10 March 1890, Monday === The Prince and Princess of Wales hosted a ball in celebration of their wedding anniversary. This report from the ''Bedfordshire Mercury'' is very brief:<blockquote> The Prince and Princess of Wales, in celebration of the anniversary of their wedding on March 10, 1863, gave a dance at Marlborough House on Monday night. The Danish Minister and Madame de Falbe were among the company invited, also the Earl and Countess Brownlow, [[Social Victorians/People/Mandeville|Viscountess Mandeville]], Lord Alwyne Compton, Baron F. de Rothschild, &c.<ref>"Notes of the Aristocracy." ''Bedfordshire Mercury'' 15 March 1890, Saturday: 7 [of 8], Col. 4b [of 6]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0001290%2F18900315&page=7&article=073&stringtohighlight=mandeville+viscount. Same print title and p.</ref></blockquote> The report from the ''Morning Post'' suggests that this was a smaller party than usual for the Prince and Princess of Wales:<blockquote>In celebration of the anniversary of the Prince and Princess of Wales's wedding day, their Royal Highnesses gave an evening party (dancing) at Marlborough House last night. His Royal Highness the Duke of Edinburgh, her Royal Highness Princess Beatrice (Princess Henry of Battenberg) and his Royal Highness Prince Henry of Battenberg, her Royal Highness the Princess Louise of Wales (Duchess of Fife) and the Duke of Fife, his Royal Highness Prince George of Wales, her Royal Highness the Princess Victoria of Wales, her Royal Highness the Princess Maud of Wales, her Royal Highness the Princess Mary Adelaide (Duchess of Teck), and his Highness the Duke of Teck and her Serene Highness the Princess Victoria of Teck and his Serene Highness Prince Francis of Teck, and their Serene Highnesses the Prince and Princess Victor of  Hohenlohe-Langenburg and the Countess Victoria Gleichen were present. The following had the honour to receive invitations, but some amongst them were unavoidably prevented from attending: — The French Ambassador (M. Waddington) and Madame Waddington, the German Ambassador (Count Hatzfeldt) and the Countess Marie Hatzfeldt, the Turkish Ambassador (Rustem Pasha), the Austro-Hungarian Ambassador (Count Deym) and the Countess Deym, the Italian Ambassador  (Count Tornielli), the Countess Tornielli, and Mademoiselle Virginia dei Conti Lazzari, the Danish Minister (M. de Falbe) and Madame de Falbe, the Russian Chargé d'Affaires (M. Bontineff), his Serene Highness Prince Louis Esterhazy, M. A. Kroupensky, M. A. de Stoeckl, Count Leyden, Count Albert Mensdorff, Count Reventlow, Mr. and Mrs. Henry White, M. de Soveral, the Marques and Marquesa de Santurce, Mr. A. de Murrieta, Mr. C. de Murrieta. The Duke and Duchess of Leeds and Lady Alice Osborne, the Duke and Duchess of Buccleuch, the Duke and Duchess of Portland, the Duke and Duchess of Westminster, the Marchioness of Blandford and Lady Frances Spencer Churchill, the Marquis and Marchioness of Granby, the Marquis and Marchioness of Londonderry, the Marquis and Marchioness of Ormonde, the Marquis and Marchioness of Salisbury and Lady Gwendolen Cecil, the Marquis and Marchioness of Stafford, Count Gleichen, the Earl and Countess Brownlow, the Earl and Countess Cadogan and Lady Emily  Cadogan, the Earl and Countess of Clarendon, the Earl of Chesterfield, the Earl of Clonmell, the Earl of Dudley, the Earl and Countess of Dunraven and Lady Florence Wyndham Quin, the Earl and Countess Granville and Lady Victoria Leveson Gower, the Earl and Countess of Hardwicke, the Earl and Countess Howe and Lady Evelyn Curzon, the Earl and Countess of  Kilmorey, the Earl and Countess of Lathom and Lady Alice Wilbraham, the Earl and Countess of Lucan and Lady Rosalind Bingham, the Earl of Mount Edgcumbe and Lady Albertha Edgcumbe, the Earl and Countess of Romney and Lady Florence Marsham, the Earl and Countess of Rosebery, the Earl of Shaftesbury, the Earl of Stradbroke, the Earl and Countess of Sefton and Lady Gertrude Molyneux, the Earl and Countess Spencer, Viscount Drumlanrig, Lord and Lady Randolph Spencer Churchill, Lord Frederick Hamilton, Lord Ernest Hamilton, Lord and Lady Algernon Gordon Lennox, [[Social Victorians/People/Mandeville|Viscountess Mandeville]], Lord Charles Montagu, Viscount Chelsea, Viscount and Viscountess Coke and the Hon. Violet White, Viscount Curzon, Lady Georgina Curzon and Lady Sarah Spencer Churchill, Viscount Fincastle, Viscount Royston, Viscount Valletort, Lord and Lady Brooke, Lord Burghersh, Lord Capell, Lord and Lady Norreys and the Hon. Coralie Glyn, Lady Charles Beresford, Lord Marcus Beresford, Lord Alwyne Compton, Lord and Lady William Nevill, Lord Richard Nevill, Lord Henry Paulet, Lord Henry Vane Tempest, Lord Herbert Vane Tempest, Admiral Lord Alcester, Lady Ampthill and the Hon. Constance Russell, Lord Alington and the Hon. Winifred and Hon. Mildred Sturt, Lord and Lady Colville of Culross  and the Hon. Blanche Colville, Lord and Lady De  Ramsey, Lady Hastings, Lord and Lady Hindlip, Lord Lurgan, Lord and Lady Revelstoke and the Hon. Susan Baring, Lord and Lady Rothschild,  Lord Rowton, Lord Suffield and the Hon. Judith and Hon. Eleanor Harbord, Lord and Lady Wimborne and the Hon. Frances Guest, Lord Wolverton, Baron Ferdinand Rothschild, Captain the Hon. Maurice Bourke, R.N., Colonel the Hon. Henry Byng and the Misses Byng, the Hon. Alan Charteris, Lieutenant-Colonel the Hon. C. Edgcumbe, the Hon. Sir Spencer and Lady Ponsonby Fane, the Hon. Sidney Greville, Colonel the Hon. Oliver Montagu, the Hon. C. R. and Mrs. Spencer, the Hon. S. M'Donnell, the Hon. Alexander Yorke, the Hon. H. and Lady Feodora Sturt, the Hon. Arthur Walsh, the Hon. R. Winn, the Right Hon. W. E. and Mrs. Gladstone and Miss Gladstone, the Right Hon. A. J. Balfour, the Right Hon. H. Chaplin, the Right. Hon. Sir Henry James, the Right Hon. Sir C. L. Wyke, the Hon. S. C. Colville, the Hon. Assheton Harbord, the Hon. Julia Stonor, the Hon. H. Stonor, the Hon. E. Stonor, Captain the Hon. Henry White, Sir Edward and Lady Guinness, Sir Charles Hartopp, Sir Frederick Johnstone, Sir John and Lady Lister Kaye, Sir James and Lady  Mackenzie, Colonel Sir Nigel and Lady Emily Kingscote, Admiral Sir R. and the Hon. Lady Macdonald and Miss Macdonald, General Sir Dighton and Lady Probyn, Sir Francis and the Hon. Lady Knollys, Major-General Sir Christopher Teesdale, Sir Oscar Clayton, Sir Allen Young, Lieutenant-General Bateson, Lieutenant-General Charles Fraser, Major-General and the Hon. Mrs. Arthur Ellis and Miss Ellis, Colonel J. P. Brabazon, Colonel and Mrs. Stanley Clarke and the Misses Clarke, Captain H. F. Stephenson, R.N., Lieutenant-Colonel F. H. Poore, Lieutenant-Colonel R. Vivian, Major C. Swaine, Captain Douglas Dawson, Captain C. H. A. Hervey, the officers of the Queen's Guard, St. James's Palace, Mr. G. Byng, Mr. Henry Calcraft, Mr. Victor Cavendish, Mr. Henry Ellis, Mr. Horace Farquhar, Mr. and Mrs. George Forbes and Miss Forbes, Mr. Montagu Guest, Mr. Charles Hall, Mr. E. W. Hamilton, Mr. and Lady Hilda Higgins, Mr. Holzmann, Miss Knollys, Mr. and Mrs. F. R. Knollys, Mr. Ronald Moncrieffe, Mr. Alfred Montgomery, Mr. Arnold Morley, Mr. Henry Petre, Mr. Alfred de Rothschild, Mr. and Mrs. Leopold de Rothschild, Mr. Reuben Sassoon and Miss Sassoon, Mr. and Mrs. Arthur Sassoon, Mr. Edgar Sebright, Mr. and Mrs. Ralph Sneyd, Mr. Christopher Sykes, and Mr. O. G. St. George Williams. Messrs. Coote and Tinney's band was in attendance.<ref>"Marlborough House." ''Morning Post'' 11 March 1890, Tuesday: 5 [of 8]. Col. 6b–c [of 7]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0000174%2F18900311&page=5&article=055&stringtohighlight=mandeville+viscount. Same print title and p. </ref></blockquote> ==April 1890== Arnold Dolmetsch took out a three-day ticket to the Reading Room in April 1890 (Campbell 22). === 9 April 1890, Wednesday === ==== The New Forest United Hunt Ball ==== <blockquote>This annual ball was beld at the New Forest Hall, Lyndhearst, on Wednesday night, and was a most brilliant gathering, upwards of 200 being present, not only the New Forest but also neighbouring hunts being well represented. Among those present were Earl and Countess of Londesborough, Lady Mildred Denison, Lady Lilian Denison, Hon. Louis Johnstone, Hon. Gerald and Mrs Lascelles, Major Downman, Capt. Sandbach, R.H.A., Col. and Mrs Sinkins, Col. Fitzroy Smyth, Lady Thursby and party, Mr Stanley Pearce (Master of the Foxhounds), Mr F. Lovell (Master of the Deerhounds) and party, Lady Adela Goff and party, Hon. Miss St. Leger Glyn and party, Mr A. H. Jeffreys, M.P., and Mrs Jeffreys, Hon. Mrs A. Peter, Mr Somerset H. Onslow, Mr Lancelot Orde, Lord Garioch, Mr and Mrs C. K. Francis, the Countess of Normandy, Lady Mary Agar, Lord Montagu, Hon. John Scott Montagu, Viscount Cantelupe, Prince Dhuleep Singh, Hon. D. Keppel, Col. Charles Needham (1st Life Guards), [[Social Victorians/People/Bourke|Hon. Mrs Algernon Bourke]], Mrs Cornwallis West, Mr and Mrs Shelley Bontein, Col. Gridley, Col. Newton, Col. Elliot, R.H.A., Lady Meyrick and party, Sir W. Jervois, Lady Jervois and party, &c.<ref>"The New Forest United Hunt Ball." ''The Sportsman'' 11 April 1890, Friday: 2 [of 4], Col. 5c [of 7]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.co.uk/viewer/bl/0001055/18900411/024/0002. Same print title and p.</ref></blockquote> ==May 1890== Leonora Braham appeared at the Opera Comique as Ruth Ferns in ''Gretna Green''. ===21 May 1890, Wednesday=== It was his pupil the young Countess Valda Gleichen who found a sponsor for Dolmetsch's first but brief appearance at a London concert on 21 May 1890, when the 'Magpie Minstrels' … gave one of their bi-annual performances at the Princes' Hall" (Campbell 30). ==June 1890== === 3 June 1890, Tuesday === ==== Dinner and Concert Hosted by Mrs. Arthur Williams and Ball by Mrs. Menzies ==== <blockquote>Yesterday evening society passed a large proportion of time on wheels, and the number of receptions was more than the most inveterate could get through wvith comfort. ... Meanwhile, the Duke of Clarence and Avondale dined with Mrs. Arthur Wilson in Grosvenor-place, and a small and select concert followed. The Duchess of Leinster was, as ever, the most beautiful among many beauties, the Hon. Helen Henniker, after her long mourning, was warmly greeted by swarms of friends, and the Countess of Lovelace, in grey satin, chaperoned her débutante niece, Miss Milbank. Prince "Eddie" went from Mrs. Arthur Wilson's hospitable mansion to that of Mrs. J. Graham Menzies. It is unusual to find mother and daughter entertaining this illustrious young man on the same evening. Mrs. Menzies, who has succeeded Lord Suffield in his beautiful house in Upper Grosvenor-street, had one of the smartest and most successful balls of the present season. The Blue Hungarians played with immense vigour and owing to the postponement of Lady Carnarvon's ball, there was no competition for men and married women. Countess Howe, Lady Brougham and Vaux, Lady Aveland and Miss Willoughby, Viscountess Stormont, the Hon. Lady Grey Egerton and Miss Egerton, the Duchess of Buccleuch, the [[Social Victorians/People/Bourke|Hon. Mrs. Algernon Bourke]], the Earl of Craven, Countess of Coventry, Mrs. Mackay, Lady Sykes, the Marchioness of Granby, Mrs. Hwfa Williams, Lord Garioch, Sir Savile and Lady Crossley, Mr. and Mrs. Harry Lawson, and many others were present.<ref>"Yesterday Evening Society." ''Pall Mall Gazette'' 4 June 1890, Wednesday: 4 [of 8], Col. 3a [of 3]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.co.uk/viewer/bl/0000098/18900604/015/0004. Same print title and p.</ref></blockquote> ==== Münster-Hay Wedding ==== Account of the wedding of Count Alexander Münster and Lady Muriel Henrietta Constance Hay. Count Bismarck sent a gift.<blockquote>St. Andrew's Church, Wells-street, was completely filled yesterday afternoon on the occasion of the marriage of Count Alexander Münster, son of Count Münster, German Ambassador in Paris, with Lady Muriel Henrietta Constance Hay, younger daughter of the Earl and Countess of Kinnoull. The ceremony was fixed for half-past two o'clock, but all the seats in the body of the church were occupied long before that time by invited guests. The rood screen was hidden with white flowers, and a number of tall palms were skilfully arranged in and about the chancel. The bridegroom was early in his place, and wore the splendid white and gold uniform of the Garde du Corps of the Emperor; his best man, Prince Hans Heinrich Pless, wearing the scarlet and gold uniform of the Garde Hussars. The six bridesmaids were Lady Mildred Denison, Lady Dorothea Stewart Murray, Hon. Marie Hay, Hon. Marjory Murray, Miss Rosalind Lovell, and Miss Gladys Hadow (niece of the bride). They wore pretty dresses of pale blue satin, veiled with white chiffon; the skirts were edged with a frill, and the bodices finished with quaint fichus of the chiffon, fastened in front with a bunch of forget-me-nots. They wore drawn hats of the chiffon, covered with forget-me-nots, and their posies were of the same flowers, intermixed with pink roses, and tied with narrow pink ribbons. Each wore a gold bangle with centre forming the initials "A.M.," and a single turquoise drop. The bride entered the church at half-past two, and was received by her father, who led her to the chancel steps, preceded by the choristers singing a nuptial hymn. The bride's dress was of ivory satin made with a very long train. The front was fringed round the hem with orange blossoms and veiled with old Brussels lace, the gift of her mother; the bodice was entirely covered with beautiful old lace, and finished at the neck on one side with a cluster of orange blossoms. She wore a small wreath of orange blossoms and myrtle arranged in the hair at the back and a tulle veil falling almost to the end of the train and held by diamond stars, the gift of the bridegroom. The bride's other jewels included two diamond drop hairpins, the gift of Count Münster; an emerald and diamond brooch, from the bridegroom; enamel and diamond heartsease brooch, from Lady Mary Mills; a diamond and emerald bracelet, from the Duke of Beaufort; and a diamond bracelet, from the Duke and Duchess of Athole. Her train was held by her two little nephews, Masters Roland and Patrick Hadow, wearing Scotch dress with lace ruffles. The service, which was fully choral, was performed by the Rev. Provost Rorison, of St. Ninian's Cathedral, Perth, assisted by the Rev. W. T. Houldsworth, rector of St. Andrew's. The Earl and Countess of Kinnoull afterwards entertained the bridal party at the residence of the Earl of Londesborough, uncle of the bride, in Grosvenor-square. Among the numerous guests were the Russian Ambassador and Madame de Staal, the German Ambassador, the Austrian Ambassador and Countess Deym, Count Münster and the Countesses Marie, Julia, and T. Münster, Prince Pless, Prince Louis Esterhazy, Count Donhoff, Baroness von Beckendorff-Hindenburg, Baron E. Fürstenberg, Count Paul Metternich, Geheimrath Schmettau, Countess Valentin, [[Social Victorians/People/de Soveral|M. de]] [[Social Victorians/People/de Soveral|Soveral]], Captain Hasenclever, Count Leyden, Herr von Rath, Count Francis Deym, Baron and Baroness Deichmann, Count Mensdorff, Herr Pilgrim Baltazzi, Count and Countess Henry Lützow, Baroness d' Erlanger [?], Herr von Kemnitz, Baron Cramm, Vicomte de Janzé, the Duke of Beaufort, the Duchess of Athole, and the Ladies Stewart Murray, the Marchioness of Downshire, the Marchioness of Stafford and Lady Sybil St. Clair Erskine, Maria Marchioness of Ailesbury, the Countess of Dunraven and Ladies Wyndham Quin, the Countess of Kilmorey, the Countess of Galloway and Miss Stewart, the Countess of Dudley and Lady Edith Ward, the Countess of Strathmore and Lady Constance Lyon, the Earl and Countess of Roden, Lady Willoughby de Eresby and Hon. Miss Willoughby, the Countess of Westmorland. Viscount and Viscountess Raincliffe, Viscountess Coke, Viscountess Stormont and Hon. MabeI Murray, Viscountess Malden and Hon. Miss Capel, Lord Hay of Kinfauns [?], Lady Delamere and Miss Cholmondeley, Lady Brougham, Lady Esher, Lord Saye and Sele and Hon. Maud and Hon. Gertrude Fiennes, Lady Helen MacGregor and Miss MacGregor, Lord and Lady Algernon Gordon Lennox and Lady Angela St. Clair Erskine, Lady Raglan, Lord Charles Innes Ker, Lady Elizabeth Bertie, Lady Frances Pratt and Lady Clementine Pratt, Lady Geraldine Somerset, Lady Dalton Fitzgerald and Miss Payne, Lady Mary Mills and Miss Pereira, Lady Dorchester, Lady Louisa Moncreiffe and Misses Moncreiffe, Lady Norreys, Lady Petre, Lady Jane Trefusis, Lord Frederic Hamilton, Baroness de Brienen and Miss de Brienen, Helen Lady Forbes and the Misses Forbes, Lady Scott, Miss Scott and Mrs. Green, Lord Zouche and Hon. Miss Curzon, Mr. and Lady Constance Hadow, Hon. Lady Campbell, Lady William Nevill and Miss Bannerman, Hon. Alastair and Mrs. Hay, Hon. Miss Greville, Captain Hon. Randolph Stewart, Hon. FitzRoy and Mrs. Stewart, Hon. Charles Walsh, Hon. William Walsh, [[Social Victorians/People/Bourke|Hon. Mrs. Algernon Bourke]], Colonel Hon. Charles and Mrs. Hay and Miss Maude Hay, Hon. Mrs. Greville Nugent, Hon. Mrs. Colville and Miss Streatfeild [sic], Hon. Claude Hay, Sir Charles and Lady Forbes of Newe, Laely Borthwick, Sir Francis Montefiore, Sir Henry Hoare, Sir George Arthur, Sir William Gordon Cumming, General and Mrs. Wilkinson, Colonel and Mrs. Chaine, Colonel Arthur Paget, Colonel H. M. Hozier, the Provost of St. Ninian's, Major Finch, Major Candy, Colonel Lloyd, Captain and Mrs. Stewart, Mr. and Mrs. Hay Drummond, Captain and Mrs. Lloyd, Mr. William Gillett, Mr. Hulse, M.P., and Mrs. Hulse, Captain Lumley, Captain Barrow, Major Anstruther, Mrs. Hwfa Williams, Mr. Arthur Hay, Mr. Raglan Somerset, Mr. and Mrs. George Cavendish Bentinck, Mrs. Villiers, Mr. Henry Petre, Mrs. Keighley, Mrs. E. Balfour and Miss Balfour and Miss Ellice, Mrs. Dick Cunynghame and Miss A. M'Gregor, Rev. C. Weidemann, Miss Balfour and Miss E. Balfour, Mrs. and Miss Halford, Mr. and Mrs. Toler, Mrs. and Miss Townley, Rev. Dr. M'Ewan, Mr. A. F. Levita, Mr. F. Stephens, Mrs. and Miss Leigh, Mr. and Mrs. George Forbes and Miss Forbes, Mrs. Luke Wheeler, Mrs. J. Beerbohm, Dr. and Mrs. W. M. Collins, Mrs. and Miss Orde, Mrs. Murray, Miss Glyn, Mrs. Godfrey Pearse, Mr. Balfour, Mr. Leopold Goldberg, Mr. and Miss Oswa d [Oswald], Mr. and Mrs. C. Bulteel, Mrs. Brydges Wyllyams, Mr. H. Balfour, the Misses Codrington, Miss Finch, Mrs. Barron and Miss Sullivan, Mr. Hamilton Aidé, Mr. Granville and Miss Berkeley, Mr. M'Gregor, Mrs. and Miss Needham, Mr. and Mrs. A. Consett and Miss Consett, Mrs. Herbert Naylor LeyIand, Mr. and Mrs. A. Darby, Mrs. Montefiore, Mrs. Charles Murray and Miss Murray, Mrs. Thomas Legh, the Rev. John F. Mitchell, Mr. and Mrs. Claud Hay, Mr. Fiztalan Manners, Mr. Albert Stopford, Mr. Hervey Pechell, and Mr. and Mrs. Charles Orde. Later in the day Count Alexander Münster and his bride left for Hillingdon Court, Uxbridge, the residence of the Hon. A. Mills, where they will pass the early days of the honeymoon, and then proceed to Chàlet Sans Souci, Bellaggio, Lake of Como, lent by Mr. Hervey Pechell. They will afterwards go to Wiesbaden, and thence to Count Münster's German country seat, where a great reception awaits them. The wedding presents were very numerous. Count Munster presented the bride with a diamond necklace and pair of diamond drop hairpins. The bridegroom's gifts to his bride included a tiara of three diamond stars, a brooch formed of an emerald of unusual size set in diamonds, large pearl pendant, gold bracelet set with turquoises, and diamond and turquoise ring. The Duke of Beaufort presented Lady Muriel with an emerald and diamond bracelet. The Earl and Countess of Kinnoull's presents included a quantity of plate and other articles. Prince Henry of Battenberg sent a large silver-mounted claret jug; Count Bismarck, a silver box; the Marchioness of Waterford, gold snake bracelet, with pearl head and ruby eyes; the Duke and Duchess of Athole, diamond "M" bangle; Lady Ermyntrude Malet, massive silver bowl; Countess Marie Münster, silver tea set and tray; Baron E. Fürstenberg, pair of gold-mounted claret jugs; Baron and Baroness Erlanger, large silver bowl; Baron and Baroness Gungberg, pair of antique silver mounted jugs.<ref>"Marriage of Count Alexander Münster and Lady Muriel Hay." ''Morning Post'' 4 June 1890, Wednesday: 7 [of 12], Col. 7a–c [of 7]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.co.uk/viewer/bl/0000174/18900604/064/0007. Same print title and p.</ref></blockquote> ===4 June 1890, Wednesday=== Derby Day. According to the Morning Post, <quote>Lady Thurlow's first dance. / Mrs. Coddington's Ball. / The Fourth of June celebration at Eton. / ... Royal Society of Literature — Paper on "Early England," by Mr. Carmichael, S. </quote> ("Arrangements for This Day." The Morning Post Wednesday, 4 June 1890: p. 7 [of 12], Col. 6A). ===13 June 1890, Friday=== ? or on the 12th? Arnold Dolmetsch had a concert at which his students performed (Campbell 31). It was reviewed very positively in the 13 June Daily Graphic, especially Helene Dolmetsch's performance. They did Purcell's Fairy Queen. They used a harpsichord. ===26 June 1890, Thursday=== There was apparently a regular celebration of [[Social Victorians/People/Arthur Collins|Arthur Collins]]' birthday, 26 June, by Bret Harte, George Du Maurier, [[Social Victorians/People/Arthur Sullivan|Arthur Sullivan]], Alfred Cellier, Arthur Blunt, and John Hare (Nissen, Axel. Brent Harte: Prince and Pauper: 239. [http://books.google.com/books?id=WEDewmUnapcC]). Choosing 1885–1902 as the dates because those apparently are the dates of the close relationship between Harte and Collins, ending in Harte's death in 1902. ==July 1890== ===3 July 1890, Thursday=== <blockquote>On July 3, 1890, Besant’s house at 19 Avenue Road, St. John’s Wood, was inaugurated as a new center of Theosophical work, serving as the European headquarters of the [[Social Victorians/Theosophical Society|Theosophical Society]] and as HPB’s residence. That house became also the meeting place of HPB’s Inner Group, twelve of her students who were eager for more intense training than was feasible in a larger, more general gathering.</blockquote>That Inner Group is different from the Esoteric Section.<ref>"Esoteric World Chapter 23." ''The Theosophical Society of America, Online Resources''. http://www.theosophical.org/index.php?option=com_content&view=article&catid=23&id=1725&Itemid=53</ref><blockquote>The hall had a seating capacity of about 200. On the opening night [July 3, 1890] [sic] the room was crammed, and many were unable to gain admission. The speakers were Mrs. Besant, Mr. Sinnett, a Mrs. Woolff (of America), and Mr. [Bertram] Keightley. HPB was present but said nothing, on account of the critical state of her health.<ref>"23a. Henry S. Olcott, July 1890, London [Olcott 1931, 4:254–6]." Esoteric World Chapter 23. ''The Theosophical Society of America, Online Resources''. http://www.theosophical.org/index.php?option=com_content&view=article&catid=23&id=1725&Itemid=53.</ref></blockquote> === 4 July 1890, Friday, 11 p.m. === ==== The Queen's State Ball at Buckingham Palace ==== The Prince and Princess of Wales were hosts of this ball, as Queen Victoria was not present. Many of the Queen's children and their spouses were present.<ref>"State Ball at Buckingham Palace." ''Morning Post'' 5 July 1890, Saturday: 5 [of 8], Col. 5a–7b [of 7]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.co.uk/viewer/bl/0000174/18900705/038/0005. Same print title and p.</ref> The dancing commenced shortly after the Prince and Princess of Wales arrived at 11:00. === 1890 July 15, Tuesday === ==== Garden Party at Marlborough House to Meet the Queen ==== The beginning of the ''Morning Post'' article, which is followed by a very long list of people invited:<blockquote>Their Royal Highnesses the Prince and Princess of Wales gave a garden party at Marlborough House yesterday afternoon to meet the Queen. Her Majesty was accompanied by their Royal Highnesses the Princesses Victoria and Margaret of Prussia, and was attended by the Duchess of Roxburghe, Miss M'Neill, the Hon. Evelyn Moore, the Hon. Bertha Lambert, and Major-General Sir Henry Ewart and Major F. A. Bigge. Madlle. De Perpigna was in attendance on the Princesses Victoria and Margaret. The following were present: — Their Royal Highnesses the Duke and Duchess of Edinburgh and Prince Alfred, and the Princesses Marie, Victoria, Alexandra, and Beatrice of Edinburgh; their Royal Highnesses the Duke and Duchess of Connaught and Prince Arthur, and the Princesses Margaret and Patricia of Connaught; their Royal Highnesses the Prince and Princess Christian of Schleswig-Holstein Sonderburg-Augustenburg and Princess Victoria and Princess Louisa of Schleswig-Holstein, her Royal Highness the Princess Louise, Marchioness of Lorne, and the Marquis of Lorne. Her Royal Highness the Duchess of Albany, her Royal Highness the Princess Frederica and the Baron von Pawell-Rammingen, his Royal Highness the Duke of Cambridge, her Royal Highness Princess Mary Adelaide Duchess of Teck and his Highness the Duke of Teck and Princess Victoria of Teck, his Royal Highness the Duke d'Orleans and Princess Hélène d'Orleans, his Imperial Highness Don Pedro Augustus of Coburg and Braganza, his Serene Highness the Prince of Schaumburg-Lippe, his Serene Highness the Prince of Leiningen and their Serene Highnesses Prince and Princess Victor of Hohenlohe-Langenburg and the Countesses Gleichen, and Count Gleichen.<ref>"Garden Party at Marlborough House." ''Morning Post'' 15 July 1890, Tuesday: 5 [of 8], Col. 3a–7c [of 7]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.co.uk/viewer/bl/0000174/18900715/044/0005. Same print title and p.</ref></blockquote> === 19 July 1890, Saturday === ==== Wedding of James Francis Harry St. Clair-Erskine and Violet Aline Vyner ==== This report from the ''Fife Free Press'' is missing a big piece of the 2nd paragraph, where the bridesmaids' and bride's dresses are described, because the page was damaged. The digitized copy is also generally poor.<blockquote>On Saturday forenoon, in Michael’s Church, Chester Square, London, was celebrated the marriage of Lord Loughhorough, eldest son of the Earl of Rosslyn with Miss Violet Aline Vyner, younger daughter of Mr R. C. Vyner, of Fairfield, Yorkshire. The chancel was beautifully decorated with palms and a profusion of lilies most artistically arranged. The Prince of Wales, Duke of Cambridge. Princess Mary Adelaide, Duchess and the Duke of Teck, and Princess Victoria, and the Right Hon. W. E. Gladstone were among those present. The wedding party began to arrive at 11 o’clock, the bridesmaids being early in attendance. They were the Ladies Sybil and Angela St Clair Erskine, sisters of the bridegroom; Lady Anne Lambton, Miss Musgrave, Miss Rachel Gurney, and Miss Fleming. They were charmingly dressed in soft cream crepon, with violet velvet Zoave jackets, forming half sleeves and capes at the back, and pretty turn-down collars and cravats of white mosseline [mousseline?] chiffon, and the skirts were very plainly made. They wore large white hats lined with a band of violet velvet near the face, and trimmed on the crown with white ostrich plumes, a bunch of violets fastening the brim at the back. Each wore a brooch — the St Clair cross in rubies and diamonds set in a circle of the latter, and surmounted by a baron’s cornet of the same precious stones — the gift of the bri[degroom]; and carried a bouquet of Marechal Niel [roses?] ...ging sprays of the same, and tied w... ribbons. The bride entered the ... eleven o’clock, being received at ... father, who led her to the cha... her away. The service be... procession was preceded up ... choir, who sang "The voic..." The bride’s dress was ... with a long court train, ... white velvet being embro... ...und the train, and fasten... ...ver true lover’s knot. The picture... ...gh silver waistband, had full slee... mousseline chiffon; and a small ... blossoms was most becomingly arra... with a long tulle veil. The Earl of Chesterfield discharged the duties of best man. The Rev. Canon Fleming, Chaplain in Ordinary to the Queen and Vicar of St Michael's, performed the marriage rite, assisted by the Rev. Edgar Sheppard, Sub-Dean of the Chapels Royal, and the Rev. J. Thomson, of Rosslyn, near Edinburgh. The hymn “Thine for ever! For of love,” was sung the end of the service. Canon Fleming afterwards delivered a most impressive address. After the benediction the clergy and bride and bridegroom passed to the vestry, the Prince of Wales following with Mrs Vyner. Pretty wedding favours of orange blossoms, Parma violets, and white heather were then distributed amongst the congregation. Mr and Mrs Vyner afterwards welcomed the wedding party at Ashburnham House, Dover-street. The ''dejeuner'' was served in three rooms, one being reserved for the bride and bridegroom and the Royal party. The table in the latter room was decorated with several of Mr Vynet's racing trophies. The band of the Grenadier Guards performed in the garden during the reception. The Prince of Wales, Duke of Cambridge, the Duke and Duchess of Teck and Princess Victoria were present at the breakfast, and among the general company were Count Munster and Countess Maria Munster, the Marchese and Marchesa de Montagliari, the Marquis and Marchioness of Ripon, the Marquis and Marchioness of Stafford, the Marquis of Cholmondeley, the Marquis of Northampton, Maria Marchioness of Ailesbury, the Dowager Marchioness of Conyngham and Lady Blanche Conyngham, the Marchioness of Downshire, the Countess of Rosslyn, Earl and Countess Compton, the Earl of Feversham, the Earl of Durham, the Countess of Coventry and the Ladies Coventry, Countess Howe and Ladies Curzon, the Countess of Yarborough, the Earl of Clonmell, the Earl and Countess of Loudoun, the Countess of Kilmorey, Countess de Grey, Viscount Molyneux, the Bishop of Gibraltar and Mrs Sandford, Viscountess de Labrosse and Mdles. de Labrosse, Lord Greenock, Lord and Lady Algernon Lennox, Lady Lilian Wemyss, Lady Julia Wombwell and Miss Wombwell, Hon. Lady Campbell of Blythswood, Lady Constance Harris, Lady Florence Harris, Lord and Lady Burghley, Lady Dorchester, Lord Houghton, Lady Curzon, Lady Brougham and Vaux and Miss Musgrave, Baron de Hirsch, Helen Lady Forbes and the Misses Forbes, Baroness Burdett Coutts and Mr Burdett Coutts, M.P., Lady Astley, Lord and Lady William Nevill, Lord and Lady Brooke and Hon. Leopold and Hon. Marjorie Greville, Lady Dalton Fitzgerald and Miss Payne, Lord Elcho, Lady Willoughby de Eresby and the Misses Willoughby, Lady Ewart, Lady Hindlip, Lady Cecilia Rose, Lord Rowton, Lord Capell, Lady Mabel Compton, Lord and Lady Herries, Lady Sykes, Lord and Lady Alwyne Compton, Lady Ventry and Hon. Miss de Moleyns, Hon. Lady Knollys, Lady Manners, Hon. Lady Drummond and Misses Drummond, Hon. Sydney Greville, Hon. Assheton Harbord, Hon. Derek Keppel, Hon. Captain Bourke, Hon. Mrs Percy Mitford, Hon. Philip Harbord, Hon. and Rev. L. Tyrwhitt, Hon. Coralie Glyn, Hon. M. Lambton, Hon L. Greville, Hon. Alwyn Greville, Hon[.] Eva Greville, Hon. Frances Dawnay, Hon Evelyn Paget, Hon Mrs Algernon Grosvcnor, Hon and Mrs Lambton. Hon. Mrs Evelyn Pelham, Hon. Fitzroy St Clair Erskine, [[Social Victorians/People/Bourke|Hon. Mrs Algernon Bourke]], Hon. W. Maxwell, Hon. G. and Mrs Dawnay, Hon. Captain Lambton, General Sir Seymour Blane, Sir William Gordon Cumming, Sir Archibald and Miss Edmunstone, Sir Henry and Lady Meysey Thompson, Mrs Gladstone, Mr and Lady Margaret Cameron, Mr and Lady Florence Astley, Mr and Lady Elizabeth Melville Cartwright and Miss Melville Cartwright, General and Mrs Duff and Miss Duff, General Owen Williams, Colonel and Mrs Anstruther Thompson, Colonel Stopford Sackville, Colonel Craig, Colonel Brabazon, Colonel Forester, Colonel Stanley Clarke (in attendance on the Prince of Wales) and Miss Clarke, Major Davidson, Canon and Mrs Fleming, Captain St John Mildmay (in attendance on the Duke of Cambridge), Captain and Mrs FitzGeorge, Mrs William Portal, the Sub Dean of the Chapels Royal, Rev. W. M. and Mrs Wollaston, Rev. R. West, Mr and Miss Chamberlain. Mr and Mrs W. H. Grenfell, Mr Christopher Sykes, M.P., Mr Reuben Sassoon, Mr Arthur Sassoon, Mrs Bischoffsheim, Mr and Mrs Herbert Naylor Leyland, Dr and Mrs Anderson, Mrs Oswald, Mr and Mrs Surtees, Mr Fitzgerald, Mr and Mrs Menzies, Miss Willoughby and Miss Gertrude Willoughby, Mr Arthur Paget, Miss Christie, Mr Dowdall, Mrs Eastwood and the Misses Eastwood, Mr Frederick Warre, Mr William Williamson, Mrs Burton, Mrs Chaine, Captain and Mrs Livesey Wardle, Captain A. R. Hill, Miss Helby, Mrs and Miss Winslow, Mr and Miss Oswald, Mr Willoughby, Mr Quintin Hume, Mr F and Miss Fitzherbert, Mrs and Miss F. Hotham, Mr and Mrs Moreton Frewin, Mrs Charles Otway, Mr Calcraft, Mr Watson, Mr Fennick, Mr Montgomery, Mr Cecil Murray, Mr and Mrs Sneyd, Mr Leslie Stephen, Mr Edgar Sebright, Miss Fleetwood Wilson, Mrs and Miss Farmer of Nonsuch, Mr and Mrs Dennistoun and Miss Dennistoun, Mr and Mrs J. R. Lane Fox and Miss Lane Fox, &c. The bride and bridegroom left early in the afternoon for Easton Lodge, Dunmow, the seat of Lord and Lady Brooke, in Essex, where they will spend the honeymoon. The bride travelled in a costume of biscuit coloured armure silk, the top of the bodice and sleeves being of pale pink mousseline de soie, and the lower part of the former inserted with pink velvet ribbons to form a high band, Tuscan straw-hat trimmed with pink crepe de chine, and biscuit feathers. The presents exceeded four hundred in number. The Prince of Wales presented the bride with a trefoil moonstone and diamond brooch and the bridegroom with a sapphire and diamond pin. The Princess of Wales's gift the bridegroom was a silver-necked claret jug. The Duke of Cambridge gave an amethyst and diamond pendant, and the bridegroom a pair of silver gilt candlesticks; and Princess Mary and the Duke of Teck presented the bride with a silver sugar basin. The bridegroom’s gifts to the bride were a diamond and sapphire watch bracelet, a diamond half-hoop ring, diamond brooch with pearl centre, diamond and turquoise brooch, formed of the St Clair badge in rubies and diamonds set in a circle of diamonds, surmounted by a baron’s coronet in the same precious stones, a large salts bottle with two heart-shaped moonstones set with rubies and diamonds and a silver sugar basin. The bride presented Lord Loughborough with a turquoise and diamond stud. The Earl of Rosslyn presented the bride with diamond necklet. The Countess of Rosslyn’s gifts were diamond orchid brooch and a pink feather fan. Mr R. C. Vyner’s gifts to his daughter were a diamond and pearl tiara and gold mounted dressing case, and Mrs Vyner gave her a sapphire and diamond ring. The Marchioness of Stafford gave a ruby and diamond pin; Lady Mary Vyner antique diamond tiara; the Ladies Angela and Sybil Erskine sapphire and diamond bracelet; Hon. Fitzroy St Clair Erskine with "1890" in rubies and diamonds; Lord and Lady A. Compton large diamond star; the Earl of Rosslyn presented his son with a large silver bowl and two silver dishes; the Countess of Rosslyn's present was a travelling bag; Mr Vyner gave him a luncheon basket; Mrs Vyner a silver ''entree'' dish; the Marchioness of Stafford case containing silver coffee and tea pots, urn and stand, sugar basin, and cream jug; Lord and Lady Brooke four antique silver sauce boats; Lord and Lady Algernon Gordon ['''Col. 1c–2a'''] Lennox three antique silver ''entree'' dishes. The Earl of Rosslyn's Fifeshire tenants presented Lord Loughborough with a beautiful antique silver bowl, two antique silver dessert dishes, and two antique sugar castors; and to the bride they gave an antique silver tea service. The congregation of Rosslyn Chapel presented the bridegroom with a complete and elegant writing set, whilst Lord Rosslyn's servants gave him a silver inkstand and pair of silver candlesticks. Mr Vyner's servants presented the bride with a silver salver and six ''liqueur'' cups. The servants of Newby Hall gave a silver coffee pot, and Mr Vyner’s Cheshire tenants presented a case containing silver tea pot, sugar basin, and cream jug. The bride also received from the Duchess of Portland a travelling bag; the Duchess de Luynes, sapphire and diamond ring; the Duke of Westminister, Indian necklace; the Marquis of Northampton, diamond bracelet; the Marquis of Ripon, sapphire and diamond bracelet; the Marchioness of Ripon, turquoise and diamond bangle, the Earl of Durham, a diamond half hoop bracelet; Earl and Countess Cowper, a diamond "V V” brooch; Dowager Viscountess Downe, moonstone and diamond crescent; Lady Skyes [Sykes] ruby and diamond fish brooch; Lady Millbank, sapphire and diamond brooch Lord Douglas Compton, double heart brooch; Lord Herbert Vane Tempest, gold curb chain bracelet set with pearls; Earl and Countess Compton, bangle with “Vi” and “good luck” on it; the Duke and Duchess of St Albans, tea service with table; the Marchioness Conyngham, silver cream jug; the Marchioness of Tavistock, silver vase; the Countess of Rodin, a silver I bowl; the Countess of Yarborough, silver candlesticks; Viscountess Downe, silver tea caddie; Lady de Trafford, gold mounted salts bottle; the Hon. F. Dawnay, large silver candlesticks[;] Hon. F and Lady Lampton, travelling clock; Hon. W. Lambton, silver candlesticks; Sir R. and Lady Graham, silver salver; Sir Roderick and Miss Cameron, two silver dishes; General Williams, diamond bangle; Colonel and Mrs G. FitzGeorge, gold mounted bottle; Major and Mrs Egerton, pair of silver candlesticks; Major Stuart Wortley, diamond Swallow; Major Davidson, heart-shaped brooch in coral and diamonds; Captain and Lady Cecilia Rose, a brougham; Mr Beaumont, silver bowl; Miss Edmonstone, moonstone and diamond hat pins; Mrs Harris, sapphire and diamond bracelet; Mr Egerton, turquoise and diamond brooch; Sir Cecil Murray, sapphire and diamond pin; Mr A. Farquharson, diamond swallow brooch; Mr and Mrs Hulse, two small silver vases; Miss Fleetwood Wilson, diamond bangle; Mrs A. Wilson, tortoiseshell candlestick; Mr Quintin Hume, salts bottle mounted with diamonds and rubies; Miss Helbert, gold violet pin; Mr Chamberlain, pair of silver candlesticks; Hon. Arthur Coventry, gold mounted bottle with "Vi" in diamonds; Mrs Leopold de Rothschild, diamond hand brooch, together with a number of other gifts. Among the presents to the bridegroom were — from the Marchioness of Downshire, antique silver sugar sifter; the Marquis of Exeter, silver sandwich case; the Marchioness of Bath, antique Dutch silver box; the Marquis of Downshire, a gold pencil; Count Munster, cigarette case and match box; Count Alexander Munster, a hunting flask; the Countess of Lindsay, antique silver pen-tray; the Earl of Mar and Kellie, silver matchbox; the Earl and Countess of Loudoun, silver cigarette box; the Earl of Chesterfield, antique silver gilt inkstand; the Countess of Bradford, gold seal with agate; the Countess of Warwick, antique silver bowl; the Earl of Coventry, silver pen-tray; the Countess of Wharncliffe, two silver candlesticks; the Earl and Countess of Cromartie, two antique silver cups; Viscountess of Newport, silver paper knife; Mr and Mrs A. Sassoon, ruby and diamond pin; Lord John Cecil, silver salver; Lord and Lady Willoughby de Eresby, antique silver-mounted cruet stand; Lord William Nevtll, antique brandy carrier; Lady Margaret Spicer, silver match box; Lord Burghley, four silver salt cellars and spoons; Baron de Hirch [Hirsch?], silver inkstand; Lady W. E. Osborne Elphinstone, silver inkstand; Lord Kesteven, silver cream jug; Lord Capell, silver cigarette case; Lord and Lady Gerard, tortoiseshell and silver travelling clock; Lady Lilian Wemyss, silver cigarette case; Dad Alwyne Compton, umbrella containing matchbox and whistle; Lord and Lady Lennox, two antique silver ''entree'' dishes and bacon dish; Lord Burghersh, silver cigarette lighter; Lady Angela 8t Clair Erskine, four silver salt cellars; Lady Randolph Churchill, gold pencil case, with two sapphires; Lord Houghton, antique gold basket; Lady Sybil St Clair Erskine, umbrella; Lord and Lady Dorchester, large crystal seal; Hon. Derek P. Keppel, pair of silver candlesticks; Hon. E. and Mrs Pelham, silver inkstand; Hon. G. N. Curzon, silver gilt bowl; Hon. F. St Clair Erskine, four silver candle-sticks; [[Social Victorians/People/Bourke|Hon. A. and Mrs Bourke]], four small silver dessert dishes; Hon. Mrs Elliot Yorke, pair of silver candlesticks; Hon. Mr and Mrs L. Greville, tortoise-shell and silver box; Hon. R Somerset, diamond and pearl pin; Hon. G. H. Willoughby, silver ink-stand; Hon. H. and Mrs Grosvenor, umbrella; [[Social Victorians/People/Bourke|Hon. Mrs Algernon Bourke]], enamel and diamond pin; Captain Hon. Maurice Bourke, cigarette case and lighter; Hon. W. Maxwell, silver-backed clothes and hat brushes; Hon. Sidney Greville, saltspoons; Hon. M. C. Maxwell Scott, two silver ''menu'' plates; Hon. W. Edwardes, pin; [[Social Victorians/People/Greville|Captain Hon. A.]] and [[Social Victorians/People/Lady Violet Greville|Mrs Greville]], silver gilt bowl, fork, spoon, and ladle; Sir Frederick Milner, diamond and moonstone pin; Sir George Chetwynd, two long silver flagons; Sir M. and Lady Fitzgerald, two silver saltspoons; Sir N. Gordon Gumming, silver-handled paper knife, &c.<ref>"Marriage of Lord Loughborough with Miss Vyner." ''Fife Free Press'' 26 July 1890, Saturday: 2 [of 8], Col. 1a–2b [of 6]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.co.uk/viewer/bl/0001110/18900726/015/0002. Same print title and p.</ref> </blockquote> === 24 July 1890, Thursday === ==== Dinner and Dance Hosted by Lord Alington ==== Perhaps the date on this is uncertain, since the article in ''Truth'' would suggest it was held in late May or early June. The newspaper story in the ''Queen'' mentions another occasion in which the flowers were notable as well. From ''Truth'':<blockquote> But not a quarter of a mile distant [from a dinner and dance hosted by Lord Rothschild featuring Princess Louise and the Marquis of Lorne] a more important event was proceeding, for Lord Alington, having previously walked down the Row and invited his friends right and left to Alington House, South Audley-street, proceeded to give a dance which was honoured by the presence of the Prince and Princess of Wales, the Princesses Victoria and Maud, the Duke of Clarence, Princess Mary Adelaide, and Princess "May" and Prince and Princess Christian. This without exaggeration, with the exception of Lady Leconfield's, Lady Willoughby de Eresby's, and Lady Cadogan's, was the best ball hitherto given this season, and the prolific way ortolans [small songbirds regarded as a delicacy] were distributed at supper will long linger in the memories of those by whom these delicacies are cherished. One lady displayed her enthusiastic appreciation by devouring five of these, and it is to be hoped her devotion did not endanger her life. As for beauty, seldom before have so many pre-eminent for good looks been present at one gathering, as a mere enumeration of a few of these will prove. Of course the Duchess of Leinster heads the list, followed in quick succession by the Duchess of Portland, Lady de Grey, Lady Randolph Churchill, Lady Dudley, Lady Kilmorey, Lady Brooke, Lady de Trafford, Lady Helen Duncombe, Lady Hilda Dundas, Lady Sybil St. Clair Erskine, Lady Olivia Taylour, Miss Rachael Gurney, Lady Cardross, Miss Bourke, Lady Rose Leigh and her sister-in-law, Miss Leigh, Miss Berens (sister to Lady Cairns), Mrs. Ralph Sneyd, Lady Gerard, and a host of others far too numerous to mention. I often wonder that no painter has yet attempted to give us in one picture a permanent record of the chief beauties of our day. It would make a most interesting and exquisite group of lovely women, such as could not be found probably in any other country than this.<ref>Marmaduke, pseud. "Letters from the Linkman." ''Truth'' 12 June 1890, Thursday: 26 [of 56], Col. 1a–b [of 2]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.co.uk/viewer/bl/0002961/18900612/064/0026. Same print title, p. 1212.</ref></blockquote> From the ''Queen'':<blockquote>The P<small>RINCE AND</small> P<small>RINCESS OF</small> W<small>ALES</small> and the Princesses Victoria and Maud honoured L<small>ORD</small> A<small>LINGTON</small> by their presence at D<small>INNER</small>, at A<small>LINGTON</small> H<small>OUSE</small>, South Audley-street, on the 24th ult., when a distinguished party was present to meet them, including, among others, the Duke and Duchess of Leinster, the Marquis of Hartington, the Marquis and Marchioness of Ormonde, Maria Marchioness of Ailesbury, Earl and Countess Cadogan and Lady Emily Cadogan, the Earl Countess of Lucan and Lady Rosaline Bingham, the Earl of Hardwicke, the Countess of Dudley and Lady Edith Ward, the EarI of Chesterfield, the Earl of Stradbroke and Lady Hilda Rous, and Earl Annesley. Covers were laid for sixty. Lord Alington afterwards gave a dance to meet the Prince and Princess of Wales and their daughters. As on the previous occasion, the floral decorations were exquisite. The entrance hall and the approaches to the reception rooms were decorated with tall palms and a profusion of lilies, pelargoniums, ferns in every variety, and roses in every imaginable shade. The conservatories at the back were carpeted and furnished luxuriously, and blocks of ice, lighted by fairy lamps, were placed about with artistic effect, serving to keep the atmosphere cool and fresh. Feathery palms, hydrangeos [hydrangeas] and arums were here used freely, and a particularly pretty result was obtained by the windows being framed, one in a fringe of ferns and red pelargoniums, and the other in ferns and fuschias. The ballroom fireplaces were adorned on each side with palms reaching to the ceiling, the mantelpieces being hidden by a delicate arrangement of roses in various shades springing from banks of hydrangeas, calceolarias, pelargoniums, and marguerites, and the walls of the staircase leading from the conservatory to the ball-room were hung with half-balls of floral roses. The supper was served in the dining-room, the tables being embellished with the loveliest orchids and roses of the most delicate tints, intermixed with pancretia; the arrangement was so light and elegant that it was difficult to believe that hands had ever touched the flowers. On those tables with silver candelabra in the centre, the flowers were all pure white, and those having gold candelabra were treated with mauve orchids and the palest pink and yellow roses. A tent, arranged near the conservatory for the Prince of Wales, was draped with Oriental hangings, and outside were groups of flowers and myriads of fairy lamps. The company began to arrive at eleven o'clock, when dancing commenced to the strains of the Blue Hungarian Band. The Princess of Wales was dressed in white striped satin and silk, the front being embroidered in pale shades, and wore handsome diamond ornaments. The Princesses Victoria and Maud wore white tulle over satin, the front being sprinkled all over with tiny sprays of lilies of the valley, each laid on a single leaf. The Duchess of Wellington was in black satin, with a pink sash arranged very prettily across the back of the bodice, and falling to the feet; a cluster of pink flowers and a beautiful diamond spray were fastened in the front of the bodicea and a diamond rivière was arranged in the hair, a diamond necklace being also worn. The Duchess of Westminster was in white satin trimmed with gold embroidery, and veiled in white chiffon. The Marchioness of Ormonde wore white striped brocade and satin trimmed with white lace, and a splendid diamond tiara and other ornaments. Countess de Grey, palest blue satin, with front beautifully embroidered in beads, and a diamond and pearl coronet. Maria, Marchioness of Ailesbury, white brocade and lace, with splendid diamond and emerald ornaments. The Marchioness of Bath, cream an violet brocaded velvet, the front being covered with mauve [38, Col. 3c – 39, Col. 1a] violets. Lady Mary Mills, rose-pink satin, with front richly embroidered; Lady Cardross, white satin, trimmed round the bodice and train with silver embroidery; Lady William Nevill, pale yellow brocade, the front veiled with black net, trimmed up the side with jet leaves, and all round the skirt was a bordering of Maréchal Niel roses, over a flounce of black net; Countess Granville wore rich white brocade and beautiful jewels; the Countess of Sefton, black satin and diamonds; Viscountess Dungan, white mousseline de soie, the skirt edged with a deep flounce; Lady Brooke, pale blue satin, trimmed with silver; Lady Emma Crichton, white satin train, with front of white lisse, prettily embroidered in red; Lady Idina Brassey, pale mauve bengaline, with front of chiffon and a handsome diamon coronet; Lady Rose Molyneux, white cross crêpe de Chine, with a pale green sash, and prettily trimmed with pink roses; Lady Wimborne, pale grey satin; the Hon. Miss Guest, pink satin, veiled with white net, sparkling with silver; Lady Sarah Spencer Churchill, white satin, with a chiffon frill; Lady Chesham, white silk, with pink roses; the Countess of Normanton, pale grey satin, with front of fine old lace; Mrs Hulse, handsome white brocade, diamond tiara, &c.; Mrs Bischoffsheim, white silk, embroidered with silver, and trimmed round the bottom of the skirt and train with a ruche of pale yellow crèpe; the Hon. Muriel Brassey, white chiffon, over satin, slightly trimmed with pink; and the [[Social Victorians/People/Bourke|Hon. Mrs Algernon Bourke]] was in pink, with magnificent diamonds.<ref>"Entertainments, Balls, &c." ''The Queen'' 2 August 1890, Saturday: 38, Col. 3c – 39 [of 82], Col. 1a–1c [of 3]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.co.uk/viewer/BL/0002627/18900802/237/0038 and https://www.britishnewspaperarchive.co.uk/viewer/bl/0002627/18900802/237/0039. Print: ''The Queen, The Lady's Newspaper'', pp. 170–171.</ref></blockquote>This is the story from the ''Morning Post'':<blockquote>The Prince and Princess of Wales and the Princesses Victoria and Maud honoured Lord Alington by their company at dinner last evening at Alington House, South Audley-street. The guests present to meet their Royal Highnesses comprised the Duke and Duchess of Leinster, the Marquis of Hartington, the Marquis and Marchioness of Ormonde, Maria Marchioness of Ailesbury, Earl and Countess Cadogan and Lady Emily Cadogan, the Earl and Countess of Lucan and Lady Rosaline Bingham, the Earl of Hardwicke, the Countess of Dudley and Lady Edith Ward, the Earl of Chesterfield, Earl Annesley, the Earl of Stradbroke and Lady Hilda Rous, Lord and Lady Gerard, Lady Norreys, Lord Rowton, Lord Calthorpe, Lord Frederick Hamilton, Lord Charles Montagu, Lord Herbert Vane Tempest, Lord Arthur Grosvenor, Lady Lilian Wemyss, Colonel the Hon. Oliver Montagu, Sir John and Lady Lister Kaye, the Hon. Humphrey and Lady Feodore Sturt, the Hon. John Baring, the Hon. Henry and the Hon. Julia Stonor, the Hon. Gilbert Willoughby, Lady Suffield and Major-General Ellis, in waiting on the Prince and Princess of Wales; Sir Henry Calcraft, Mr. and Lady Rose Leigh, General and Mrs. Owen Williams, Mr. Mildmay, M.P., Mr. and Mrs. Arthur Sassoon, Mr. Montague Guest, Captain Orr-Ewing, Mrs. Bulkeley, Mr. Ricardo, and Mr. Caryl Craven. Lord Alington afterwards gave a dance expressly to meet the Prince and Princess of Wales. Among the company were— The Russian Ambassador, the Danish Minister, Prince Louis Esterhazy, Comte Costa de Beaunyardt, the Duchess of Buccleuch and Lady Evelyn Fitzmaurice, the Duchess of Westminster, the Dowager Duchess of Marlborough and Lady Sarah Spencer Churchill, the Duchess of Wellington and Lady Cardross, the Marquis and Marchioness of Granby and Miss Bourke, the Marchioness of Stafford and Lady Sybil St. Clair Erskine, the Marchioness of Bath and Lady Beatrice Thynne, the Marquis of Cholmondeley, the Marquese and Marquesa de Santurce and Lady Wilham Nevill, Countess Spencer, Countess Granville and Lady Victoria Leveson-Gower, Countess de Grey, the Earl of Dunraven, the Countess of Lathom and Lady Edith Wilbraham, the Countess of Enniskillen and Lady Christian Cole, the Earl of Ilchester, the Earl of Durham and Lady Anne Lambton, the Earl of Dalkeith and Lord Ernest Scott, the Countess of Sefton and Lady Rose Molyneux, Countess Howe and the Ladies Curzon, the Countess of Normanton and Lady Mary Agar and Miss Mary Liddell, Earl Craven, Viscount Clifden, Viscount Ennismore and Lady Beatrice Hare, Viscount Coke and the Hon. Violet White, Viscount and Viscountess Castlerosse and the Hon. Susan Baring, Viscountess Newport and the Hon. Miss Bruce, Viscount and Viscountess Melgund, Viscount and Viscountess Curzon, Viscount and Lady Violet Dangan and Lady Eva Wellesley, Viscount Dungarvan, Viscount Chelsea, Viscount Royston, Lady Hastings, Lord Capell, Lord and Lady Willoughby de Eresby and Hon. Margaret Willoughby, Lady Cloncurry and Hon. Miss Winn, Lord and Lady Brooke, Lady Wimborne and Hon. Miss Guest, Lord Sandhurst, Lord and Lady Edmund Talbot, Lord and Lady Alwyne Compton and Miss Gurney, Lord and Lady Chesham, Lady Rossmore and Miss Naylor, Lord Kenyon, Lord Garioch, Lady Alice Portal, Lady Margaret Levett and the Ladies Ashley, Lady W. Nevill, Lord Paulet, Lady Charles Beresford, Lady Forbes and Misses Forbes, Lady Claud Hamilton, Lord Carlow, Lady Mary Mills, Lord Lurgan, Lord Henry Vane Tempest, Lord and Lady Algernon Gordon Lennox, Lord Richard Nevill, the Hon. W. Coventry, the Hon. G. Joliffe, the Hon. Schomberg M'Donnell, the Hon. H. Coventry, Captain the Hon. E. Dawson, the Hon. Alistair and Mrs. Hay, the Hon. Mrs. Grosvenor, [[Social Victorians/People/Bourke|the Hon. Algernon and Mrs. Bourke]], the Hon. F. Dawnay, the Hon. E. J. Mills, the Hon. A. Johnstone, the Hon. Claude Hay, the Hon. Sidney Greville, the Hon. Mr. Dundas and Lady Hilda Dundas, the Hon. Thomas and Lady Idina Brassey and the Hon. Muriel Brassey, the Hon. Mr. Mansfield, Colonel the Hon. Henry Byng and Miss Byng, the Hon. Mrs. Oliphant, the Hon. Mr. Harbord, the Right Hon. Henry Chaplin, M.P., the Hon. G. Somerset, Sir William Gordon Cumming, Sir George Arthur, Sir Hubert Miller, Sir Charles Forbes, Sir William and Lady Eden, Sir George Chetwynd, Sir Frederick Johnstone, Sir John D. Poynder, Colonel and Lady Emma Crichton, the Hon. Miss Harbord, Captain and Lady Jane Combe, Colonel Paget, Captain Williams, Captain Ford, Captain Doyle, Captain Hanbury, Captain Campbell, Captain Constable, Captain Kinloch, Captain Longfield, M. Gutmansthal, Mrs. Bingham, Mr. Guthrie, Mrs. Arthur Paget, Mrs. Charles Wilson and Miss Wilson, Mr. Hulse, M.P., and Mrs. Hulse, Mr. de Murrieta, Mrs. Bischoffsheim, Mr. Spencer Portal, Mr. and Mrs. Gerald Paget, Mr. Leigh and Miss Leigh, Mr. Percy Daniell, Mr. Lister, Mr. Frederick Vincent, Mr. Cazalet, Mr. Alfred de Rothschild, Mr. John Savile Lumley, Mr. and Mrs Leopold de Rothschild, Mr. and Mrs. Skeffington Smith and Miss Taylor, Mrs. George Cavendish Bentinck, Mr. Alfred Farquhar, [[Social Victorians/People/Fanny Ronalds|Mr. Reginald Ronalds]], Miss Alice Ellice, Mr. George Marjoribanks, Mr. Wyndham, Mr. Dugdale, Mr. Montagu, Mrs. Sneyd, Mr. Wynn, Mr. Edward Hamilton, Mr. Murray Guthrie, Mr. George Lambert, Mrs. Sanford, Miss Mabel Forbes. Mr. Herbert Magniac, Mr. Bailey, Mr. Milner, Mr. Charles Kindersley, Mr. Beaumont, Mr. Walter Hervey, Mr. H. Hoare, Mr. Foley, Mr. Scott Murray, Mr. Coventry, Mr. Bertie, Mr. Jarvis, Mr. Guthrie, Mr. George Cavendish Bentinck, Mr. E. Charteris, Mr. Cholmondeley, Mr. Oswald Magniac, Mr. Cecil Campbell, Mr. and Mrs. Henry Oppenheim, Mr. Peploe, Mr. A. Charteris, Mr. Seymour Gore, Mr. Robert Antrobus, Mr. Elliot, M. de Champs, Mr. Wombwell, Mr. Charles Hoare, M.P., and many others.<ref>"Lord Alington's Ball." ''Morning Post'' 25 July 1890, Friday: 3 [of 8], Col. 5 b–c [of 7]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.co.uk/viewer/bl/0000174/18900725/014/0003. Same print title and p.</ref></blockquote> ==August 1890== ===6 August 1890, Friday=== ==== Beautiful Women ==== The ''Lancaster Observer and Morecambe Chronicle'' reprinted a story from ''Vanity Fair'' about "Beautiful Women":<blockquote>Beautiful Women. — ''Vanity Fair'' asks what country in the world can show a more beautiful bevy of women than England? When Lady Helen Vincent, with her sister, Lady Cynthia Graham; when Lady Warwick with her sisters, the Duchess of Sutherland and Lady Westmorland; and when Lady Mar and Kellie, Lady de Trafford, Princess Pless, Lady de Gray[,] Lady Naylor-Leyland, the Duchess of Portland, Lady Alington, Lady Sophie Scott, Lady Chelsea, [[Social Victorians/People/Bourke|Lady Algernon Bourke]], Lady Henry Bentinck, Mrs. Willie Grenfell, Mrs. Rupert Beckett, Mrs. Arthur Paget, and Countess Clary are gathered together it is a sight to make an old man young; while Mrs. Gerard Leigh and her sister, Lady Yarborough, and Lady Powis, Lady Norreys, Mrs Farquharson, Mrs. Willie James, Lady Dalkeith, Mrs. Pretyman, Mrs. Gervase Beckett, Lady Rossmore, Lady Sarah Wilson, Lady Colebrook, Lady Hartopp, Mrs. Willie Walker, and Lady Milton are almost equally admired. The many pretty girls include Miss Enid and Miss Muriel Wilson, who still head the list of the unmarried beauties, Lady Beatrice Butler, Lady Alexandra Hamilton, Miss Kennard, Miss Madeline Bourke, and Miss Leila Crichton; while among the debutantes Lady Evelyn Crichton and Lady Vivian's daughters have had a great success, and Lady Alice Montagu, petite and charmingly pretty, has been so much admired. The daughters of Lady Gosford, Lady Verulam, Lady Leitrim, Lady Inchiquin, and Lady Grey have also been admired, as well as Lady Helen Stewart, Lady Katherine Scott, and Miss Chaplin.<ref>"Beautiful Women." ''Lancaster Observer and Morecambe Chronicle'' 6 August 1897, Friday: 2 [of 8], Col. 5b [of 8]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.co.uk/viewer/bl/0001804/18970806/023/0002. Same print title and p.</ref></blockquote> ===25 August 1890, Monday=== Summer Bank Holiday ==September 1890== ==October 1890== ===22 October 1890, Wednesday=== Arnold Dolmetsch went to the Reading Room (Campbell 22). ===25 October 1890, Saturday=== [[Social Victorians/Loder De Vere Beauclerk Wedding|Loder—De Vere Beauclerk Wedding]] ===31 October 1890, Friday=== Halloween. ==November 1890== ===5 November 1890, Wednesday=== Guy Fawkes Day ===19 November 1890, Wednesday=== Arnold Dolmetsch, with some of his students and his daughter Helene, provided musical illustrations for a lecture given by Dr. Frederick Bridge on "Mozart as Teacher," probably at Gresham College, where Bridges was professor (Campbell 34). ===21 November 1890, Friday=== Dr. Frederick Bridge's last fall 1890 lecture at Gresham College, for which Dolmetsch provided illustration. Campbell says, "it is, in fact, the first record in modern times of music by Byrd, Dr. Bull, Jenkins, Simpson, Lawes, Locke and Purcell being played 'on the instruments for which it was written'" (Campbell 34). ===25 November 1890, Tuesday=== Arnold Dolmetsch got a three-month pass to the Reading Room and "thereafter held yearly tickets until 1916" (Campbell 22). ==== 1890 November 29, Saturday ==== ===== [[Social Victorians/Dudley-Beckwith Wedding 1890-11-29|Wedding of Francis Dudley, Lord Leigh and Héléne Forbes Beckwith]] ===== ==December 1890== Sometimes in December 1890, [[Social Victorians/People/William Robert Woodman|William Woodman]], one of the founding members of the [[Social Victorians/Golden Dawn|Golden Dawn]], died (Gilbert 86 12). === 4 December 1890, Thursday === ==== [[Mure-Portal Wedding 1890-12-04|Wedding of Miss Mure and Mr. S. J. Portal]] ==== ===19 December 1890, Friday=== "The eleventh annual ''Truth'' Toy Exhibition for the children in London hospitals, workhouses, and infirmaries was held at the Grosvenor Gallery, Bond-street, on Dec. 19 and 20. There are over 22,000 children in these institutions, and each of them has a separate toy, besides the large and more expensive toys which are presented for the general use of the inmates. A special feature of the show was the dolls dressed by lady readers of ''Truth''. Several special donations in connection with the fund have been made, the principal of which is that of 10,200 new sixpences sent for distribution by the same liberal donor who has given a similar present on former occasions; while Mr. Tom Smith has had specially made, and has forwarded for distribution, over 22,000 crackers; and Mr. Horniman (as stated in our last issue) has given to the adults in hospitals and workhouses 1200 packets of tea, to be given to them as Christmas boxes." (Illustrated London News (London, England), Saturday, December 27, 1890; pg. 806; Issue 2697, Col. B) ===20 December 1890, Saturday=== "In order that the adults connected with the hospitals and workhouses may participate in the good things given to the children in the ''Truth'' toy distribution, Mr. F. J. Horniman, of Wormwood-street, City, has sent Mr. Labouchere 1200 packets of tea to be given to them as a Christmas box." (Illustrated London News (London, England), Saturday, December 20, 1890; pg. 774; Issue 2696, Col. B) From the ''Times'', 22 December 1890, "The Late Sir Edgar Boehm": <blockquote>On Saturday, in accordance with the special request of the Queen, the late Sir Edgar Boehm, R.A., was buried in St. Paul’s Cathedral, in the south aisle of the crypt, the spot being known as “The Painters Corner.” [new paragraph] The funeral cortége left the residence of the deceased at about 11 o’clock, there being five mourning and several private carriages. In the first carriage were the chief mourners, Sir Edgar Collins Boehm, the only son of the late baronet, and Mr. Conrad Herapath. The second and third carriages were occupied by Sir Frederic Leighton, P.R.A., Sir Nigel Kingscote, Mr. Richard Mills, Colonel Francis Baring, Mr. Alma-Tadema, R.A., Sir R. H. Collins, Mr. Edward J. Poynter, R.A., and Mr. Duncan MacGregor, all of whom subsequently, at the cathedral, acted as pall bearers. The fourth carriage contained representatives of the Council of the Royal Academy – Mr. Edwin Long, R.A., Mr. J. B. Burgess, R.A., Mr. F. Goodall, R.A., and Mr. Beavis. In the fifth carriage were the following members of the professional staff of the deceased – Mr. R. Glassby, Mr. E. Lantéri, Signor Finili, and Herr Gross. The cortége stopped for a few moments at the Royal Academy, in order that it might be joined by two carriages containing other representatives of the institution. Leaving Piccadilly, the route taken was Waterloo-place, Pall-mall, Cockspur-street, the Strand, Fleet-street, and Ludgate-hill, the cathedral being reached about noon. The procession was met at the great west door by Canon Gregory, the Archdeacon of London, the Rev. Dr. Baker, Minor Canons Milman, Russell, and Kelly, and the choir, who had a few minutes previously left the vestry; by Major Bigge, Equerry to the Queen, representing her Majesty; Colonel Stanley Clarke, who attended on behalf of the Prince and Princess of Wales; and Colonel W. J. Colville, representing the Duke of Edinburgh. The [[Social Victorians/People/Princess Louise|Princess Louise]] (Marchioness of Lorne) attired in deep mourning, and accompanied by [[Social Victorians/People/Arthur Collins|Lieut.-Col. Arthur Collins]] and Lady Sophia Macnamara, arrived at the cathedral a few minutes before 12 o’clock, and was conducted to a seat in the south side of the nave, close to the late Sir Edgar Boehm’s two daughters, upon whom her Royal Highness had called earlier in the morning. As the procession came slowly up the nave towards the chancel, “I am the resurrection of life” and other sentences of the burial service were chanted to music by Dr. Croft. The coffin, which was completely hidden by splendid wreaths, was preceded by the choristers and the clergy. Then followed Sir E. C. Boehm, with Mr. Conrad Herapath and Mr. Alfred Gilbert, A.R.A., the officers and council of the Royal Academy, and members of the deceased’s studio. The coffin was deposited upon a bier, which had been placed under the dome in front of the opening into the crypt, through which the body was subsequently lowered. The mourners having been conducted to the seats which had been reserved for them, and the clergy and choir having proceeded to their places in the chancel, Psalms xxxix. and xc. Were sung to music by Purcell and Felton, followed by Spohr’s anthem, “Blest are the departed,” and the lesson 1 Cor. Xv. 20, which was read by Canon Gregory. Whilst the hymn “Days and moments quickly flying” was being sung the Archdeacon of London and Minor Canon Milman proceeded from the chancel and took up positions by the side of the coffin. The remainder of the service preceding and following the lowering of the body into the crypt was read by Minor Canon Milman, and the collect was impressively recited by Archdeacon Sinclair. The late Dr. Newman’s beautiful hymn, “Lead kindly light,” was afterwards sung by the choir, and the service was brought to a close by Beethoven’s Funeral March, which was played in compliance with the special request of her Majesty, at whose desire also Chopin’s Funeral March had preceded the service. Dr. Martin was the organist. While Beethoven’s march was being played the son and daughters of the late “Sculptor in ordinary to her Majesty,” together with other mourners, descended the crypt by the door near Howard’s monument, and saw the coffin for the last time. It bore the following inscription:- “Joseph Edgar Boehm. Born July 6, 1834; died at his work December 12, 1890. Thy will be done.” The coffin had already been deposited in the brick grave prepared for it, which is next to that of Sir Edwin Landseer. Immediately around it lie the remains of painters and sculptors of bygone days – Sir Joshua Reynolds, James Barry, Benjamin West, Henry Fuseli, Sir Thomas Lawrence, J. M. W. Turner, and John Henry Foley, while within half-a-dozen yards is the tomb of the great architect of the cathedral, Sir Christopher Wren. The coffin as last seen was covered by the floral tributes of loving friends, the symbolic laurel wreath forwarded by her Majesty surmounting them. This bore the inscription, “A tribute of gratitude for many beautiful memorial works executed for her. From Victoria, R. I.” Attached to the beautiful wreath sent by the Prince and Princess of Wales were the words, “A token of sincere regard and friendship.” Wreaths were forwarded by other members of the Royal Family, by Sir John and Lady Millais, Lord and Lady Reay, the Countess Sydney, Lord and Lady de Vesci, Mr. Henry Irving, Mr. and Mrs. Bancroft, by members of the council, students and officers of the Royal Academy, the Society of Artistic Sculptors (Vienna), and by the London Hungarian Association." (http://glassby.com/Chapter1.htm) </blockquote> ===24 December 1890, Wednesday=== "The people of South London and adjacent suburbs have to be grateful to Mr. Frederick Horniman, a well-known City merchant residing at Dulwich, for a munificent and beneficial Christmas gift. This gentleman has, during thirty years, formed a collection, worth above £100,000, of specimens of art, European, Indian, Chinese, and Japanese, also of decorative manufactures, and of ethnology and natural history, and rare books and manuscripts, at Surrey House, Forest Hill, which he intends to present to the public. The museum was opened by Sir Morell Mackenzie on Wednesday afternoon, Dec. 24. It already comprises twenty-four rooms, containing many beautiful specimens of horse and chain armour, Elizabethan bed-room furniture, an old English parlour and pantry, an Oriental armoury, a bible and manuscript room, an Egyptian gallery, and ethnographical saloon, a book and embroidery saloon, a porcelain and glass room, and a zoological saloon, with two live Russian bears and a monkey. We may describe the museum further, after another visit. Our Artist has sketched, in the ethnograhical saloon, an idol's shrine, made of cocoanut-fibre, from Fiji. Mr. Horniman, in acknowledging a vote of thanks, said that in an adjoining house he had accumulated a vast library of bibles and entomological works and specimens. It was his intention to build a hall at the back of the present building to contain a thousand persons, while the galleries would contain a library, and a stage would be provided, so that both eye and ear could be amused. He also contemplated buying sufficient land to enable a public body to erect class-rooms and gymnasia. Three cheers were given for Mr. Horniman, and the company proceeded to inspect the museum." "(Mr. F. Horniman's Museum, Forest Hill." Illustrated London News (London, England), Saturday, January 03, 1891; pg. 7; Issue 2698, Col. C) ===25 December 1890, Thursday=== Christmas Day ===26 December 1890, Friday=== Boxing Day ==Works Cited== *"Besant Chronology.pdf." From Anderson, Nancy Fix, Walter L Arnstein, Deborah Logan, and Susie L Steinbach, Volume Editors. Lives of Victorian Political Figures, Part III: Queen Victoria, Florence Nightingale, Annie Besant and Millicent Garrett Fawcett by their Contemporaries. Volume 3 of Lives of Victorian Political Figures. Series Editors, Nancy LoPatin-Lummis and Michael Partridge. London: Pickering and Chatto, 2008. *Crawford, Elizabeth. The Women’s Suffrage Movement: A Reference Guide, 1866–1928. Google Books. Accessed 14 October 2010. pn3boggrfbavgeq2amcq9qste3qqx14 0 264381 2835226 2834270 2026-09-30T22:03:05Z Scogdill 1331941 2835226 wikitext text/x-wiki [[File:Viscount Mandeville Vanity Fair 1882-04-22.jpg|alt=Old drawing for a magazine of an aristocratic man in a formal suit|thumb|"Kim," Viscount Mandeville, 1882]] == Overview == The Mandeville who was in a relationship with music-hall and vaudeville star Bessie Bellwood was Kim (George Victor Drogo) Montagu, 8th Duke of Manchester (17 June 1853 – 18 August 1892). He was Viscount Mandeville from 18 August 1855 (when his grandfather died) to 22 March 1890 (when his father died).<ref name=":1" /> When he succeeded to the dukedom in 1890, he ended his relationship with Bellwood. His father was the 7th Duke and his mother was [[Social Victorians/People/Louisa Montagu Cavendish|Louise Cavendish]], "double Duchess" of [[Social Victorians/People/Manchester|Manchester]] and then [[Social Victorians/People/Devonshire|Devonshire]]. Viscount Mandeville (right) was "Man of the Day" (#255) for ''Vanity Fair'', drawn by Leslie Ward ("Spy").<ref>"Viscount Mandeville Vanity Fair 1882-04-22.jpg." Wikimedia Commons. https://commons.wikimedia.org/wiki/File:Viscount_Mandeville_Vanity_Fair_1882-04-22.jpg (retrieved 8 September 2026).</ref> == Also Known As == *Family name: Montagu *The title Viscount Mandeville is a courtesy title for the heir apparent and eldest son of the [[Social Victorians/People/Manchester |Duke of Manchester]]. This title is one of only 2 (for the heir apparent of a duke) that is below the rank of Earl (the other is the heir apparent of the Duke of Somerset). (Is Mandeville a toponym?) *Viscount Mandeville **"Kim" (George Victor Drogo) Montagu [8th Duke], (18 August 1855 – 22 March 1890) **[[Social Victorians/People/William Angus Drogo Montagu|William Angus Drogo Montagu]], 9th Duke (22 March 1890 – 18 August 1892) **Alexander George Francis Drogo Montagu (2 October 1902 – 9 February 1947)<ref>{{Cite journal|date=2020-10-15|title=Alexander Montagu, 10th Duke of Manchester|url=https://en.wikipedia.org/w/index.php?title=Alexander_Montagu,_10th_Duke_of_Manchester&oldid=983660353|journal=Wikipedia|language=en}}</ref> *Viscountess Mandeville **Consuelo Iznaga y Clement Montagu [8th Duchess] (22 May 1876 – 22 March 1890) **Helena Zimmerman Montagu (14 November 1890 – 18 August 1892) *Lord Kimbolton (Baron Kimbolton of Kimbolton is the courtesy title for the heir presumptive, the heir apparent's eldest son, so the son of Viscount Mandeville<ref>{{Cite journal|date=2026-09-21|title=Duke of Manchester|url=https://en.wikipedia.org/w/index.php?title=Duke_of_Manchester&oldid=1375987697|journal=Wikipedia|language=en}}</ref>) ** [[Social Victorians/People/William Angus Drogo Montagu|William Angus Drogo Montagu]], 9th Duke (1877 – 22 March 1890) == Acquaintances, Friends and Enemies == === "Kim" Montagu, 8th Duke, Lord Mandeville until 1890 === ==== Friends ==== * Edward Russell, 24th Baron de Clifford * Derrick Westenra, 5th Baron Rossmore * Francis Needham, 3rd Earl of Kilmorey === Consuelo Iznaga y Clement Montagu === ==== Friends ==== *Consuelo Iznaga y Clement Montagu was in the intimate circle of [[Social Victorians/People/Albert Edward, Prince of Wales |Albert Edward, Prince of Wales]]. ==Organizations== === "Kim" Montagu, 8th Duke, Lord Mandeville until 1890 === * Eton<ref name=":1" /> === Consuelo Iznaga y Clement Montagu === * Consuelo Iznaga y Clement Montagu was a member of the New York City social set called the Buccaneers when she was a teenager.<ref name=":0">{{Cite journal|date=2020-10-06|title=Consuelo Montagu, Duchess of Manchester|url=https://en.wikipedia.org/w/index.php?title=Consuelo_Montagu,_Duchess_of_Manchester&oldid=982192002|journal=Wikipedia|language=en}}</ref> Edith Wharton is said to have take details from the 8th Duke's marriage ''The Buccaneers''.<ref name=":1">{{Cite journal|date=2020-10-06|title=George Montagu, 8th Duke of Manchester|url=https://en.wikipedia.org/w/index.php?title=George_Montagu,_8th_Duke_of_Manchester&oldid=982188929|journal=Wikipedia|language=en}}</ref> == Timeline == '''1855 August 18''', the 6th Duke died. The families "placed in mourning":<blockquote>He is succeeded in the Dukedom by his eldest son, Viscount Mandeville, M.P. By the melancholy event the families of the Marquess and Marchioness of Tweeddale, the Duchess of Wellington, the Duke of Montrose, Lord and Lady Olivia Ossulston [?], Lady Eliza [Elisa?] Steele, the Duke of Richmond, the Countess of St Germans, Lady Sophia Cecil, and many others of rank, are placed in mourning.<ref>"Death of the Duke of Manchester." ''Edinburgh Evening Post and Scottish Standard'' 22 August 1855, Wednesday: 2 [of 4], Col. 5c [of 8]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0001177%2F18550822&page=2&article=025&stringtohighlight=mandeville+viscount. Print title ''Edinburgh Evening Post and Scottish Record''; n.p.</ref></blockquote>'''1855 October 11, Wednesday''', H. I. Cridland says in a "Notice,"<blockquote>I will hold Audit Days at Lyttelton, on Wednesday, 11th October, for the receipt of rents and other monies due to the 25th of September, on account of the Soames, Jackson, Ecclesiastical, and Lyttelton Trust Estates, the lands of Lord Mandeville, Lady Emily Bathurst, Lady Olivia Sparrow, Rev. J. P. Rhoades, Rev. Charles Hodge, Dr. Merrion C. T. Maunsell, George Hart, late William Draper, and J. E. Fitz Gerald, Esqrs. ... Tenants are requested to present their last receipt.<ref>"Notice." ''Lyttelton Times'' 6 October 1855, Saturday: 1 [of 10], Col. 3c [of 3]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0003346%2F18551006&page=1&article=004&stringtohighlight=mandeville+viscount. Newspaper title ''The Lyttelton Times'', n.p. </ref></blockquote>This notice was repeated in the ''Lyttelton Times'' on 29 December 1855. '''1855 October 20, Saturday''', the [[Social Victorians/People/Wilton|Earl and Countess of Wilton]] hosted a [[Social Victorians/Timeline/1850s#1855 October 20, Saturday|house party at Heaton Hall]], with a visit to a silk mill in town. [[Social Victorians/People/Louisa Montagu Cavendish|Luise, Duchess of Manchester]] was present with the Duke and their son Lord Mandeville (Kim, later 8th Duke), who was 2 years old. '''1876 May 22''', Consuelo Iznaga y Clement and "Kim" (George Victor Drogo, 8th Duke) Montagu married in Grace Church, New York City.<ref name=":0" /> '''1890 January 29, Wednesday''', Consuelo Lady Mandeville was a guest at the house party around and the wedding of [[Social Victorians/Timeline/1890#1890 January 29, Wednesday|Miss Clarita de Murietta and the Duc de Santona]]. She had her eldest son with her, Lord Kimbolton (the 9th Duke of Manchester), as well as her mother in law, [[Social Victorians/People/Louisa Montagu Cavendish|Louise, Duchess of Manchester]]. [[Social Victorians/Santurce Murrieta Wedding 1890-01-29|Santurce Murrieta Wedding 1890-01-29]] '''1890 February 6, Thursday''' '''(shortly before 6 February)''', Kim Lord Mandeville attended a [[Social Victorians/Timeline/1890#1890 February 6, Thursday|boxing match fought by the prize-fighter Pete Jackson]] at the New Pelican Club. '''1890 February 8, Saturday''', Kim Lord Mandeville was among the [[Social Victorians/Timeline/1890#1890 February 8, Saturday|recent arrivals at Brighton]] although apparently after the most notable had already left. Certainly he does not appear to have been at the party the next evening that the Prince of Wales attended. '''1890 February 9, Sunday''', the Prince of Wales came after one of Consuelo's dinner parties:<blockquote>Lady Mandeville, who has been giving a series of small dinners in her house in Cumberland Place, had a dinner on Sunday. The Prince of Wales came in after dinner to meet a small party.<ref>"Society Gossip. (From ''The World''.)." ''Leighton Buzzard Observer and Linslade Gazette'' 11 February 1890, Tuesday: 6 [of 8], Col. 6b [of 7]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0001091%2F18900211&page=6&article=106&stringtohighlight=mandeville+viscount. Print title: ''The Leighton Buzzard Observer'', p. 6. </ref></blockquote>'''1890 February 24, Monday''', Consuelo Lady Mandeville attended [[Social Victorians/Timeline/1890#24 February 1890, Monday|Lilly Langtry's performance as Rosalind in As You Like It at the St. James's Theatre]]. '''1890 February 25, Tuesday''', Consuelo Lady Mandeville attended a [[Social Victorians/Timeline/1890#25 February 1890, Tuesday|party hosted by Mrs. Adair]]. Viscount Mandeville is not listed among those who attended. '''1890 March 4, Wednesday''', Consuelo's brother Fernando Yznaga married New York "beauty and society leader" Miss Mabel Wright.<ref>"Personal." ''American Register'' 22 March 1890, Saturday: 5 [of 8], Col. 5a [of 7]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0003338%2F18900322&page=5&article=070&stringtohighlight=mandeville+viscount. Same print title and p.</ref> Presumably at least Consuelo was there? '''1890 March 10, Monday''', the Prince and Princess of Wales gave a [[Social Victorians/Timeline/1890#10 March 1890, Monday10 March 1890, Monday|dance at Marlborough House in honor of their wedding anniversary]]. The Viscountess Mandeville is listed among the guests invited, but the Viscount is not mentioned. '''1890 March 22, Saturday''', the Portsmouth ''Evening News'' expressed outrage about a man with a reputation like Kim's becoming 8th Duke of Manchester:<blockquote>While the House of Commons were debating the necessity for a House of Lords, the Duke of Manchester was on his death bed in Naples. There is more in the incident than appears at first sight, for Viscount Mandeville succeeds to the Dukedom, with the attendant rights of presentation to seven livings and the privilege of mutilating or rejecting Bills demanded by the people and passed by their representatives in the Commons.<p> It will hardly be urged by the moat zealous advocate of the Upper Chamber, as at present constituted, that the new Duke of Manchester, ''nee'' Viscount Mandeville, will bring much dignity, wisdom, or weight to the House of irresponsible legislators. This nobleman has had a merry time. The one sensible thing he did was to marry a charming and accomplished American lady, who, by consenting to share the name of Mandeville has kept its head above water. Viscount Mandeville himself has a weakness for bankruptcy proceedings, rows with cabmen, which music hall ladies come forward to take his part, and the class of events generally which do not approve themselves to the minds of the ordinary Briton. It is possible that Lord Mandeville may now discover that he has sown his wild oats, and may settle down with his beautiful and popular wife to the enjoyment of his  25,000 acres of land and £38,000 a-year. We have not to do with what Lord Mandeville may be. Our simple duty is to point out that it is an outrage on common decency and common sense that a man bearing the reputation of Lord Mandeville should have the right to step into the House of Lords whenever a vote is needed to swell the prejudice or sustain the selfishness that find among the Peers their natural home.<ref>"To-Day." ''Portsmouth Evening News'' 22 March 1890, Saturday: 2 [of 4], Col. 1c [of 6]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0000290%2F18900322&page=2&article=001&stringtohighlight=mandeville+viscount. Print title: ''The Evening News'', n.p.</ref></blockquote>The ''Birmingham Daily Mail'' had a similar opinion, though perhaps slightly more optimistic:<blockquote>The Duke of Manchester, who expired last night at Naples, cannot be said to have been much of a public man. He led a quiet, retired life, and the announcement of his death would, if Lord  Mandeville were not heir to the title, arouse but little interest. Lord Mandeville is, unfortunately for himself, more widely known than his father was. He developed tastes for gambling, with disastrous financial results, as the details of his bankruptcy made public last year, and more recently, his name has been publicly associated with those of prizefighters and music-hall singers. Altogether, he can hardly be termed a credit to the aristocracy of England, but the higher position to which he will now attain may cause him to alter his ways and try redeem the errors of the past.<ref>"Notes and News." ''Birmingham Mail'' 22 March 1890, Saturday: 2 [of 4], Col. 3a [of 8]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0000644%2F18900322&page=2&article=027&stringtohighlight=mandeville+viscount. Print title: ''Birmingham Daily Mail'', n.p.</ref></blockquote>On the same day, Consuelo's brother and new wife were reported to apparently be immigrating to the UK:<blockquote>Among the immigrants, says a London lady correspondent, is a New York belle who has just been married to Mr. Ferdinand Yznaga, brother to Lady Mandeville and of Lady Lister-Kaye. Young Mrs. Yznaga will enter London society under the wing of her sister-in-law, Lady Mandeville, and is expected to make as great a furore as did Mrs. Langtry a few seasons ago. Mr. Yznaga married a sister-in-law of Mr. Vanderbilt, who divorced him two years ago.<ref>"An American Belle." ''Huddersfield and Holmfirth Examiner'' 22 March 1890, Saturday: 6 [of 16], Col. 4a [of 6]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0003869%2F18900322&page=6&article=006&stringtohighlight=mandeville+viscount. Print title: ''The Huddersfield Examiner'', p. 6.</ref></blockquote>'''1890 November 14''', William Angus Drogo Montagu (9th Duke) and Helena Zimmerman married secretly, in London. '''1897 July 2''', the Duke and Duchess of Devonshire ( [[Social Victorians/People/Louisa Montagu Cavendish|Luise Friederike Auguste Gräfin von Alten Montagu Cavendish]] and [[Social Victorians/People/Spencer Compton Cavendish|Spencer Cavendish]]) hosted the [[Social Victorians/1897 Fancy Dress Ball|Duchess of Devonshire's fancy-dress ball]] at Devonshire House. Lord Charles Montagu, likely Charles William Augustus Montagu, attended, as did [[Social Victorians/People/William Angus Drogo Montagu|William Angus Drogo Montagu]]. == Demographics == ===Nationality=== *Consuelo Iznaga y Clement was Cuban-American. *Helena Zimmerman was American. *George, William and Alexander Montagu were British. === Residences === * 1890: "The family estates — 27,312 acres, with a nominal rent-roll of £40,000 — were chiefly situated in Huntingdonshire and Armagh."<ref>"Men and Things." (London) ''Echo'' 22 March 1890, Saturday: 1 [of 4], Col. 6b [of 7]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0004596%2F18900322&page=1&article=010&stringtohighlight=mandeville+viscount. Same print title, n.p.</ref> * In 1890 at the death of the 7th Duke, Kimbolton Castle: <blockquote>The Duke of Manchester... He was an old-fashioned Tory, and a man of simple tastes, whose chief interests were military and agricultural rather than political. Kimbolton Castle is a magnificent place, and the Duke's horses and troop of yeomanry were always the admiration of the Prince of Wales, the Marquis of Hartington, and many other visitors. Lord Hartington, it may be mentioned, was at Kimbolton when the news came of the  breaking out of the war between France and Germany [1871], he being a member of the Cabinet. The Duke had travelled much as a young man, and was familiar with the Continent, as also with South Africa, of which he was very fond. There is a private chapel at Kimbolton Castle, connected with which is a very extensive library containing some theological and historical volumes of great value. Notwithstanding his somewhat bluff manner the Duke was liked by the tenantry and poor from the kindly interest he took in their concerns. Even the poachers had a good word for his Grace. The feature, however, of the Duke's career was the marked contrast between his pursuits and those of the Duchess. The Duke loved every blade of grass, every tree and flower on his ancestral domain, and cared nothing for London life in its modern developments. Lord Mandeville [the 8th Duke] succeeds to the title, but the estates are heavily mortgaged.<ref>"Death of the Duke of Manchester." ''Pall Mall Gazette'' 22 March 1890, Saturday: 6 [of 8], Col. 2b [of 3]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0000098%2F18900322&page=6&article=014&stringtohighlight=mandeville+viscount. Same print title and p. </ref></blockquote> == Family == *Consuelo (María Consuelo) Iznaga y Clement Montagu, Duchess of Manchester (1853 – 20 November 1909), née Doña María Consuelo Iznaga y Clement<ref name=":0" /> *"Kim" (George Victor Drogo) Montagu, 8th Duke of Manchester (17 June 1853 – 18 August 1892)<ref name=":1" /> #William Angus Drogo Montagu, 9th Duke of Manchester (3 March 1877 – 9 February 1947) #Jacqueline Mary Alva Montagu (27 November 1879 – 15 March 1895). #Alice Eleanor Louise Montagu (27 November 1879 – 10 January 1900) *[[Social Victorians/People/William Angus Drogo Montagu|William Angus Drogo Montagu]], 9th Duke of Manchester (3 March 1877 – 9 February 1947)<ref>{{Cite journal|date=2020-10-08|title=William Montagu, 9th Duke of Manchester|url=https://en.wikipedia.org/w/index.php?title=William_Montagu,_9th_Duke_of_Manchester&oldid=982513036|journal=Wikipedia|language=en}}</ref> *Helena Zimmerman Montagu (25 September 1878 – 15 December 1971)<ref>{{Cite journal|date=2020-10-08|title=Helena, Countess of Kintore|url=https://en.wikipedia.org/w/index.php?title=Helena,_Countess_of_Kintore&oldid=982513630|journal=Wikipedia|language=en}}</ref> #Mary Alice Montagu Gregory (26 October 1901 – 9 October 1962) #Alexander George Francis Drogo Montagu, 10th Duke of Manchester (2 October 1902 – 23 November 1977) #Edward Eugene Fernando Montagu (26 July 1906 – 4 May 1954/1956) #Ellen Millicent Louise Montagu Hofer Shairp (5 January 1908 – 2 August 1948) === Relations === The three Iznaga y Clement sisters were prominent in London "Society": *Consuelo (María Consuelo) Iznaga Montagu, Duchess of Manchester (1853 – 20 November 1909) *Emilie Iznaga y Clement () *Natividad (Natica) Iznaga y Clement Lister-Kaye () == Questions and Notes == *In a ''British Newspaper Archive'' search for name=mandeville keyword=#viscount for 18 August 1855–22 March 1890 (September 2026), first did "Publication date oldest first," but Kim was 2 years old when his grandfather died and his father acceded to the dukedom, so on p. 57 of the search results (the page containing 1 January 1856) I switched to "Publication date newest first." Decided it would be more fruitful to work backwards. == Papers, Memoirs and Biographies == == Footnotes == {{reflist}} 5u8jafmrj4umleiprmeh25x36qa5obj 2835232 2835226 2026-09-30T22:21:48Z Scogdill 1331941 2835232 wikitext text/x-wiki [[File:Viscount Mandeville Vanity Fair 1882-04-22.jpg|alt=Old drawing for a magazine of an aristocratic man in a formal suit|thumb|"Kim," Viscount Mandeville, 1882]] == Overview == The Mandeville who was in a relationship with music-hall and vaudeville star Bessie Bellwood was Kim (George Victor Drogo) Montagu, 8th Duke of Manchester (17 June 1853 – 18 August 1892). He was Viscount Mandeville from 18 August 1855 (when his grandfather died) to 22 March 1890 (when his father died).<ref name=":1" /> When he succeeded to the dukedom in 1890, he ended his relationship with Bellwood. His father was the 7th Duke and his mother was [[Social Victorians/People/Louisa Montagu Cavendish|Louise Cavendish]], "double Duchess" of [[Social Victorians/People/Manchester|Manchester]] and then [[Social Victorians/People/Devonshire|Devonshire]]. Viscount Mandeville (right) was "Man of the Day" (#255) for ''Vanity Fair'', drawn by Leslie Ward ("Spy").<ref>"Viscount Mandeville Vanity Fair 1882-04-22.jpg." Wikimedia Commons. https://commons.wikimedia.org/wiki/File:Viscount_Mandeville_Vanity_Fair_1882-04-22.jpg (retrieved 8 September 2026).</ref> == Also Known As == *Family name: Montagu *The title Viscount Mandeville is a courtesy title for the heir apparent and eldest son of the [[Social Victorians/People/Manchester |Duke of Manchester]]. This title is one of only 2 (for the heir apparent of a duke) that is below the rank of Earl (the other is the heir apparent of the Duke of Somerset). (Is Mandeville a toponym?) *Viscount Mandeville **"Kim" (George Victor Drogo) Montagu [8th Duke], (18 August 1855 – 22 March 1890) **[[Social Victorians/People/William Angus Drogo Montagu|William Angus Drogo Montagu]], 9th Duke (22 March 1890 – 18 August 1892) **Alexander George Francis Drogo Montagu (2 October 1902 – 9 February 1947)<ref>{{Cite journal|date=2020-10-15|title=Alexander Montagu, 10th Duke of Manchester|url=https://en.wikipedia.org/w/index.php?title=Alexander_Montagu,_10th_Duke_of_Manchester&oldid=983660353|journal=Wikipedia|language=en}}</ref> *Viscountess Mandeville **Consuelo Iznaga y Clement Montagu [8th Duchess] (22 May 1876 – 22 March 1890) **Helena Zimmerman Montagu (14 November 1890 – 18 August 1892) *Lord Kimbolton (Baron Kimbolton of Kimbolton is the courtesy title for the heir presumptive, the heir apparent's eldest son, so the son of Viscount Mandeville<ref>{{Cite journal|date=2026-09-21|title=Duke of Manchester|url=https://en.wikipedia.org/w/index.php?title=Duke_of_Manchester&oldid=1375987697|journal=Wikipedia|language=en}}</ref>) ** [[Social Victorians/People/William Angus Drogo Montagu|William Angus Drogo Montagu]], 9th Duke (1877 – 22 March 1890) == Acquaintances, Friends and Enemies == === "Kim" Montagu, 8th Duke, Lord Mandeville until 1890 === ==== Friends ==== * Edward Russell, 24th Baron de Clifford * Derrick Westenra, 5th Baron Rossmore * Francis Needham, 3rd Earl of Kilmorey === Consuelo Iznaga y Clement Montagu === ==== Friends ==== *Consuelo Iznaga y Clement Montagu was in the intimate circle of [[Social Victorians/People/Albert Edward, Prince of Wales |Albert Edward, Prince of Wales]]. ==Organizations== === "Kim" Montagu, 8th Duke, Lord Mandeville until 1890 === * Eton<ref name=":1" /> === Consuelo Iznaga y Clement Montagu === * Consuelo Iznaga y Clement Montagu was a member of the New York City social set called the Buccaneers when she was a teenager.<ref name=":0">{{Cite journal|date=2020-10-06|title=Consuelo Montagu, Duchess of Manchester|url=https://en.wikipedia.org/w/index.php?title=Consuelo_Montagu,_Duchess_of_Manchester&oldid=982192002|journal=Wikipedia|language=en}}</ref> Edith Wharton is said to have take details from the 8th Duke's marriage ''The Buccaneers''.<ref name=":1">{{Cite journal|date=2020-10-06|title=George Montagu, 8th Duke of Manchester|url=https://en.wikipedia.org/w/index.php?title=George_Montagu,_8th_Duke_of_Manchester&oldid=982188929|journal=Wikipedia|language=en}}</ref> == Timeline == '''1855 August 18''', the 6th Duke died. The families "placed in mourning":<blockquote>He is succeeded in the Dukedom by his eldest son, Viscount Mandeville, M.P. By the melancholy event the families of the Marquess and Marchioness of Tweeddale, the Duchess of Wellington, the Duke of Montrose, Lord and Lady Olivia Ossulston [?], Lady Eliza [Elisa?] Steele, the Duke of Richmond, the Countess of St Germans, Lady Sophia Cecil, and many others of rank, are placed in mourning.<ref>"Death of the Duke of Manchester." ''Edinburgh Evening Post and Scottish Standard'' 22 August 1855, Wednesday: 2 [of 4], Col. 5c [of 8]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0001177%2F18550822&page=2&article=025&stringtohighlight=mandeville+viscount. Print title ''Edinburgh Evening Post and Scottish Record''; n.p.</ref></blockquote>'''1855 October 11, Wednesday''', H. I. Cridland says in a "Notice,"<blockquote>I will hold Audit Days at Lyttelton, on Wednesday, 11th October, for the receipt of rents and other monies due to the 25th of September, on account of the Soames, Jackson, Ecclesiastical, and Lyttelton Trust Estates, the lands of Lord Mandeville, Lady Emily Bathurst, Lady Olivia Sparrow, Rev. J. P. Rhoades, Rev. Charles Hodge, Dr. Merrion C. T. Maunsell, George Hart, late William Draper, and J. E. Fitz Gerald, Esqrs. ... Tenants are requested to present their last receipt.<ref>"Notice." ''Lyttelton Times'' 6 October 1855, Saturday: 1 [of 10], Col. 3c [of 3]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0003346%2F18551006&page=1&article=004&stringtohighlight=mandeville+viscount. Newspaper title ''The Lyttelton Times'', n.p. </ref></blockquote>This notice was repeated in the ''Lyttelton Times'' on 29 December 1855. '''1855 October 20, Saturday''', the [[Social Victorians/People/Wilton|Earl and Countess of Wilton]] hosted a [[Social Victorians/Timeline/1850s#1855 October 20, Saturday|house party at Heaton Hall]], with a visit to a silk mill in town. [[Social Victorians/People/Louisa Montagu Cavendish|Luise, Duchess of Manchester]] was present with the Duke and their son Lord Mandeville (Kim, later 8th Duke), who was 2 years old. '''1876 May 22''', Consuelo Iznaga y Clement and "Kim" (George Victor Drogo, 8th Duke) Montagu married in Grace Church, New York City.<ref name=":0" /> '''1890 January 29, Wednesday''', Consuelo Lady Mandeville was a guest at the house party around and the [[Social Victorians/Santurce Murrieta Wedding 1890-01-29|wedding of Miss Clarita de Murietta and the Duc de Santona]]. She had her eldest son with her, Lord Kimbolton (the 9th Duke of Manchester). Her mother in law, [[Social Victorians/People/Louisa Montagu Cavendish|Louise, Duchess of Manchester]] was also present. '''1890 February 6, Thursday''' '''(shortly before 6 February)''', Kim Lord Mandeville attended a [[Social Victorians/Timeline/1890#1890 February 6, Thursday|boxing match fought by the prize-fighter Pete Jackson]] at the New Pelican Club. '''1890 February 8, Saturday''', Kim Lord Mandeville was among the [[Social Victorians/Timeline/1890#1890 February 8, Saturday|recent arrivals at Brighton]] although apparently after the most notable had already left. Certainly he does not appear to have been at the party the next evening that the Prince of Wales attended. '''1890 February 9, Sunday''', the Prince of Wales came after one of Consuelo's dinner parties:<blockquote>Lady Mandeville, who has been giving a series of small dinners in her house in Cumberland Place, had a dinner on Sunday. The Prince of Wales came in after dinner to meet a small party.<ref>"Society Gossip. (From ''The World''.)." ''Leighton Buzzard Observer and Linslade Gazette'' 11 February 1890, Tuesday: 6 [of 8], Col. 6b [of 7]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0001091%2F18900211&page=6&article=106&stringtohighlight=mandeville+viscount. Print title: ''The Leighton Buzzard Observer'', p. 6. </ref></blockquote>'''1890 February 24, Monday''', Consuelo Lady Mandeville attended [[Social Victorians/Timeline/1890#24 February 1890, Monday|Lilly Langtry's performance as Rosalind in As You Like It at the St. James's Theatre]]. '''1890 February 25, Tuesday''', Consuelo Lady Mandeville attended a [[Social Victorians/Timeline/1890#25 February 1890, Tuesday|party hosted by Mrs. Adair]]. Viscount Mandeville is not listed among those who attended. '''1890 March 4, Wednesday''', Consuelo's brother Fernando Yznaga married New York "beauty and society leader" Miss Mabel Wright.<ref>"Personal." ''American Register'' 22 March 1890, Saturday: 5 [of 8], Col. 5a [of 7]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0003338%2F18900322&page=5&article=070&stringtohighlight=mandeville+viscount. Same print title and p.</ref> Presumably at least Consuelo was there? '''1890 March 10, Monday''', the Prince and Princess of Wales gave a [[Social Victorians/Timeline/1890#10 March 1890, Monday10 March 1890, Monday|dance at Marlborough House in honor of their wedding anniversary]]. The Viscountess Mandeville is listed among the guests invited, but the Viscount is not mentioned. '''1890 March 22, Saturday''', the Portsmouth ''Evening News'' expressed outrage about a man with a reputation like Kim's becoming 8th Duke of Manchester:<blockquote>While the House of Commons were debating the necessity for a House of Lords, the Duke of Manchester was on his death bed in Naples. There is more in the incident than appears at first sight, for Viscount Mandeville succeeds to the Dukedom, with the attendant rights of presentation to seven livings and the privilege of mutilating or rejecting Bills demanded by the people and passed by their representatives in the Commons.<p> It will hardly be urged by the moat zealous advocate of the Upper Chamber, as at present constituted, that the new Duke of Manchester, ''nee'' Viscount Mandeville, will bring much dignity, wisdom, or weight to the House of irresponsible legislators. This nobleman has had a merry time. The one sensible thing he did was to marry a charming and accomplished American lady, who, by consenting to share the name of Mandeville has kept its head above water. Viscount Mandeville himself has a weakness for bankruptcy proceedings, rows with cabmen, which music hall ladies come forward to take his part, and the class of events generally which do not approve themselves to the minds of the ordinary Briton. It is possible that Lord Mandeville may now discover that he has sown his wild oats, and may settle down with his beautiful and popular wife to the enjoyment of his  25,000 acres of land and £38,000 a-year. We have not to do with what Lord Mandeville may be. Our simple duty is to point out that it is an outrage on common decency and common sense that a man bearing the reputation of Lord Mandeville should have the right to step into the House of Lords whenever a vote is needed to swell the prejudice or sustain the selfishness that find among the Peers their natural home.<ref>"To-Day." ''Portsmouth Evening News'' 22 March 1890, Saturday: 2 [of 4], Col. 1c [of 6]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0000290%2F18900322&page=2&article=001&stringtohighlight=mandeville+viscount. Print title: ''The Evening News'', n.p.</ref></blockquote>The ''Birmingham Daily Mail'' had a similar opinion, though perhaps slightly more optimistic:<blockquote>The Duke of Manchester, who expired last night at Naples, cannot be said to have been much of a public man. He led a quiet, retired life, and the announcement of his death would, if Lord  Mandeville were not heir to the title, arouse but little interest. Lord Mandeville is, unfortunately for himself, more widely known than his father was. He developed tastes for gambling, with disastrous financial results, as the details of his bankruptcy made public last year, and more recently, his name has been publicly associated with those of prizefighters and music-hall singers. Altogether, he can hardly be termed a credit to the aristocracy of England, but the higher position to which he will now attain may cause him to alter his ways and try redeem the errors of the past.<ref>"Notes and News." ''Birmingham Mail'' 22 March 1890, Saturday: 2 [of 4], Col. 3a [of 8]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0000644%2F18900322&page=2&article=027&stringtohighlight=mandeville+viscount. Print title: ''Birmingham Daily Mail'', n.p.</ref></blockquote>On the same day, Consuelo's brother and new wife were reported to apparently be immigrating to the UK:<blockquote>Among the immigrants, says a London lady correspondent, is a New York belle who has just been married to Mr. Ferdinand Yznaga, brother to Lady Mandeville and of Lady Lister-Kaye. Young Mrs. Yznaga will enter London society under the wing of her sister-in-law, Lady Mandeville, and is expected to make as great a furore as did Mrs. Langtry a few seasons ago. Mr. Yznaga married a sister-in-law of Mr. Vanderbilt, who divorced him two years ago.<ref>"An American Belle." ''Huddersfield and Holmfirth Examiner'' 22 March 1890, Saturday: 6 [of 16], Col. 4a [of 6]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0003869%2F18900322&page=6&article=006&stringtohighlight=mandeville+viscount. Print title: ''The Huddersfield Examiner'', p. 6.</ref></blockquote>'''1890 November 14''', William Angus Drogo Montagu (9th Duke) and Helena Zimmerman married secretly, in London. '''1897 July 2''', the Duke and Duchess of Devonshire ( [[Social Victorians/People/Louisa Montagu Cavendish|Luise Friederike Auguste Gräfin von Alten Montagu Cavendish]] and [[Social Victorians/People/Spencer Compton Cavendish|Spencer Cavendish]]) hosted the [[Social Victorians/1897 Fancy Dress Ball|Duchess of Devonshire's fancy-dress ball]] at Devonshire House. Lord Charles Montagu, likely Charles William Augustus Montagu, attended, as did [[Social Victorians/People/William Angus Drogo Montagu|William Angus Drogo Montagu]]. == Demographics == ===Nationality=== *Consuelo Iznaga y Clement was Cuban-American. *Helena Zimmerman was American. *George, William and Alexander Montagu were British. === Residences === * 1890: "The family estates — 27,312 acres, with a nominal rent-roll of £40,000 — were chiefly situated in Huntingdonshire and Armagh."<ref>"Men and Things." (London) ''Echo'' 22 March 1890, Saturday: 1 [of 4], Col. 6b [of 7]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0004596%2F18900322&page=1&article=010&stringtohighlight=mandeville+viscount. Same print title, n.p.</ref> * In 1890 at the death of the 7th Duke, Kimbolton Castle: <blockquote>The Duke of Manchester... He was an old-fashioned Tory, and a man of simple tastes, whose chief interests were military and agricultural rather than political. Kimbolton Castle is a magnificent place, and the Duke's horses and troop of yeomanry were always the admiration of the Prince of Wales, the Marquis of Hartington, and many other visitors. Lord Hartington, it may be mentioned, was at Kimbolton when the news came of the  breaking out of the war between France and Germany [1871], he being a member of the Cabinet. The Duke had travelled much as a young man, and was familiar with the Continent, as also with South Africa, of which he was very fond. There is a private chapel at Kimbolton Castle, connected with which is a very extensive library containing some theological and historical volumes of great value. Notwithstanding his somewhat bluff manner the Duke was liked by the tenantry and poor from the kindly interest he took in their concerns. Even the poachers had a good word for his Grace. The feature, however, of the Duke's career was the marked contrast between his pursuits and those of the Duchess. The Duke loved every blade of grass, every tree and flower on his ancestral domain, and cared nothing for London life in its modern developments. Lord Mandeville [the 8th Duke] succeeds to the title, but the estates are heavily mortgaged.<ref>"Death of the Duke of Manchester." ''Pall Mall Gazette'' 22 March 1890, Saturday: 6 [of 8], Col. 2b [of 3]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0000098%2F18900322&page=6&article=014&stringtohighlight=mandeville+viscount. Same print title and p. </ref></blockquote> == Family == *Consuelo (María Consuelo) Iznaga y Clement Montagu, Duchess of Manchester (1853 – 20 November 1909), née Doña María Consuelo Iznaga y Clement<ref name=":0" /> *"Kim" (George Victor Drogo) Montagu, 8th Duke of Manchester (17 June 1853 – 18 August 1892)<ref name=":1" /> #William Angus Drogo Montagu, 9th Duke of Manchester (3 March 1877 – 9 February 1947) #Jacqueline Mary Alva Montagu (27 November 1879 – 15 March 1895). #Alice Eleanor Louise Montagu (27 November 1879 – 10 January 1900) *[[Social Victorians/People/William Angus Drogo Montagu|William Angus Drogo Montagu]], 9th Duke of Manchester (3 March 1877 – 9 February 1947)<ref>{{Cite journal|date=2020-10-08|title=William Montagu, 9th Duke of Manchester|url=https://en.wikipedia.org/w/index.php?title=William_Montagu,_9th_Duke_of_Manchester&oldid=982513036|journal=Wikipedia|language=en}}</ref> *Helena Zimmerman Montagu (25 September 1878 – 15 December 1971)<ref>{{Cite journal|date=2020-10-08|title=Helena, Countess of Kintore|url=https://en.wikipedia.org/w/index.php?title=Helena,_Countess_of_Kintore&oldid=982513630|journal=Wikipedia|language=en}}</ref> #Mary Alice Montagu Gregory (26 October 1901 – 9 October 1962) #Alexander George Francis Drogo Montagu, 10th Duke of Manchester (2 October 1902 – 23 November 1977) #Edward Eugene Fernando Montagu (26 July 1906 – 4 May 1954/1956) #Ellen Millicent Louise Montagu Hofer Shairp (5 January 1908 – 2 August 1948) === Relations === The three Iznaga y Clement sisters were prominent in London "Society": *Consuelo (María Consuelo) Iznaga Montagu, Duchess of Manchester (1853 – 20 November 1909) *Emilie Iznaga y Clement () *Natividad (Natica) Iznaga y Clement Lister-Kaye () == Questions and Notes == *In a ''British Newspaper Archive'' search for name=mandeville keyword=#viscount for 18 August 1855–22 March 1890 (September 2026), first did "Publication date oldest first," but Kim was 2 years old when his grandfather died and his father acceded to the dukedom, so on p. 57 of the search results (the page containing 1 January 1856) I switched to "Publication date newest first." Decided it would be more fruitful to work backwards. == Papers, Memoirs and Biographies == == Footnotes == {{reflist}} frtfwv08gi0rp9u4jvgnedfvjf9jn3l 0 264914 2835248 2835135 2026-10-01T01:22:29Z Jtneill 10242 /* Psychometrics */ 2835248 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/Complete2}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * emotion inducement * measurement of emotion * the Positive and Negative Affect Scale * book chapter marking criteria ==How can emotion be induced?== Some emotion research studies induce specific emotions in order to better under them. In ways can human emotion be induced for the purpose of psychological research? {| class="wikitable" ! Method ! Example ! Example study |- | '''Imagined scenarios''' | Imagine a specified emotional situation or vividly imagine an emotionally evocative scenario | Holmes, E. A., Mathews, A., Mackintosh, B., & Dalgleish, T. (2008). The causal effect of mental imagery on emotion assessed using picture-word cues. ''Emotion, 8''(3), 395–409. https://doi.org/10.1037/1528-3542.8.3.395 |- | '''Images, video, VR''' | View emotionally evocative photographs, film clips, or virtual reality | Uhrig, M. K., Trautmann, N., Baumgärtner, U., Treede, R.-D., Henrich, F., Hiller, W., & Marschall, S. (2016). Emotion elicitation: A comparison of pictures and films. ''Frontiers in Psychology, 7'', 180. https://doi.org/10.3389/fpsyg.2016.00180 |- | '''Music''' | Listen to music selected to induce a particular emotional state | Kenealy, P. (1988). Validation of a music mood induction procedure: Some preliminary findings. ''Cognition and Emotion, 2''(1), 41–48. https://doi.org/10.1080/02699938808415228 |- | '''Autobiographical recall''' | Recall and re-experience a personal event associated with the target emotion | Mills, C., & D'Mello, S. (2014). On the validity of the autobiographical emotional memory task for emotion induction. ''PLoS ONE, 9''(4), e95837. https://doi.org/10.1371/journal.pone.0095837 |- | '''Social situational manipulation''' | Interact with another person whose behaviour is deliberately designed to elicit an emotion | Kučera, D., & Haviger, J. (2012). Using mood induction procedures in psychological research. ''Procedia - Social and Behavioral Sciences, 69'', 31–40. https://doi.org/10.1016/j.sbspro.2012.11.380 |} ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Empirical emotion research requires measurement. How can emotion be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. [[w:Functional magnetic resonance imaging|fMRI]] is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * Behaviour (e.g., body language, eye tracking, key strokes) * Facial expression (e.g. specific combinations of muscle activation) * Neural activity: ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2) * Physiological arousal (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * Resource intensive (especially fMRI) - needs equipment, expertise, software etc. * Based on what is externally [[w:Observation|observable]] or physiologically scannable. But emotion is also fundamentally phenomenological/subjective. So, other measurement options include using analysis of written or spoken language or simple to ask people to [[w:Introspection|introspect]] and self-report. ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed about their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because it is: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === The temporal framing of the PANAS can be customised: {| class="wikitable" ! Time frame ! Description |- | '''Moment''' | You feel this way right now, that is, at the present moment. |- | '''Today''' | You have felt this way today. |- | '''Past few days''' | You have felt this way during the past few days. |- | '''Week''' | You have felt this way during the past week. |- | '''Past few weeks''' | You have felt this way during the past few weeks. |- | '''Year''' | You have felt this way during the past year. |- | '''General''' | You generally feel this way, that is, how you feel on average. |} === Psychometrics === * '''Independence of positive and negative affective''': The correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlations indicate that when one dimension is higher the other one tends to be lower, but the relationship is very weak (1% to 5% shared variance). Thus, it is best to consider PA and NA as independent dimensions of affective experience. For example, consider in what situations might: ** PA and NA both be high? ** PA and NA both be low? * '''Test-retest reliability''': How stable is this measure of emotion over time? Based on an 8-week test-retest period, Watson et al. (1988) found: ** Moment: PA .54 and NA .45 (~25% relability) ** General: PA .68 and NA .71 (~50 relability) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3 to 3.5 ** NA = 1.5 to 2 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter tips== * Follow the [[Motivation and emotion/Assessment/Chapter|author guidelines]] and [[Motivation and emotion/Assessment/Using generative AI|using genAI guidelines]] * Address the [[Motivation and emotion/Assessment/Chapter#Marking criteria|marking criteria]] * Check the [[Motivation and emotion/Assessment/Chapter#Marking rubric|marking rubric]] * Compare with [[Motivation and emotion/Book|top chapters]] * Get feedback ** Studiosity Writing Feedback+ ** Peer review ** AI review ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [https://au-lti.bbcollab.com/recording/f787e4083a49474785fc57b7631570b9 Tutorial 8] (2026)<!-- * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025) * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] hgrtxx86aul9732pw99vrllr80o9wwb 2835249 2835248 2026-10-01T01:23:43Z Jtneill 10242 /* Psychometrics */ 2835249 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/Complete2}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * emotion inducement * measurement of emotion * the Positive and Negative Affect Scale * book chapter marking criteria ==How can emotion be induced?== Some emotion research studies induce specific emotions in order to better under them. In ways can human emotion be induced for the purpose of psychological research? {| class="wikitable" ! Method ! Example ! Example study |- | '''Imagined scenarios''' | Imagine a specified emotional situation or vividly imagine an emotionally evocative scenario | Holmes, E. A., Mathews, A., Mackintosh, B., & Dalgleish, T. (2008). The causal effect of mental imagery on emotion assessed using picture-word cues. ''Emotion, 8''(3), 395–409. https://doi.org/10.1037/1528-3542.8.3.395 |- | '''Images, video, VR''' | View emotionally evocative photographs, film clips, or virtual reality | Uhrig, M. K., Trautmann, N., Baumgärtner, U., Treede, R.-D., Henrich, F., Hiller, W., & Marschall, S. (2016). Emotion elicitation: A comparison of pictures and films. ''Frontiers in Psychology, 7'', 180. https://doi.org/10.3389/fpsyg.2016.00180 |- | '''Music''' | Listen to music selected to induce a particular emotional state | Kenealy, P. (1988). Validation of a music mood induction procedure: Some preliminary findings. ''Cognition and Emotion, 2''(1), 41–48. https://doi.org/10.1080/02699938808415228 |- | '''Autobiographical recall''' | Recall and re-experience a personal event associated with the target emotion | Mills, C., & D'Mello, S. (2014). On the validity of the autobiographical emotional memory task for emotion induction. ''PLoS ONE, 9''(4), e95837. https://doi.org/10.1371/journal.pone.0095837 |- | '''Social situational manipulation''' | Interact with another person whose behaviour is deliberately designed to elicit an emotion | Kučera, D., & Haviger, J. (2012). Using mood induction procedures in psychological research. ''Procedia - Social and Behavioral Sciences, 69'', 31–40. https://doi.org/10.1016/j.sbspro.2012.11.380 |} ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Empirical emotion research requires measurement. How can emotion be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. [[w:Functional magnetic resonance imaging|fMRI]] is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * Behaviour (e.g., body language, eye tracking, key strokes) * Facial expression (e.g. specific combinations of muscle activation) * Neural activity: ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2) * Physiological arousal (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * Resource intensive (especially fMRI) - needs equipment, expertise, software etc. * Based on what is externally [[w:Observation|observable]] or physiologically scannable. But emotion is also fundamentally phenomenological/subjective. So, other measurement options include using analysis of written or spoken language or simple to ask people to [[w:Introspection|introspect]] and self-report. ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed about their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because it is: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === The temporal framing of the PANAS can be customised: {| class="wikitable" ! Time frame ! Description |- | '''Moment''' | You feel this way right now, that is, at the present moment. |- | '''Today''' | You have felt this way today. |- | '''Past few days''' | You have felt this way during the past few days. |- | '''Week''' | You have felt this way during the past week. |- | '''Past few weeks''' | You have felt this way during the past few weeks. |- | '''Year''' | You have felt this way during the past year. |- | '''General''' | You generally feel this way, that is, how you feel on average. |} === Psychometrics === * '''Independence of positive and negative affective''': The correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlations indicate that when one dimension is higher the other one tends to be lower, but the relationship is very weak (1% to 5% shared variance). Thus, it is best to consider PA and NA as independent dimensions of affective experience. For example, consider in what situations might: ** PA and NA both be high? ** PA and NA both be low? * '''Test-retest reliability''': How stable is the PANAS-20 over time? Based on an 8-week test-retest period, Watson et al. (1988) found: ** Moment: PA .54 and NA .45 (~25% relability) ** General: PA .68 and NA .71 (~50 relability) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3 to 3.5 ** NA = 1.5 to 2 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter tips== * Follow the [[Motivation and emotion/Assessment/Chapter|author guidelines]] and [[Motivation and emotion/Assessment/Using generative AI|using genAI guidelines]] * Address the [[Motivation and emotion/Assessment/Chapter#Marking criteria|marking criteria]] * Check the [[Motivation and emotion/Assessment/Chapter#Marking rubric|marking rubric]] * Compare with [[Motivation and emotion/Book|top chapters]] * Get feedback ** Studiosity Writing Feedback+ ** Peer review ** AI review ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [https://au-lti.bbcollab.com/recording/f787e4083a49474785fc57b7631570b9 Tutorial 8] (2026)<!-- * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025) * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] 1onnvnjgp3kxbi9u9vw0pup0kyrxsxm 2835250 2835249 2026-10-01T01:24:32Z Jtneill 10242 /* Distributions */ 2835250 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/Complete2}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * emotion inducement * measurement of emotion * the Positive and Negative Affect Scale * book chapter marking criteria ==How can emotion be induced?== Some emotion research studies induce specific emotions in order to better under them. In ways can human emotion be induced for the purpose of psychological research? {| class="wikitable" ! Method ! Example ! Example study |- | '''Imagined scenarios''' | Imagine a specified emotional situation or vividly imagine an emotionally evocative scenario | Holmes, E. A., Mathews, A., Mackintosh, B., & Dalgleish, T. (2008). The causal effect of mental imagery on emotion assessed using picture-word cues. ''Emotion, 8''(3), 395–409. https://doi.org/10.1037/1528-3542.8.3.395 |- | '''Images, video, VR''' | View emotionally evocative photographs, film clips, or virtual reality | Uhrig, M. K., Trautmann, N., Baumgärtner, U., Treede, R.-D., Henrich, F., Hiller, W., & Marschall, S. (2016). Emotion elicitation: A comparison of pictures and films. ''Frontiers in Psychology, 7'', 180. https://doi.org/10.3389/fpsyg.2016.00180 |- | '''Music''' | Listen to music selected to induce a particular emotional state | Kenealy, P. (1988). Validation of a music mood induction procedure: Some preliminary findings. ''Cognition and Emotion, 2''(1), 41–48. https://doi.org/10.1080/02699938808415228 |- | '''Autobiographical recall''' | Recall and re-experience a personal event associated with the target emotion | Mills, C., & D'Mello, S. (2014). On the validity of the autobiographical emotional memory task for emotion induction. ''PLoS ONE, 9''(4), e95837. https://doi.org/10.1371/journal.pone.0095837 |- | '''Social situational manipulation''' | Interact with another person whose behaviour is deliberately designed to elicit an emotion | Kučera, D., & Haviger, J. (2012). Using mood induction procedures in psychological research. ''Procedia - Social and Behavioral Sciences, 69'', 31–40. https://doi.org/10.1016/j.sbspro.2012.11.380 |} ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Empirical emotion research requires measurement. How can emotion be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. [[w:Functional magnetic resonance imaging|fMRI]] is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * Behaviour (e.g., body language, eye tracking, key strokes) * Facial expression (e.g. specific combinations of muscle activation) * Neural activity: ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2) * Physiological arousal (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * Resource intensive (especially fMRI) - needs equipment, expertise, software etc. * Based on what is externally [[w:Observation|observable]] or physiologically scannable. But emotion is also fundamentally phenomenological/subjective. So, other measurement options include using analysis of written or spoken language or simple to ask people to [[w:Introspection|introspect]] and self-report. ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed about their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because it is: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === The temporal framing of the PANAS can be customised: {| class="wikitable" ! Time frame ! Description |- | '''Moment''' | You feel this way right now, that is, at the present moment. |- | '''Today''' | You have felt this way today. |- | '''Past few days''' | You have felt this way during the past few days. |- | '''Week''' | You have felt this way during the past week. |- | '''Past few weeks''' | You have felt this way during the past few weeks. |- | '''Year''' | You have felt this way during the past year. |- | '''General''' | You generally feel this way, that is, how you feel on average. |} === Psychometrics === * '''Independence of positive and negative affective''': The correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlations indicate that when one dimension is higher the other one tends to be lower, but the relationship is very weak (1% to 5% shared variance). Thus, it is best to consider PA and NA as independent dimensions of affective experience. For example, consider in what situations might: ** PA and NA both be high? ** PA and NA both be low? * '''Test-retest reliability''': How stable is the PANAS-20 over time? Based on an 8-week test-retest period, Watson et al. (1988) found: ** Moment: PA .54 and NA .45 (~25% relability) ** General: PA .68 and NA .71 (~50 relability) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3.0 to 3.5 ** NA = 1.5 to 2.0 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter tips== * Follow the [[Motivation and emotion/Assessment/Chapter|author guidelines]] and [[Motivation and emotion/Assessment/Using generative AI|using genAI guidelines]] * Address the [[Motivation and emotion/Assessment/Chapter#Marking criteria|marking criteria]] * Check the [[Motivation and emotion/Assessment/Chapter#Marking rubric|marking rubric]] * Compare with [[Motivation and emotion/Book|top chapters]] * Get feedback ** Studiosity Writing Feedback+ ** Peer review ** AI review ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [https://au-lti.bbcollab.com/recording/f787e4083a49474785fc57b7631570b9 Tutorial 8] (2026)<!-- * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025) * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] dzmrv5qazufihu72tuv5jemxlug94jr 2835255 2835250 2026-10-01T02:29:29Z Jtneill 10242 /* How can emotion be measured? */ Revise 2835255 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/Complete2}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * emotion inducement * measurement of emotion * the Positive and Negative Affect Scale * book chapter marking criteria ==How can emotion be induced?== Some emotion research studies induce specific emotions in order to better under them. In ways can human emotion be induced for the purpose of psychological research? {| class="wikitable" ! Method ! Example ! Example study |- | '''Imagined scenarios''' | Imagine a specified emotional situation or vividly imagine an emotionally evocative scenario | Holmes, E. A., Mathews, A., Mackintosh, B., & Dalgleish, T. (2008). The causal effect of mental imagery on emotion assessed using picture-word cues. ''Emotion, 8''(3), 395–409. https://doi.org/10.1037/1528-3542.8.3.395 |- | '''Images, video, VR''' | View emotionally evocative photographs, film clips, or virtual reality | Uhrig, M. K., Trautmann, N., Baumgärtner, U., Treede, R.-D., Henrich, F., Hiller, W., & Marschall, S. (2016). Emotion elicitation: A comparison of pictures and films. ''Frontiers in Psychology, 7'', 180. https://doi.org/10.3389/fpsyg.2016.00180 |- | '''Music''' | Listen to music selected to induce a particular emotional state | Kenealy, P. (1988). Validation of a music mood induction procedure: Some preliminary findings. ''Cognition and Emotion, 2''(1), 41–48. https://doi.org/10.1080/02699938808415228 |- | '''Autobiographical recall''' | Recall and re-experience a personal event associated with the target emotion | Mills, C., & D'Mello, S. (2014). On the validity of the autobiographical emotional memory task for emotion induction. ''PLoS ONE, 9''(4), e95837. https://doi.org/10.1371/journal.pone.0095837 |- | '''Social situational manipulation''' | Interact with another person whose behaviour is deliberately designed to elicit an emotion | Kučera, D., & Haviger, J. (2012). Using mood induction procedures in psychological research. ''Procedia - Social and Behavioral Sciences, 69'', 31–40. https://doi.org/10.1016/j.sbspro.2012.11.380 |} ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Empirical emotion research requires measurement. However, emotions are not directly [[w:Observation|observable]], so how can they be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. [[w:Functional magnetic resonance imaging|fMRI]] is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * '''Behaviour''' (e.g., body language, eye tracking, key strokes) * '''Facial expression''' (e.g. specific combinations of muscle activation) * '''Neural activity''': e.g., ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2) * '''Physiological arousal''' (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * '''Resource intensive''' (especially fMRI) - needs equipment, expertise, software etc. * '''Based on what is observable''' - these measures use what is externally observable or physiologically scannable to infer emotionality. But emotion is fundamentally phenomenological/subjective. So, other measurement options include: * analysis of written or spoken '''language''' * ask people to [[w:Introspection|introspect]] and '''self-report''' ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed about their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because it is: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === The temporal framing of the PANAS can be customised: {| class="wikitable" ! Time frame ! Description |- | '''Moment''' | You feel this way right now, that is, at the present moment. |- | '''Today''' | You have felt this way today. |- | '''Past few days''' | You have felt this way during the past few days. |- | '''Week''' | You have felt this way during the past week. |- | '''Past few weeks''' | You have felt this way during the past few weeks. |- | '''Year''' | You have felt this way during the past year. |- | '''General''' | You generally feel this way, that is, how you feel on average. |} === Psychometrics === * '''Independence of positive and negative affective''': The correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlations indicate that when one dimension is higher the other one tends to be lower, but the relationship is very weak (1% to 5% shared variance). Thus, it is best to consider PA and NA as independent dimensions of affective experience. For example, consider in what situations might: ** PA and NA both be high? ** PA and NA both be low? * '''Test-retest reliability''': How stable is the PANAS-20 over time? Based on an 8-week test-retest period, Watson et al. (1988) found: ** Moment: PA .54 and NA .45 (~25% relability) ** General: PA .68 and NA .71 (~50 relability) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3.0 to 3.5 ** NA = 1.5 to 2.0 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter tips== * Follow the [[Motivation and emotion/Assessment/Chapter|author guidelines]] and [[Motivation and emotion/Assessment/Using generative AI|using genAI guidelines]] * Address the [[Motivation and emotion/Assessment/Chapter#Marking criteria|marking criteria]] * Check the [[Motivation and emotion/Assessment/Chapter#Marking rubric|marking rubric]] * Compare with [[Motivation and emotion/Book|top chapters]] * Get feedback ** Studiosity Writing Feedback+ ** Peer review ** AI review ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [https://au-lti.bbcollab.com/recording/f787e4083a49474785fc57b7631570b9 Tutorial 8] (2026)<!-- * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025) * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] nmkz72mzuhgs1nwvwfvhzbp791klhxo 2835258 2835255 2026-10-01T02:38:19Z Jtneill 10242 /* Self-report */ 2835258 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/Complete2}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * emotion inducement * measurement of emotion * the Positive and Negative Affect Scale * book chapter marking criteria ==How can emotion be induced?== Some emotion research studies induce specific emotions in order to better under them. In ways can human emotion be induced for the purpose of psychological research? {| class="wikitable" ! Method ! Example ! Example study |- | '''Imagined scenarios''' | Imagine a specified emotional situation or vividly imagine an emotionally evocative scenario | Holmes, E. A., Mathews, A., Mackintosh, B., & Dalgleish, T. (2008). The causal effect of mental imagery on emotion assessed using picture-word cues. ''Emotion, 8''(3), 395–409. https://doi.org/10.1037/1528-3542.8.3.395 |- | '''Images, video, VR''' | View emotionally evocative photographs, film clips, or virtual reality | Uhrig, M. K., Trautmann, N., Baumgärtner, U., Treede, R.-D., Henrich, F., Hiller, W., & Marschall, S. (2016). Emotion elicitation: A comparison of pictures and films. ''Frontiers in Psychology, 7'', 180. https://doi.org/10.3389/fpsyg.2016.00180 |- | '''Music''' | Listen to music selected to induce a particular emotional state | Kenealy, P. (1988). Validation of a music mood induction procedure: Some preliminary findings. ''Cognition and Emotion, 2''(1), 41–48. https://doi.org/10.1080/02699938808415228 |- | '''Autobiographical recall''' | Recall and re-experience a personal event associated with the target emotion | Mills, C., & D'Mello, S. (2014). On the validity of the autobiographical emotional memory task for emotion induction. ''PLoS ONE, 9''(4), e95837. https://doi.org/10.1371/journal.pone.0095837 |- | '''Social situational manipulation''' | Interact with another person whose behaviour is deliberately designed to elicit an emotion | Kučera, D., & Haviger, J. (2012). Using mood induction procedures in psychological research. ''Procedia - Social and Behavioral Sciences, 69'', 31–40. https://doi.org/10.1016/j.sbspro.2012.11.380 |} ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Empirical emotion research requires measurement. However, emotions are not directly [[w:Observation|observable]], so how can they be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. [[w:Functional magnetic resonance imaging|fMRI]] is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * '''Behaviour''' (e.g., body language, eye tracking, key strokes) * '''Facial expression''' (e.g. specific combinations of muscle activation) * '''Neural activity''': e.g., ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2) * '''Physiological arousal''' (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * '''Resource intensive''' (especially fMRI) - needs equipment, expertise, software etc. * '''Based on what is observable''' - these measures use what is externally observable or physiologically scannable to infer emotionality. But emotion is fundamentally phenomenological/subjective. So, other measurement options include: * analysis of written or spoken '''language''' * ask people to [[w:Introspection|introspect]] and '''self-report''' ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed for their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools in the health sector, such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because it is: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === The temporal framing of the PANAS can be customised: {| class="wikitable" ! Time frame ! Description |- | '''Moment''' | You feel this way right now, that is, at the present moment. |- | '''Today''' | You have felt this way today. |- | '''Past few days''' | You have felt this way during the past few days. |- | '''Week''' | You have felt this way during the past week. |- | '''Past few weeks''' | You have felt this way during the past few weeks. |- | '''Year''' | You have felt this way during the past year. |- | '''General''' | You generally feel this way, that is, how you feel on average. |} === Psychometrics === * '''Independence of positive and negative affective''': The correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlations indicate that when one dimension is higher the other one tends to be lower, but the relationship is very weak (1% to 5% shared variance). Thus, it is best to consider PA and NA as independent dimensions of affective experience. For example, consider in what situations might: ** PA and NA both be high? ** PA and NA both be low? * '''Test-retest reliability''': How stable is the PANAS-20 over time? Based on an 8-week test-retest period, Watson et al. (1988) found: ** Moment: PA .54 and NA .45 (~25% relability) ** General: PA .68 and NA .71 (~50 relability) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3.0 to 3.5 ** NA = 1.5 to 2.0 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter tips== * Follow the [[Motivation and emotion/Assessment/Chapter|author guidelines]] and [[Motivation and emotion/Assessment/Using generative AI|using genAI guidelines]] * Address the [[Motivation and emotion/Assessment/Chapter#Marking criteria|marking criteria]] * Check the [[Motivation and emotion/Assessment/Chapter#Marking rubric|marking rubric]] * Compare with [[Motivation and emotion/Book|top chapters]] * Get feedback ** Studiosity Writing Feedback+ ** Peer review ** AI review ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [https://au-lti.bbcollab.com/recording/f787e4083a49474785fc57b7631570b9 Tutorial 8] (2026)<!-- * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025) * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] ssnp03utecvj6mw8cecge16aqufeu3x 0 266023 2835284 2835143 2026-10-01T08:13:17Z ThaniosAkro 2805358 /* First result */ 2835284 wikitext text/x-wiki ==Introduction== The word "simultaneous" implies that two or more equations exist in the same context at the same time. For example: <math>3x + 2y - 13 = 0\ \dots\ (1)</math> <math>2x - y - 4 = 0 \ \dots\ (2)</math> Equations <math>(1)</math> and <math>(2)</math> are 2 simultaneous equations. When we see two simultaneous equations, it's natural to ask the question: What are the values of <math>x</math> and <math>y</math> that satisfy both equations <math>(1)</math> and <math>(2)</math>? To calculate <math>(x,y)</math> common to both <math>(1)</math> and <math>(2)</math>: <math>(2)*2\ \dots\ 4x - 2y - 8 = 0 \ \dots\ (3)</math> <math>(3)+(1)\ \dots\ 7x - 21 = 0;\ x = 3.</math> Substitute <math>3</math> for <math>x</math> in <math>(2):\ 2(3) - y - 4 = 0;\ y = 2.</math> The values <math>(x,y)=(3,2)</math> satisfy both equations <math>(1)</math> and <math>(2).</math> In cartesian coordinate geometry of 2 dimensions, point <math>(3,2)</math> is the point of intersection of two lines <math>(1)</math> and <math>(2).</math> See Figure 1 below. If the 2 lines are parallel, there is no point of intersection. See Figure 2 below. The trivial solution <math>(0, 0)</math> is a valid solution. See Figure 3 below. {{RoundBoxTop|theme=2}} <gallery> File:0726_2lines.png|<small>Figure 1. 2 lines that intersect at point (3,2).</small> File:0726_2parallelLines.png|<small>Figure 2. When 2 lines are parallel, there is no point of intersection.</small> File:0729_2lines.png|<small>Figure 3. The trivial solution x=y=0 is a valid solution.</small> </gallery> {{RoundBoxBottom}} The information contained in equations <math>(1)</math> and <math>(2)</math> may constitute a matrix: <pre> [ [3, 2, -13], [2, -1, -4] ] </pre> In fact, in the python programming language, the following statement is valid code: <syntaxhighlight lang=python> data = [ [3, 2, -13], [2, -1, -4] ] </syntaxhighlight> For there to be a point of intersection, <code>data</code> must be valid. Here are examples of invalid data: <syntaxhighlight lang=python> data = [ [3, 2, -13], # Both lines are parallel. [6, 4, -5] # See Figure 2 above. ] </syntaxhighlight> <syntaxhighlight lang=python> data = [ [3, 2, -13], [0, 0, -4] # Empty row, representing equation 0x + 0y - 4 = 0. ] </syntaxhighlight> <syntaxhighlight lang=python> data = [ [3, 0, -13], # Empty column representing 2 parallel lines: [2, 0, -4] # 3x = 13 and 2x = 4. ] </syntaxhighlight> The matrix above with name "data" is described as matrix "2 by 3," meaning that it contains 2 rows with 3 columns or 3 members per row. ==Solving 2 by 3== ===Implementation=== Below is python code containing function <code>solve2by3 (input).</code> The function accepts as input a matrix like <code>data</code> above. After the code are examples of invocation with both good data and bad data. <syntaxhighlight lang=python> import sys import decimal dD = decimal.Decimal def solve2by3 (input_, level=0) : ''' input represents system: a1*x + b1*y + c1 = 0 a2*x + b2*y + c2 = 0 input = ( (a1,b1,c1), (a2,b2,c2), ) To invoke: x,y = solve2by3 (input) Function solve2by3 () may return None. input is not changed by this function. ''' if level : thisName = 'solve2by3 (input_, level = {}) :'.format(level) else : thisName = 'solve2by3 (input_) :' try : error = 0 try : input = [ list(v) for v in input_ ] (a1,b1,c1), (a2,b2,c2) = input except : input = 0 input or {}['input_ not recognized.'] # six_values = a1,b1,c1, a2,b2,c2 for v in six_values : isinstance(v, (int, float, dD)) or {}['Non-numeric value in input.'] set1 = { isinstance(v, dD) for v in six_values } if len(set1) == 2 : # Mix of Decimal and non-Decimal in input. Make all type Decimal. (a1,b1,c1, a2,b2,c2) = [ dD(str(v)) for v in six_values ] # a1 or b1 or {}['Row 1 empty.'] ; a1 or a2 or {}['Column 1 empty.'] a2 or b2 or {}['Row 2 empty.'] ; b1 or b2 or {}['Column 2 empty.'] # if not a1 : # Make a1 non-zero. (a1,b1,c1),(a2,b2,c2) = (a2,b2,c2), (a1,b1,c1) # if a2 : # Make a2 zero. if a2 == a1 : a2,b2,c2 = a1-a2, b1-b2, c1-c2 elif a2 == -a1 : a2,b2,c2 = a1+a2, b1+b2, c1+c2 else : list1 = [ a2*v for v in (a1,b1,c1) ] list2 = [ a1*v for v in (a2,b2,c2) ] a2,b2,c2 = [ (v1-v2) for v1,v2 in zip (list1, list2) ] a2 and {}['Internal error. a2 should be 0.'] b2 or {}['Parallel input.'] # The matrix is: # a1, b1, c1 with a1 non-zero # 0, b2, c2 and b2 non-zero. # 0 x + b2 y + c2 = 0 y = -c2/b2 # a1 x + b1 y + c1 = 0 x = -(b1*y + c1)/a1 # Here is why a1 must be non-zero. output = x,y except : error = str(sys.exc_info())[1:].split(',') ; error[1:] = [ ','.join(error[1:-1]) ] # if error : print (thisName) for v in error : print (' ', v.strip()) if input : print (' input of solve2by3() =') print (' ', input[0]) print (' ', input[1]) return None # return output </syntaxhighlight> ====Examples==== Invocation with good data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve2by3([ [3, 2, -13], [2, -1, -4] ]) print (output) </syntaxhighlight> <pre> (3.0, 2.0) </pre> {{RoundBoxBottom}} Invocation with bad or invalid data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve2by3([ [3, 2, -13], # Both lines are parallel. [6, 4, -5] # See Figure 2 above. ]) print (output) </syntaxhighlight> <pre> solve2by3 (input_) : <class 'KeyError'> KeyError('Parallel input.') input of solve2by3() = [3, 2, -13] [6, 4, -5] None </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve2by3([ [3, 2, -13, 7], # Input matrix not exactly 2 by 3. [6, 4, -5] ]) print (output) </syntaxhighlight> <pre> solve2by3 (input_) : <class 'KeyError'> KeyError('input_ not recognized.') None </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve2by3([ [3, 0, 2], [6, 0, 4] ]) print (output) </syntaxhighlight> <pre> solve2by3 (input_) : <class 'KeyError'> KeyError('Column 2 empty.') input of solve2by3() = [3, 0, 2] [6, 0, 4] None </pre> {{RoundBoxBottom}} ===Reversing the process=== ====Linear Function==== [[File:1212line01.png|thumb|400px|''' Figure 1. Diagram of line defined by 2 points.''' </br> 2 points are: <math>(-5,4), (3,1).</math> </br> Equation of line is: <math>3x + 8y - 17 = 0.</math> ]] Examples above calculate the point of intersection of 2 lines. An example of reversing the process is this task: Given two points <math>(x_1, y_1), (x_2, y_2)</math> calculate equation of line containing these 2 points. Equation of line is of format <math>Ax + By + C = 0,</math> For example: <math>3x + 2y + 10 = 0\ \dots\ (1).</math> Equation <math>(1)</math> can be expressed as <math>6x + 4y + 20 = 0</math> or <math>-9x - 6y - 30 = 0.</math> Also, there appear to be 3 unknowns, but only two sets of values are required to define the line. Assume <math>C = 1</math> and the 2 relevant equations are: <math>Ax_1 + By_1 + 1 = 0</math> <math>Ax_2 + By_2 + 1 = 0</math> To solve for <math>A, B:</math> <math>x_1A + y_1B + 1 = 0</math> <math>x_2A + y_2B + 1 = 0</math> Suppose the line is defined by points <math>(3,1), (-5,4):</math> <syntaxhighlight lang=python> # python code: input = [ [3,1,1], [-5,4,1], ] result = solve2by3 (input) print (result) </syntaxhighlight> <syntaxhighlight> (-0.17647058823529413, -0.47058823529411764) </syntaxhighlight> Desired equation is: <math>-0.17647058823529413\cdot x -0.47058823529411764\cdot y + 1 = 0\ \dots\ (2).</math> To improve appearance of <math>(2):</math> <syntaxhighlight lang=python> # python code: print (A/B) </syntaxhighlight> <syntaxhighlight> 0.37500000000000006 </syntaxhighlight> Let <math>A, B = 3, 8</math> and check: <syntaxhighlight lang=python> # python code A,B = 3,8 p1 = x1,y1 = 3,1 p2 = x2,y2 = -5,4 for v in (p1,p2) : x,y = v C = -(A*x + B*y) s1 = 'C' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> C -17 C -17 </syntaxhighlight> Desired equation <math>(2)</math> becomes <math>3x + 8y - 17 = 0\ \dots\ (3).</math> ====Wrong assumptions==== [[File:1212line02.png|thumb|400px|''' Figure 2. Diagram of line defined by 2 points and passing through origin.''' </br> 2 points are: <math>(3,2), (6,4).</math> </br> Equation of line is: <math>2x - 3y = 0.</math> </br> Non-zero value for coefficient <math>C</math> is impossible. ]] Sometimes you create a matrix that seems correct, but it fails to produce a result. Here is such an example: What is equation of line defined by points <math>(3, 2), (6, 4)?</math> As above assume that <math>C = 1.</math> <syntaxhighlight lang=python> # python code: p1 = x1,y1 = 3,2 p2 = x2,y2 = 6,4 input = [ [x1,y1,1], [x2,y2,1], ] result = solve2by3 (input) print (result) </syntaxhighlight> This assumption failed: <syntaxhighlight> solve2by3() : parallel input. input = [3, 2, 1] [6, 4, 1] None </syntaxhighlight> Assume that <math>A = 1.</math> <syntaxhighlight lang=python> # python code: # 1(x1) + B(y1) + 1(C) = 0 # 1(x2) + B(y2) + 1(c) = 0 # y1(B) + 1(C) + x1 = 0 # y2(B) + 1(C) + x2 = 0 input = [ [y1,1,x1], # Notice that input has been [y2,1,x2], # rotated left by one column. ] result = solve2by3 (input) print (result) </syntaxhighlight> <syntaxhighlight> (-1.5, 0.0) </syntaxhighlight> Equation of line is: <math>1\cdot x + (-1.5)\cdot y + 0 = 0</math> or <math>2x - 3y = 0</math> This line includes the origin. Therefore constant <math>C</math> cannot be non-zero. Generally: * Without rotation, <math>A, B = \text{result}</math> and <math>C = 1.</math> * With rotation left by one column, <math>B, C = \text{result}</math> and <math>A = 1.</math> In this case: <syntaxhighlight lang=python> # python code: >>> B,C = result ; A = 1 >>> A,B,C >>> 1,-1.5,0 </syntaxhighlight> For example of big matrix that failed the first time, but was successful the second time, see [https://en.wikiversity.org/wiki/Solving_simultaneous_equations#Cubic_Resistive_Network cubic resistive network] below. ==Solving 3 by 4== Below is python code containing function <code>solve3by4 (input).</code> The function accepts as input a 3 by 4 matrix like that described in the code comments. In 3d coordinate geometry the equations <code>(1), (2), (3)</code> are the equations of 3 planes and the solution of the system is the point of intersection of the 3 planes. Given 3 random planes, there are 2 conditions that do not produce a unique point of intersection: * If 2 of the planes are parallel. See Figure 1 below. * If the 3 planes form a "tent" or "delta." See Figure 2, 3 or 4 below. A special case of this condition occurs when size of "tent" is zero, in which case all three planes intersect on a common line and there is an infinite number of solutions. See Figure 5 below. The trivial solution <math>(0, 0, 0)</math> is valid. See Figure 6 below. <code></code> <code></code> {{RoundBoxTop|theme=2}} <gallery> File:0726_2parallelPlanes.png|<small>Figure 1. When 2 planes are parallel, there is no point of intersection.</small> File:0730triangularTube.png|<small>Figure 2. Triangular tube, 3 planes that never intersect.</small> File:0726_3planes0.png|<small>Figure 3. 3 planes that form a "tent," view 1. There is no point of intersection.</small> File:0726_3planes1.png|<small>Figure 4. 3 planes that form a "tent," view 2. There is no point of intersection.</small> File:1109_3planes1.png|<small>Figure 5. 3 planes that intersect on a common line. Points <math>(6,6,1),</math> <math>(7,7,4),</math> <math>(8,8,7)</math> are on this line and are common to all 3 planes.</small> File:0729_3planes.png|<small>Figure 6. 3 planes that intersect at origin (0, 0, 0).</small> </gallery> {{RoundBoxBottom}} ===Auxiliary functions=== <syntaxhighlight lang=python> def two_planes_parallel (plane1, plane2) : ''' status = two_planes_parallel (plane1, plane2) status = True if parallel. ''' A1,B1,C1 = plane1[:3] A2,B2,C2 = plane2[:3] A3 = B1*C2 - B2*C1 B3 = C1*A2 - C2*A1 C3 = A1*B2 - A2*B1 return ({ A3,B3,C3 } == {0}) def check_three_rows (input) : ''' result = check_three_rows (input) result is None or string. ''' row0,row1,row2 = input if two_planes_parallel (row0,row1) : return 'Two rows parallel: 0,1' if two_planes_parallel (row0,row2) : return 'Two rows parallel: 0,2' if two_planes_parallel (row1,row2) : return 'Two rows parallel: 1,2' A0,B0,C0 = row0[:3] ; A1,B1,C1 = row1[:3] ; A2,B2,C2 = row2[:3] # Line at intersection of planes 1,2 has direction numbers: A3 = B1*C2 - B2*C1 ; B3 = C1*A2 - C2*A1 ; C3 = A1*B2 - A2*B1 # Line at intersection of planes 0,2 has direction numbers: A4 = B0*C2 - B2*C0 ; B4 = C0*A2 - C2*A0 ; C4 = A0*B2 - A2*B0 # Are 2 lines of intersection parallel? if two_planes_parallel ((A3,B3,C3), (A4,B4,C4)) : return 'Three rows form tent.' return None </syntaxhighlight> ===Implementation=== <syntaxhighlight lang=python> def solve3by4 (input_, level=0) : ''' input_ is : [ [a0,b0,c0,d0], [a1,b1,c1,d1], [a2,b2,c2,d2] ] representing system: a0*x + b0*y + c0*z + d0 = 0 a1*x + b1*y + c1*z + d1 = 0 a2*x + b2*y + c2*z + d2 = 0 x,y,z = solve3by4 (input) Function solve3by4 () may return None. input is not changed by this function. ''' if level : thisName = 'solve3by4 (input_, level = {}) :'.format(level) else : thisName = 'solve3by4 (input_) :' try : error = 0 try : input = [ list(v) for v in input_ ] (a0,b0,c0,d0), (a1,b1,c1,d1), (a2,b2,c2,d2) = input except : input = 0 input or {}['input_ not recognized.'] # twelve_values = a0,b0,c0,d0, a1,b1,c1,d1, a2,b2,c2,d2 for v in twelve_values : isinstance(v, (int, float, dD)) or {}['Non-numeric value in input.'] set1 = { isinstance(v, dD) for v in twelve_values } if len(set1) == 2 : # Mix of Decimal and non-Decimal in input. Make all type Decimal. (a0,b0,c0,d0, a1,b1,c1,d1, a2,b2,c2,d2) = [ dD(str(v)) for v in twelve_values ] # a0 or b0 or c0 or {}['Row 0 empty.'] ; a0 or a1 or a2 or {}['Column 0 empty.'] a1 or b1 or c1 or {}['Row 1 empty.'] ; b0 or b1 or b2 or {}['Column 1 empty.'] a2 or b2 or c2 or {}['Row 2 empty.'] ; c0 or c1 or c2 or {}['Column 2 empty.'] # input = [ [a0,b0,c0,d0], [a1,b1,c1,d1], [a2,b2,c2,d2] ] result = check_three_rows (input) ; result and {}[result] # if not a0 : # Make a0 non-zero. if a1 : input[0],input[1] = input[1],input[0] else : input[0],input[2] = input[2],input[0] # # The matrix is: # a0, b0, c0, d0 with a0 non-zero. # a1, b1, c1, d1 # a2, b2, c2, d2 # Process rows so that a1, a2 become zero. row0 = input[0] ; a0 = row0[0] for p in (1,2) : rowp = input[p] ; ap = rowp[0] if ap : if ap == a0 : input[p] = [ (v1-v2) for (v1,v2) in zip(row0, rowp) ] elif ap == -a0: input[p] = [ (v1+v2) for (v1,v2) in zip(row0, rowp) ] else : input[p] = [ (v0*ap-vp*a0) for (v0,vp) in zip(row0, rowp) ] if input[p][0] : {}['Internal error. input[{}][0] should be 0.'.format(p)] (a0,b0,c0,d0), (a1,b1,c1,d1), (a2,b2,c2,d2) = input # The matrix is: # a0, b0, c0, d0 with a0 non-zero. # 0, b1, c1, d1 # 0, b2, c2, d2 two_rows = (b1,c1,d1), (b2,c2,d2) output = solve2by3 (two_rows, level-1) if output : y,z = output # a0 x + b0 y + c0 z + d0 = 0 x = -(b0*y + c0*z + d0)/a0 # Here is why a0 must be non-zero. output = x,y,z except : error = str(sys.exc_info())[1:].split(',') ; error[1:] = [ ','.join(error[1:-1]) ] # if error : print (thisName) for v in error : print (' ', v.strip()) if input : print (' input of solve3by4() =') print (' ', input[0]) print (' ', input[1]) print (' ', input[2]) return None # return output </syntaxhighlight> ====Examples==== Below are examples of invocation with both good data and bad data. Invocation with good data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve3by4([ [2, -1, 3, -17], [1, 3, 2, -25] , [3, 2, -1, -12] , ]) print (output) </syntaxhighlight> <pre> (3.0, 4.0, 5.0) </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve3by4([ [12, -12, -5, -24], [-6, 15, 8, 12] , [ 0, 10, 3, 0] , ]) print (output) </syntaxhighlight> <pre> (2.0, 0.0, -0.0) </pre> {{RoundBoxBottom}} Invocation with bad or invalid data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve3by4([ [20, 16, 2, 17], [-77, -27, -25, -24], [81, 45, 18, 43] ]) print (output) </syntaxhighlight> <pre> solve3by4 (input_) : <class 'KeyError'> KeyError('Three rows form tent.') input of solve3by4() = [20, 16, 2, 17] [-77, -27, -25, -24] [81, 45, 18, 43] None </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve3by4([ [34, -5, -21, 30], [-54, -33, 63, 62], [18, 11, -21, 38] ]) print (output) </syntaxhighlight> <pre> solve3by4 (input_) : <class 'KeyError'> KeyError('Two rows parallel: 1,2') input of solve3by4() = [34, -5, -21, 30] [-54, -33, 63, 62] [18, 11, -21, 38] None </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve3by4([ [20, 16, 2, 17], [-77, -27, '-25', -24], [81, 45, 18, 43] ]) print (output) </syntaxhighlight> <pre> solve3by4 (input_) : <class 'KeyError'> KeyError('Non-numeric value in input.') input of solve3by4() = [20, 16, 2, 17] [-77, -27, '-25', -24] [81, 45, 18, 43] None </pre> {{RoundBoxBottom}} ===Reversing the Process=== ====Quadratic function==== [[File:1212quadratic01.png|thumb|400px|''' Figure 1. Graph of quadratic function defined by 3 points.''' ]] A quadratic function <math>y = f(x) = Ax^2 + Bx + C</math> is defined by 3 points: <math>(-2, 9.0), (5, 4.8), (10, 13.8).</math> What is <math>f(x)?</math> <math>y = Ax^2 + Bx + C</math> <math>A, B, C</math> are 3 unknowns. <math>x^2(A) + x(B) + 1(C) - y = 0</math> <syntaxhighlight lang=python> # python code: x1,y1 = -2, 9 x2,y2 = 5, 4.8 x3,y3 = 10, 13.8 input = [ [x1**2, x1, 1, -y1], [x2**2, x2, 1, -y2], [x3**2, x3, 1, -y3], ] A, B, C = solve3by4 (input) s1 = 'A,B,C' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> A,B,C (0.2, -1.2, 5.8) </syntaxhighlight> <math>y = f(x) = 0.2x^2 - 1.2x + 5.8</math> ====Wrong assumptions==== [[File:1212plane02.png|thumb|400px|''' Figure 2. Graph of plane containing X axis.''' </br> Because plane passes through origin, non-zero value for coefficient <math>D</math> is impossible. </br> Because plane is parallel to <math>X</math> axis, non-zero value for coefficient <math>A</math> is impossible. ]] In 3 dimensions a plane (<math>Ax + By + Cz + D = 0</math>) is defined by 3 points: <math>(5, 3, -2), (-1, 12, -8), (37, 15, -10).</math> What is equation of plane? <math>Ax + By + Cz + D = 0</math> <math>xA + yB + zC + D = 0</math> Assume that <math>D = 1.</math> <math>xA + yB + zC + 1 = 0</math> <syntaxhighlight lang=python> # python code pt1 = x1,y1,z1 = (5, 3, -2) pt2 = x2,y2,z2 = (-1, 12, -8) pt3 = x3,y3,z3 = (37, 15, -10) input = [ [ 5, 3, -2, 1], [-1, 12, -8, 1], [37, 15, -10, 1], ] result = solve3by4 (input) s1 = 'result' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> solve2by3() : parallel input. input = (-63, 42, -6) (36, -24, 32) checkDirectionNumbers() : 3 rows form a tent. input of solve3by4() = (5, 3, -2, 1) (-1, 12, -8, 1) (37, 15, -10, 1) result None </syntaxhighlight> Input was invalid. Rotate input left and try again. <syntaxhighlight lang=python> # python code. input = [ [ 3, -2, 1, 5], [12, -8, 1, -1], [15, -10, 1, 37], ] result = solve3by4 (input) s1 = 'result' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> solve2by3() : empty column in input. input = (0, 9, 63) (0, 12, -36) checkDirectionNumbers() : 3 rows form a tent. input of solve3by4() = (3, -2, 1, 5) (12, -8, 1, -1) (15, -10, 1, 37) result None </syntaxhighlight> Input was invalid. Rotate input left and try again. <syntaxhighlight lang=python> input = [ [ -2, 1, 5, 3], [ -8, 1, -1, 12], [-10, 1, 37, 15], ] result = solve3by4 (input) s1 = 'result' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> result (1.5, 0, 0) </syntaxhighlight> Without rotation: <math>A, B, C = \text{result}</math> and <math>D = 1.</math> With rotation left: <math>B, C, D = \text{result}</math> and <math>A = 1.</math> With another rotation left: <math>C, D, A = \text{result}</math> and <math>B = 1.</math> <syntaxhighlight lang=python> # python code: C, D, A = (1.5, 0, 0) ; B = 1 A, B, C, D </syntaxhighlight> <syntaxhighlight> (0, 1, 1.5, 0) </syntaxhighlight> Equation of plane is: <math>0x + 1y + 1.5z + 0 = 0</math> or <math>2y + 3z = 0</math> =====A better method===== {{RoundBoxTop|theme=3}} There are four unknown values: <math>A,B,C,D.</math> Create matrix 4 by 5: <syntaxhighlight lang=python> # python code. pt1 = x1,y1,z1 = (5, 3, -2) pt2 = x2,y2,z2 = (-1, 12, -8) pt3 = x3,y3,z3 = (37, 15, -10) input = [] for (x_,y_,z_) in (pt1,pt2,pt3) : x,y,z = [ dD(v) for v in (x_,y_,z_) ] input += [ [ x,y,z,1,0 ] ] # For valid plane at least one of A,B,C must be non-zero. # For last condition let A + B + C = 5. input += [ [ 1,1,1,0,-5 ] ] A,B,C,D = solveMbyN(input) print (input) print ( '({})x + ({})y + ({})z + ({}) = 0'.format(A,B,C,D) ) </syntaxhighlight> <syntaxhighlight> [[ 5, 3, -2, 1, 0], # 5A + 3B - 2C + 1D + 0 = 0 [-1, 12, -8, 1, 0], # -1A + 12B - 8C + 1D + 0 = 0 [37, 15, -10, 1, 0], # 37A + 15B - 10C + 1D + 0 = 0 [ 1, 1, 1, 0, -5]] # 1A + 1B + 1C + 0D - 5 = 0 (0)x + (2)y + (3)z + (0) = 0 </syntaxhighlight> Equation of plane is: <math>2y + 3z = 0.</math> {{RoundBoxBottom}} ==Solving M by (M+1)== ===Implementation=== Below is python code containing function <code>solveMbyN (input).</code> The function accepts as input a 4 by 5 matrix (or greater) like that described in the code comments. This function is recursive, calling itself with M being reduced by 1 with each recursive invocation until the matrix is size 3 by 4 in which case function solve3by4() is called. <syntaxhighlight lang=python> # python code enable_reduceRow = 0 FPE = FloatingPointError # Not used by python. Used here as target of 'goto'. def solveMbyN (input_, level=0) : ''' Input represents system: a0*w + b0*x + c0*y + d0*z + e0 = 0 a1*w + b1*x + c1*y + d1*z + e1 = 0 a2*w + b2*x + c2*y + d2*z + e2 = 0 a3*w + b3*x + c3*y + d3*z + e3 = 0 or greater. This solves a matrix of M rows by N columns where N = M+1 and M >= 2 input = [ (a0,b0,c0,d0,e0), (a1,b1,c1,d1,e1), (a2,b2,c2,d2,e2), (a3,b3,c3,d3,e3), ] To invoke: w,x,y,z = solveMbyN (input [, level]) Function solveMbyN () may return None. If input is size 15 by 16: v1,v2,v3, .... ,v14,v15 = solveMbyN (input) Input is not changed by this function. ''' thisName = 'solveMbyN (input_, level = {}) :'.format(level) try : error = 0 try: input = [ list(v) for v in input_ ] except : input = 0 input or {}['input_ not recognized.'] number_of_rows = len(input) (number_of_rows > 1) or {}['number_of_rows must be > 1.'] if number_of_rows == 2 : output = solve2by3(input, level) raise FPE # Equivalent to goto. if number_of_rows == 3 : output = solve3by4(input, level) raise FPE # Equivalent to goto. number_of_columns = number_of_rows + 1 if level == 0 : dD_count = other_count = 0 for row_number in range (number_of_rows-1,-1,-1) : row = input[row_number] # Check that each row is correct length. if (len(row) != number_of_columns) : error = [ 'row # {} has bad length: {}'.format(row_number, len(row))] error += [ 'Correct length is : {}'.format(number_of_columns)] raise FPE for v in row : # Check that all data is numeric. isinstance(v, (int,float,dD)) or {}['Non-numeric value in input.'] # Record if type dD or not. if isinstance(v, dD) : dD_count += 1 else : other_count += 1 if dD_count and other_count : # Mix of types Decimal and non-Decimal in input. Make all values type Decimal. input = [ [ dD(str(p)) for p in row ] for row in input ] # Each row must not be empty. for row_number in range (number_of_rows-1,-1,-1) : found = 0 for v in input[row_number][:-1]: if v : found = 1 ; break if not found : {}['Empty row in input: # {} of {} rows.'.format(row_number, number_of_rows)] # Arrange input if necessary so that a0 is non-zero. if not input[0][0] : for p in range (1, number_of_rows) : if input[p][0] : input[p], input[0] = input[0], input[p] break # The matrix is: # [a0,b0,c0,d0,e0], with a0 non-zero, # [a1,b1,c1,d1,e1], # [a2,b2,c2,d2,e2], # [a3,b3,c3,d3,e3], # If abs(level) is large, following test can produce error: # OverflowError('int too large to convert to float') # Solution is to convert values in input to type float or Decimal. dD(input[0][0]) ; float(input[0][0]) # Each column must not be empty. for column_number in range (number_of_columns-2,-1,-1) : found = 0 for row in input : if row[column_number] : found = 1 ; break if not found : {}['Empty column in input: # {} of {} columns.'.format(column_number, number_of_columns)] if enable_reduceRow : # global variable # For matrices greater than 10 by 11 enable this piece of code. # This code calculates the max(abs) of all values in row, # divides all values by the max(abs) and updates row with result. # [27, -15, 42] becomes [27/42, -15/42, 42/42]. # Without this code you may see: # solveMbyN (input, level = -52) : # <class 'decimal.Overflow'> # Overflow([<class 'decimal.Overflow'>]) for row in input : max = 0 for v in row : if abs(v) > max : max = abs(v) if max < 1e100 : continue for column_number in range (number_of_columns-1,-1,-1) : if row[column_number] : row[column_number] /= max # Process rows so that a1, a2, a3, .... become zero. row0 = input[0] ; a0 = row0[0] for p in range (1, number_of_rows) : rowp = input[p] ; ap = rowp[0] if ap : if ap == a0 : input[p] = [ (v1-v2) for (v1,v2) in zip(row0, rowp) ] elif ap == -a0: input[p] = [ (v1+v2) for (v1,v2) in zip(row0, rowp) ] else : input[p] = [ (v0*ap-vp*a0) for (v0,vp) in zip(row0, rowp) ] if input[p][0] : try: str1 = str(float(input[p][0])) except : str1 = 'Error' {}['Internal error. input[{}][0] = {}, should be 0.'.format(p,str1)] # The matrix is: # [a0, b0, c0, d0, e0], with a0 non-zero, # [ 0, b1, c1, d1, e1], # [ 0, b2, c2, d2, e2], # [ 0, b3, c3, d3, e3], next_input = [ row[1:] for row in input[1:] ] # next_input is : # [ b1, c1, d1, e1], # [ b2, c2, d2, e2], # [ b3, c3, d3, e3], output = solveMbyN (next_input, level-1) # Here is where function solveMbyN() calls itself. if output : # input[0] = a0, b0, c0, d0, e0 # output = x, y, z (len(input[0][1:-1]) == len(output)) or {}["Internal error. Inputs to zip() don't match."] listOfProducts = [ v1*v2 for v1,v2 in zip(input[0][1:-1], output) ] # listOfProducts = [ b0*x, c0*y, d0*z ] sumOfProducts = input[0][-1] for v in listOfProducts : sumOfProducts += v # sumOfProducts = b0*x + c0*y + d0*z + e0 # a0*w + b0*x + c0*y + d0*z + e0 = 0 # a0*w + sumOfProducts = 0 w = -sumOfProducts/a0 # Here is why a0 must be non-zero. output = (w,) + output except FPE : pass # Target of 'goto'. except : error = str(sys.exc_info())[1:].split(',') ; error[1:] = [ ','.join(error[1:-1]) ] # if error : print (thisName) for v in error : print (' ', v.strip()) if input : print (' Length of input =', len(input)) for p in range (0, len(input)) : if p >= 8 : break try : row = [ float(v) for v in input_[p] ] except : row = 'Error in this row.' print (' input_[{}] ='.format(p), row) return None # return output </syntaxhighlight> ===Examples=== Below are examples of invocation with both good data and bad data. Invocation with good data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> L1 = [ [Decimal('-870442133162'), Decimal('239132906684'), Decimal('397660499756'), Decimal('788825405004'), Decimal('156830886652'), Decimal('-87096140169')], [Decimal('-112130420352'), Decimal('-93605595828'), Decimal('-185262083472'), Decimal('-93369903383'), Decimal('-497973505065'), Decimal('-766710012513')], [Decimal('-142983492168'), Decimal('619713461197'), Decimal('-608752759383'), Decimal('-448477443042'), Decimal('-281161661751'), Decimal('-799463977245')], [Decimal('572854919541'), Decimal('-148673693908'), Decimal('341291756040'), Decimal('362403188059'), Decimal('-202136092949'), Decimal('-429932229578')], [Decimal('157632861972'), Decimal('330790263276'), Decimal('-836474627955'), Decimal('644295395386'), Decimal('-595590967129'), Decimal('-392835045727')] ] output = solveMbyN(L1) print (output) </syntaxhighlight> The following results were produced with decimal precision set at 50: <pre> ( Decimal('-0.06331410760212760088313271882866553044211194694576'), Decimal('1.0969089506763419155148060427588009931309074487534'), Decimal('1.0837038580207682607126722016017867670831200359767'), Decimal('-0.42989566124678842791674322699930461340596671792215'), Decimal('-2.0541601084281682582146753421426610779297051535362') ) </pre> {{RoundBoxBottom}} Invocation with bad or invalid data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solveMbyN([ [-4, -6, 3, -4, -8, -8], [1, 0, 2, 5, 1, 7], [9, -3, -8, 4, 7, -5], [1, -9, 5, -2, 5, -2], [1, -3, -6, -3, -6, 6] ]) print (output) </syntaxhighlight> <pre> # With each step towards solve2by3() the length of each number in digits can theoretically double. solve2by3() : parallel input. input = (-181440, 181440, -101088) (90720, -90720, 406944) checkDirectionNumbers() : 3 rows form a tent. input of solve3by4() = [-756, -1176, 0, -1872] [-324, -744, 240, -936] [-324, -384, -120, -264] input of solveMbyN() with 4 rows = [-6, 11, 16, -4, 20] [-66, -5, -20, -44, -92] [-42, 23, -12, 12, -16] [-18, -21, -16, -32, 16] input of solveMbyN() with 5 rows = [-4, -6, 3, -4, -8, -8] [1, 0, 2, 5, 1, 7] [9, -3, -8, 4, 7, -5] [1, -9, 5, -2, 5, -2] [1, -3, -6, -3, -6, 6] None </pre> Provided that numbers are small, integers, floats and Decimal objects produce the same results: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solveMbyN([ [-4.0, -6.0, 3.0, -4.0, -8.0, -8.0], [1.0, 0.0, 2.0, 5.0, 1.0, 7.0], [9.0, -3.0, -8.0, 4.0, 7.0, -5.0], [1.0, -9.0, 5.0, -2.0, 5.0, -2.0], [1.0, -3.0, -6.0, -3.0, -6.0, 6.0] ]) print (output) </syntaxhighlight> <pre> solve2by3() : parallel input. input = (-181440.0, 181440.0, -101088.0) (90720.0, -90720.0, 406944.0) checkDirectionNumbers() : 3 rows form a tent. input of solve3by4() = [-756.0, -1176.0, 0.0, -1872.0] [-324.0, -744.0, 240.0, -936.0] [-324.0, -384.0, -120.0, -264.0] input of solveMbyN() with 4 rows = [-6.0, 11.0, 16.0, -4.0, 20.0] [-66.0, -5.0, -20.0, -44.0, -92.0] [-42.0, 23.0, -12.0, 12.0, -16.0] [-18.0, -21.0, -16.0, -32.0, 16.0] input of solveMbyN() with 5 rows = [-4.0, -6.0, 3.0, -4.0, -8.0, -8.0] [1.0, 0.0, 2.0, 5.0, 1.0, 7.0] [9.0, -3.0, -8.0, 4.0, 7.0, -5.0] [1.0, -9.0, 5.0, -2.0, 5.0, -2.0] [1.0, -3.0, -6.0, -3.0, -6.0, 6.0] None </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solveMbyN([ [Decimal('-4'), Decimal('-6'), Decimal('3'), Decimal('-4'), Decimal('-8'), Decimal('-8')], [Decimal('1'), Decimal('0'), Decimal('2'), Decimal('5'), Decimal('1'), Decimal('7')], [Decimal('9'), Decimal('-3'), Decimal('-8'), Decimal('4'), Decimal('7'), Decimal('-5')], [Decimal('1'), Decimal('-9'), Decimal('5'), Decimal('-2'), Decimal('5'), Decimal('-2')], [Decimal('1'), Decimal('-3'), Decimal('-6'), Decimal('-3'), Decimal('-6'), Decimal('6')] ]) print (output) </syntaxhighlight> <pre> solve2by3() : parallel input. input = (Decimal('-181440'), Decimal('181440'), Decimal('-101088')) (Decimal('90720'), Decimal('-90720'), Decimal('406944')) checkDirectionNumbers() : 3 rows form a tent. input of solve3by4() = [Decimal('-756'), Decimal('-1176'), Decimal('0'), Decimal('-1872')] [Decimal('-324'), Decimal('-744'), Decimal('240'), Decimal('-936')] [Decimal('-324'), Decimal('-384'), Decimal('-120'), Decimal('-264')] input of solveMbyN() with 4 rows = [Decimal('-6'), Decimal('11'), Decimal('16'), Decimal('-4'), Decimal('20')] [Decimal('-66'), Decimal('-5'), Decimal('-20'), Decimal('-44'), Decimal('-92')] [Decimal('-42'), Decimal('23'), Decimal('-12'), Decimal('12'), Decimal('-16')] [Decimal('-18'), Decimal('-21'), Decimal('-16'), Decimal('-32'), Decimal('16')] input of solveMbyN() with 5 rows = [Decimal('-4'), Decimal('-6'), Decimal('3'), Decimal('-4'), Decimal('-8'), Decimal('-8')] [Decimal('1'), Decimal('0'), Decimal('2'), Decimal('5'), Decimal('1'), Decimal('7')] [Decimal('9'), Decimal('-3'), Decimal('-8'), Decimal('4'), Decimal('7'), Decimal('-5')] [Decimal('1'), Decimal('-9'), Decimal('5'), Decimal('-2'), Decimal('5'), Decimal('-2')] [Decimal('1'), Decimal('-3'), Decimal('-6'), Decimal('-3'), Decimal('-6'), Decimal('6')] None </pre> {{RoundBoxBottom}} {{RoundBoxBottom}} ===Sphere=== In cartesian coordinate geometry of three dimensions a sphere is represented by equation: <math>x^2 + y^2 + z^2 + Ax + By + Cz + D = 0.</math> On the surface of a certain sphere there are 4 known points: <syntaxhighlight lang=python> # python code point1 = (13,7,20) point2 = (13,7,4) point3 = (13,-17,4) point4 = (16,4,4) </syntaxhighlight> What is equation of sphere? Rearrange equation of sphere to prepare for creation of input matrix: <math>(x)A + (y)B + (z)C + (1)D + (x^2 + y^2 + z^2) = 0.</math> Create input matrix of size 4 by 5: <syntaxhighlight lang=python> # python code input = [] for (x,y,z) in (point1, point2, point3, point4) : input += [ ( x, y, z, 1, (x**2 + y**2 + z**2) ) ] print (input) </syntaxhighlight> <syntaxhighlight> [ (13, 7, 20, 1, 618), (13, 7, 4, 1, 234), (13, -17, 4, 1, 474), (16, 4, 4, 1, 288), ] # Matrix containing 4 rows with 5 members per row. </syntaxhighlight> <syntaxhighlight lang=python> # python code result = solveMbyN(input) print (result) </syntaxhighlight> <syntaxhighlight> (-8.0, 10.0, -24.0, -104.0) </syntaxhighlight> Equation of sphere is : <math>x^2 + y^2 + z^2 - 8x + 10y - 24z - 104 = 0</math> ===Quintic function=== [[File:1212quintic01.png|thumb|400px|''' Figure 4. Graph of quintic function defined by 6 points.''' ]] A quintic function <math>y = f(x) = Ax^5 + Bx^4 + Cx^3 + Dx^2 + Ex + F</math> is defined by 6 points: <math>(-8, 0), (-6, 0), (-3, 0), (1,0), (3,0), (5,10).</math> What is <math>f(x)?</math> <math>y = f(x) = Ax^5 + Bx^4 + Cx^3 + Dx^2 + Ex + F</math> <math>A, B, C, D, E, F</math> are 6 unknowns. <math>x^5(A) + x^4(B) + x^3(C) + x^2(D) + x(E) + 1(F) - y = 0</math> <syntaxhighlight lang=python> # python code: pt1 = x1,y1 = -8,0 pt2 = x2,y2 = -6,0 pt3 = x3,y3 = -3,0 pt4 = x4,y4 = 1,0 pt5 = x4,y5 = 3,0 pt6 = x6,y6 = 5,10 input = [] for pt in (pt1,pt2,pt3,pt4,pt5,pt6) : x,y = pt input += [[ x**5, x**4, x**3, x**2, x, 1, -y ]] print (input) </syntaxhighlight> <syntaxhighlight> [[-32768, 4096, -512, 64, -8, 1, 0], [ -7776, 1296, -216, 36, -6, 1, 0], [ -243, 81, -27, 9, -3, 1, 0], [ 1, 1, 1, 1, 1, 1, 0], [ 243, 81, 27, 9, 3, 1, 0], [ 3125, 625, 125, 25, 5, 1, -10]] </syntaxhighlight> <syntaxhighlight> result = solveMbyN (input) s1 = 'result' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> result (0.0010926573426573423, 0.014204545454545447, 0.027316433566433533, -0.18028846153846156, -0.3343531468531468, 0.47202797202797203) </syntaxhighlight> From these results the following ratios may be deduced: <math>\frac{1}{A} = 915.2;\ </math> <math>\frac{B}{A} = 13;\ </math> <math>\frac{C}{A} = 25;\ </math> <math>\frac{D}{A} = -165;\ </math> <math>\frac{E}{A} = -306;\ </math> <math>\frac{F}{A} = 432.</math> <math>y = f(x) = \frac{x^5 + 13x^4 + 25x^3 - 165x^2 - 306x + 432}{915.2}</math> ===Resistive network=== {{RoundBoxTop|theme=2}} [[File:1127network01.png|thumb|400px|''' Figure 1. Diagram of resistive network containing 8 resistors.''' ]] A resistive network containing 8 resistors is connected as shown in Figure 1. What is resistance <math>R</math> between points <math>P_1, P_3?</math> {{RoundBoxBottom}} ====Solve for 8 Branch Currents==== {{RoundBoxTop|theme=2}} [[File:1127network02.png|thumb|400px|''' Figure 2. Diagram of resistive network showing all branch currents.''' </br> </br> At any point to which 3 or more conductors are connected, sum of currents = 0. </br> At point <math>P_4</math> currents <math>i_1, i_7</math> flow towards point; current <math>i_4</math> flows away from point. </br> <math>i_1 + i_7 - i_4 = 0.</math> </br> </br> In any closed loop sum of voltages = 0. </br> In loop containing points <math>P_1, P_2</math> voltages <math>e_2, e_8</math> are clockwise; voltage <math>e_3</math> is counter-clockwise. <math></math> </br> <math>e_2 + e_8 - e_3 = 0.</math><math></math><math></math> </br> </br> Direction of flow through <math>r_7, r_8</math> is assumed and is subject to correction. ]] Voltage across <math>r_1:</math> Using <math>E = IR,\ e_1 = i_1\cdot r_1 = r_1\cdot a.</math> Similarly: <math>e_2 = r_2\cdot b.</math> <math>e_3 = r_3\cdot c.</math> <math>\dots\dots</math> <math>e_8 = r_8\cdot h.</math> Build a matrix size 8 by 9 which will be input to function solveMbyN(). <syntaxhighlight lang=python> # Python code: r1,r2,r3,r4,r5,r6,r7,r8 = 10,20,30,40,50,60,70,80 input = [] # e1 = e2 + e7 # 10a = 20b + 70g # 10a - 20b + 0c + 0d + 0e + 0f - 70g + 0h + 0 = 0 input += [[r1, - r2, 0, 0, 0, 0, - r7, 0, 0]] # e3 = e2 + e8 # 30c = 20b + 80h # 0a - 20b + 30c + 0d + 0e + 0f + 0g - 80h + 0 = 0 input += [[0, - r2, r3, 0, 0, 0, 0, - r8, 0]] # e5 = e7 + e4 # 50e = 70g + 40d # 0a + 0b + 0c - 40d + 50e + 0f - 70g + 0h + 0 = 0 input += [[0, 0, 0, - r4, r5, 0, - r7, 0, 0]] # e5 = e8 + e6 # 50e = 80h + 60f # 0a + 0b + 0c + 0d + 50e - 60f + 0g - 80h + 0 = 0 input += [[0, 0, 0, 0, r5, - r6, 0, - r8, 0]] # i7 + i5 + i8 = i2 # g + e + h = b # 0a - 1b + 0c + 0d + 1e + 0f + 1g + 1h + 0 = 0 input += [[0 ,- 1, 0, 0, 1, 0, 1, 1, 0]] # i4 = i1 + i7 # d = a + g # -1a + 0b + 0c + 1d + 0e + 0f - 1g + 0h + 0 = 0 input += [[-1, 0, 0, 1, 0, 0, - 1, 0, 0]] # i6 = i3 + i8 # f = c + h # 0a + 0b - 1c + 0d + 0e + 1f + 0g - 1h + 0 = 0 input += [[0, 0, - 1, 0, 0, 1, 0, - 1, 0]] # Total input current = 1 # a + b + c = 1 # 1a + 1b + 1c + 0d + 0e + 0f + 0g + 0h - 1 = 0 input += [[1, 1, 1, 0, 0, 0, 0, 0, - 1]] </syntaxhighlight> This last entry can contain almost any arbitrary values. For example: <syntaxhighlight lang=python> # Python code: # i7 = 2.3 input += [[0, 0, 0, 0, 0, 0, 1, 0, - 2.3]] # e5 = 1.9 input += [[0, 0, 0, 0, r5, 0, 0, 0, - 1.9]] </syntaxhighlight> Changing this last entry changes all values of <math>e_x, i_x.</math> However, the ratio <math>\frac{e_x}{i_x} = r_x</math> remains constant. {{RoundBoxTop|theme=3}} input is matrix of size 8 by 9: <syntaxhighlight> [ [10, -20, 0, 0, 0, 0, -70, 0, 0], # e1 = e2 + e7, or r1(i1) - r2(i2) - r7(i7) = 0 [ 0, -20, 30, 0, 0, 0, 0, -80, 0], # e3 = e2 + e8, or r3(i3) - r2(i2) - r8(i8) = 0 [ 0, 0, 0, -40, 50, 0, -70, 0, 0], # e5 = e4 + e7, or r5(i5) - r4(i4) - r7(i7) = 0 [ 0, 0, 0, 0, 50, -60, 0, -80, 0], # e5 = e6 + e8, or r5(i5) - r6(i6) - r8(i8) = 0 [ 0, -1, 0, 0, 1, 0, 1, 1, 0], # i2 = i5 + i7 + i8, or 1(i5) + 1(i7) + 1(i8) - 1(i2) = 0 [-1, 0, 0, 1, 0, 0, -1, 0, 0], # i4 = i1 + i7, or 1(i4) - 1(i1) - 1(i7) = 0 [ 0, 0, -1, 0, 0, 1, 0, -1, 0], # i6 = i3 + i8, or 1(i6) - 1(i3) - 1(i8) = 0 [ 1, 1, 1, 0, 0, 0, 0, 0, -1] # i1 + i2 + i3 = 1, or 1(i1) + 1(i2) + 1(i3) - 1 = 0 ] </syntaxhighlight> {{RoundBoxBottom}} <syntaxhighlight lang=python> i1,i2,i3,i4,i5,i6,i7,i8 = values_of_i = solveMbyN (input) s1 = 'values_of_i' ; print(s1,eval(s1)) s1 = 'i1 + i2 + i3' ; print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> values_of_i (0.45727389222364606, 0.3065353746543468, 0.23619073312200717, 0.4350171983543536, 0.31685438726647336, 0.24812841437917316, -0.022256693869292507, 0.011937681257165982) i1 + i2 + i3 1.0 </syntaxhighlight> <math>i_7</math> has negative value. Reverse <math>i_7</math> to make all branch currents positive. {{RoundBoxBottom}} ====Make all Branch Currents positive==== {{RoundBoxTop|theme=2}} [[File:1127network03.png|thumb|400px|''' Figure 3. Diagram of resistive network showing all branch currents positive.''' ]] Make <math>i_7</math> positive and check results. <syntaxhighlight lang=python> # Python code i7 *= -1 values_of_e = e1,e2,e3,e4,e5,e6,e7,e8 = [ eval(s1) for s in '12345678' for s1 in [ 'i' + s + '*r' + s ] ] s1 = 'values_of_e' print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> values_of_e [ 4.572738922236461, 6.130707493086937, 7.085721993660215, 17.400687934174144, 15.842719363323669, 14.88770486275039, 1.5579685708504756, 0.9550145005732785] </syntaxhighlight> <syntaxhighlight lang=python> # python code t1 = ( 'e1+e7-e2', # e1 + e7 should equal e2 'e2+e8-e3', # e2 + e8 should equal e3 'e7+e5-e4', # e7 + e5 should equal e4 'e8+e6-e5', # e8 + e6 should equal e5 'e1+e4-(e2+e5)', # e1 + e4 should equal e2 + e5 'e1+e4-(e3+e6)', # e1 + e4 should equal e3 + e6 'e1+e7+e8-e3', # e1 + e7 + e8 should equal e3 'e7+e8+e6-e4', # e7 + e8 + e6 should equal e4 'i1-i7-i4', # i1 should equal i7 + i4 'i6-i3-i8', # i6 should equal i3 + i8 'i2+i7-(i8+i5)', # i2 + i7 should equal i8 + i5 'i1+i2+i3 - (i4+i5+i6)', # Total input current should # equal total output current. ) for s1 in t1 : print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> e1+e7-e2 -8.881784197001252e-16 e2+e8-e3 0.0 e7+e5-e4 0.0 e8+e6-e5 0.0 e1+e4-(e2+e5) 0.0 e1+e4-(e3+e6) 0.0 e1+e7+e8-e3 -8.881784197001252e-16 e7+e8+e6-e4 0.0 i1-i7-i4 -5.551115123125783e-17 i6-i3-i8 6.938893903907228e-18 i2+i7-(i8+i5) 0.0 i1+i2+i3 - (i4+i5+i6) 0.0 </syntaxhighlight> {{RoundBoxBottom}} ====Compute R==== {{RoundBoxTop|theme=8}} <syntaxhighlight lang=python> # Python code E1 = e3+e6 I1 = i1 + i2 + i3 R1 = E1/I1 s1 = 'R1' ; print(s1,eval(s1)) E2 = e1 + e7 + e5 I2 = i4 + i5 + i6 R2 = E2/I2 s1 = 'R2' ; print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> R1 21.973426856410605 R2 21.973426856410605 </syntaxhighlight> <math>R = R_1 = R_2</math> {{RoundBoxBottom}} ==Solving big matrices== A big matrix is one of size greater than 10 by 11. With each recursive call of solveMbyN() the size of each value in decimal digits can theoretically double. Python's integer math enjoys infinite precision. If your original matrix is of size 32 by 33, and each value in the matrix is an int of 1 decimal digit, function solve2by3() can be called with ints of size 2**30 (1,073,741,824) decimal digits. Floats can be used instead of ints, but the limited precision of floats may not provide a desirable level of accuracy in the result. Python's decimal objects are a good compromise and function reduceRow() above is an attempt to keep the size of each member manageable. Function reduceRow() works well. However, as with all operations involving python's decimal objects, you need to pay careful attention to precision and accuracy of the results. On my Mac the following python code generates a matrix of size 100 by 101 and calculates the result containing 100 values in about 1.5 seconds, including the time to generate 10,100 random numbers, each containing up to 12 decimal digits with the decimal point in a random position, and including the time to test output over 100 rows to verify that all calculated values of the solution satisfy each row. In function solveMbyN() above find line: <syntaxhighlight lang=python> if 0 : # For matrices greater than 10 by 11 enable this piece of code. </syntaxhighlight> Change it to: <syntaxhighlight lang=python> if 1 : # For matrices greater than 10 by 11 enable this piece of code. </syntaxhighlight> Then: <syntaxhighlight lang=python> from random import getrandbits from decimal import * import sys getcontext().prec=50 # Set precision to 50. numRows=100 def randomNumber(): # 1 invocation in 256 returns 0. if not (getrandbits(10) & 0xFF) : return Decimal(0) return [ w for q in [ getrandbits(10) & 1] for sign in [ (-1,1)[q] ] for numberOfDecimalPlaces in [ getrandbits(10) & 0xF ] for s1 in [ str(getrandbits(50))[-12:] ] for s2 in [ '0'*12+s1 ] for posn in [ len(s2)-numberOfDecimalPlaces ] for w in [ sign*Decimal(s2[:posn]+'.'+s2[posn:]) ] ][0] data = [[ randomNumber() for p in range(numRows+1) ] for p in range (numRows) ] datan = sorted([ v for row in data for v in row if v < 0 ]) datap = sorted([ v for row in data for v in row if v >= 0 ]) print ('A small sample of the random numbers in data:') print ('+ve values:',len(datap), ',', datap[:2],'\n ',datap[-2:]) print ('-ve values:',len(datan), ',', datan[:2],'\n ',datan[-2:]) output = solveMbyN(data) print ('A small sample of the solutions:') print ('output[0] =', output[0]) print ('output[19] =', output[19]) print ('output[59] =', output[59]) print ('output[99] =', output[99]) </syntaxhighlight> <pre> A small sample of the random numbers in data: +ve values: 5021 , [Decimal('1.16871265E-7'), Decimal('1.73721245E-7')] [Decimal('998523464710'), Decimal('999768605679')] -ve values: 5079 , [Decimal('-991079944209'), Decimal('-989786083110')] [Decimal('-4.10272824E-7'), Decimal('-2.38664537E-7')] A small sample of the solutions: output[0] = 0.43689400018920695253771832432651757885163362928745 output[19] = 0.19867480862268284151047885891372314311902973127033 output[59] = 0.46169681824826309421940885550155275946668017604646 output[99] = -0.020598220802233733529683040085023443421113627790464 </pre> ===Testing results=== Data input to function solveMbyN() is an array of 100 rows, each row containing 101 numbers. <pre> [ [v0_0, v0_1, v0_2, ..... v0_98,v0_99,v0_100], ....... [v99_0,v99_1,v99_2, ...... v99_98,v99_99,v99_100],] ] </pre> Data received from function solveMbyN() is an array of 100 numbers. <pre> [ s0,s1,s2, ...... s98,s99 ] </pre> The first row is tested with the solutions by; <pre> L2 = [ v0_0*s0, v0_1*s1, v0_2*s2, ..... v0_98*s98,v0_99*s99,v0_100 ] </pre> sum is the sum of all items in L2. sum is appended to L1 and the process is repeated for all 100 rows. <syntaxhighlight lang=python> L1 = [] for row in data : # a, b, c, d, e, f, g ....... # row # u, v, w, x, y, z # output L2 = [ row[p]*t1[p] for t1 in (output+(1,),) for p in range (0, len(row)) ] # L2 = [a*u , b*v , c*w , d*x , e*y , f*z , g] sum = [ sum for sum in [0] for p in L2 for sum in [sum+p] ][-1] # sum = [a*u, a*u + b*v, a*u + b*v + c*w, a*u + b*v + c*w + d*x, a*u + b*v + c*w + d*x + e*y, # a*u + b*v + c*w + d*x + e*y + f*z, a*u + b*v + c*w + d*x + e*y + f*z + g][-1] # sum = a*u + b*v + c*w + d*x + e*y + f*z + g # sum is the sum of all items in L2 L1 += [abs(sum)] L1a = sorted(L1) print (len(L1a), L1a[0], L1a[-1]) </syntaxhighlight> Ideally sum should be zero. In practice it's extremely unlikely that sum will be zero. My results typically gave values close to <pre> 100 4.1065149609E-38 9.6425614873452398368906E-25 </pre> The worst of the results above was 23 zeroes after the decimal point. Better results can be achieved by increasing precision. ===Cubic Resistive Network=== {{RoundBoxTop|theme=2}} [[File:1129network01.png|thumb|400px|''' Figure 1. Diagram of resistive network containing 12 resistors.''' </br> Blue arrows show assumed direction of current. ]] A resistive network containing 12 resistors is connected as shown in Figure 1. The network is called "cubic" because, in 3 dimensions, each resistor is located on one edge of a cube. What is resistance <math>R</math> between points <math>P_1, P_2?</math> <syntaxhighlight lang=python> # Python code: values_of_r = r1,r2,r3,r4,r5,r6,r7,r8,r9,r10,r11,r12 = 10,20,30,40,50,60,70,80,90,100,110,120 </syntaxhighlight> {{RoundBoxBottom}} ====Solve for 12 Branch Currents==== =====Create matrix 12 by 13===== <syntaxhighlight lang=python> # Python code: input = [ [10, 20, -30, -40, 0, 0, 0, 0, 0, 0, 0, 0, 0], # e1 + e2 = e3 + e4 [ 0, 0, 0, 0, 50, 60, -70, -80, 0, 0, 0, 0, 0], # e5 + e6 = e7 + e8 [ 0, 0, 0, 40, 0, 0, 0, -80, 0, 0, 110, -120, 0], # e11 + e4 = e8 + e12 [10, 0, 0, 0, -50, 0, 0, 0, 90, -100, 0, 0, 0], # e9 + e1 = e5 + e10 [ 0, 0, 0, 0, 1, -1, 0, 0, 0, -1, 0, 0, 0], # i5 = i10 + i6 [ 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, -1, 0, 0], # i7 = i11 + i8 [-1, 0, -1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0], # i9 = i1 + i3 [ 0, 0, -1, 1, 0, 0, 0, 0, 0, 0, -1, 0, 0], # i4 = i3 + i11 [-1, 1, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0], # i2 = i1 + i10 [ 0, 0, 0, 0, 0, -1, 0, -1, 0, 0, 0, 1, 0], # i12 = i6 + i8 [ 0, -1, 0, -1, 1, 0, 1, 0, 1, 0, 0, -1, 0], # i9 + i5 + i7 = i2 + i4 + i12 [ 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1.6] # i3 = 1.6 ] i1,i2,i3,i4,i5,i6,i7,i8,i9,i10,i11,i12 = values_of_i = solveMbyN (input) s1 = 'values_of_i' print(s1,eval(s1)) </syntaxhighlight> This matrix failed: <syntaxhighlight> solve2by3() : empty row in input. input = (0, 0, 0) (90533116137774317568000000000000000000000000000000000000000000, -84449318308603494400000000000000000000000000000000000000000000, 1.4228848407261846e+61) checkDirectionNumbers() : 2 rows parallel, 1 and 2. input of solve3by4() = [38760268800000000000000000000, 593753233920000000000000000000, -569385344000000000000000000000, 0] [620164300800000000000000000000000000, 9500051742720000000000000000000000000, -9110165504000000000000000000000000000, 0] [153839206400000000000000000000000, 20882470400000000000000000000000, -81126144000000000000000000000000, -3.67098806272e+32] </syntaxhighlight> =====Try again===== <syntaxhighlight lang=python> # Python code: input = [ [10, 20, -30, -40, 0, 0, 0, 0, 0, 0, 0, 0, 0], # e1 + e2 = e3 + e4 [ 0, 0, 0, 0, 50, 60, -70, -80, 0, 0, 0, 0, 0], # e5 + e6 = e7 + e8 [ 0, 0, 0, 40, 0, 0, 0, -80, 0, 0, 110, -120, 0], # e11 + e4 = e8 + e12 [10, 0, 0, 0, -50, 0, 0, 0, 90, -100, 0, 0, 0], # e9 + e1 = e5 + e10 [ 0, 0, 0, 0, 1, -1, 0, 0, 0, -1, 0, 0, 0], # i5 = i10 + i6 [ 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, -1, 0, 0], # i7 = i11 + i8 [-1, 0, -1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0], # i9 = i1 + i3 [ 0, 0, -1, 1, 0, 0, 0, 0, 0, 0, -1, 0, 0], # i4 = i3 + i11 [-1, 1, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0], # i2 = i1 + i10 [ 0, 0, 0, 0, 0, -1, 0, -1, 0, 0, 0, 1, 0], # i12 = i6 + i8 #[ 0, -1, 0, -1, 1, 0, 1, 0, 1, 0, 0, -1, 0], # i9 + i5 + i7 = i2 + i4 + i12 DELETED. [10, 20, 0, 0, 0, 0, -70, -80, 90, 0, 0, -120, 0], # e9 + e1 + e2 = e7 + e8 + e12 ADDED. [ 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1.6] # i3 = 1.6 ] import decimal dD = decimal.Decimal dgt = decimal.getcontext() Precision = dgt.prec = 30 Tolerance = dD("1e-" + str(Precision-2)) # Convert all values in input to decimal objects with precision of 30. input = [ [ dD(str(p)) for p in v ] for v in input ] i1,i2,i3,i4,i5,i6,i7,i8,i9,i10,i11,i12 = values_of_i = solveMbyN (input) </syntaxhighlight> <syntaxhighlight> # values_of_i 5.5027171492204899777282850777 9.3809275973899113038721525414 1.5999999999999999999999999999 # i3 should be 1.6. 4.8661430860000781463681475402 6.12901340210213730316883522816 2.25080295393271597702496776458 4.68526862814050716992927753670 1.41912554214042902356112999643 7.10271714922048997772828507766 3.87821044816942132614386746358 3.26614308600007814636814754027 3.66992849607314500058609776103 </syntaxhighlight> ====Compute R==== {{RoundBoxTop|theme=8}} <syntaxhighlight lang=python> # python code values_of_e = e1,e2,e3,e4,e5,e6,e7,e8,e9,e10,e11,e12 = [ (i*r) for (i,r) in zip(values_of_i, values_of_r) ] </syntaxhighlight> <syntaxhighlight> values_of_e 55.0271714922048997772828507770 187.618551947798226077443050828 47.9999999999999999999999999970 194.645723440003125854725901608 306.450670105106865158441761408 135.048177235962958621498065875 327.968803969835501895049427569 113.530043371234321884890399714 639.244543429844097995545656989 387.821044816942132614386746358 359.275739460008596100496229430 440.391419528777400070331731324 </syntaxhighlight> <math>e_3</math> should be <math>48,\ i_3*r_3</math> or <math>1.6*30.</math> <syntaxhighlight lang=python> E1 = e5 + e10 + e2 I1 = i9 + i5 + i7 R1 = E1/I1 s1 = 'R1' ; print(s1,eval(s1)) E2 = e7 + e8 - e6 + e10 - e1 + e3 + e4 I2 = i2 + i4 + i12 R2 = E2/I2 s1 = 'R2' ; print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> R1 49.2208688540148837936367036806 R2 49.2208688540148837936367036803 </syntaxhighlight> Display results with precision of 28: <syntaxhighlight lang=python> dgt.prec = 28 R1 += 0 ; R2 += 0 dgt.prec = Precision s1 = 'R1' ; print(s1,eval(s1)) s1 = 'R2' ; print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> R1 49.22086885401488379363670368 R2 49.22086885401488379363670368 </syntaxhighlight> <math>R = R_1 = R_2.</math> {{RoundBoxBottom}} ====Review==== In matrix all values <math>i_1, i_2, \dots, i_{11}, i_{12}</math> and <math>e_1, e_2, \dots, e_{11}, e_{12}</math> are included. Testing was done with the following lines substituted for last line of matrix: <syntaxhighlight lang=python> # python code [ 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, -3.15] # i7 = 3.15 [ 0, 0, 0, r4, 0, 0, 0, 0, 0, 0, 0, 0, -6 ] # e4 = 6 [ 0, 0, r3, 0, 0, 0, 0, r8, 0, 0, 0, 0, -5 ] # e3 + e8 = 5 </syntaxhighlight> All tests produced a consistent value of <math>R.</math> ====Checking==== =====Examples of current nodes===== {{RoundBoxTop|theme=2}} <gallery> File:0101network01.png|<small><math>i_1 + i_{10} = i_2</math></small> File:0101network02.png|<small><math>i_6 + i_8 = i_{12}</math></small> </gallery> {{RoundBoxBottom}} =====Examples of voltage loops===== {{RoundBoxTop|theme=2}} <gallery> File:0108network00.png|<small>Top and Bottom.<math>e_1 + e_2 - e_4 - e_3 = 0</math><math>e_5 + e_6 - e_8 - e_7 = 0</math></small> File:0108network01.png|<small>Two sides in background.<math>e_5 + e_{10} - e_1 - e_9 = 0</math><math>e_6 + e_{12} - e_2 - e_{10} = 0</math></small> File:0108network02.png|<small>Two sides in foreground.<math>e_7 + e_{11} - e_3 - e_9 = 0</math><math>e_8 + e_{12} - e_4 - e_{11} = 0</math></small> </gallery> {{RoundBoxBottom}} =====Python code===== <syntaxhighlight lang=python> t1 = ( # 3 nodes on top 'i1 + i10 - i2', 'i1 + i3 - i9', 'i3 + i11 - i4', # 3 nodes on bottom 'i10 + i6 - i5', 'i11 + i8 - i7', 'i6 + i8 - i12', # Total input current equals total output current. 'i5 + i7 + i9 - i2 - i4 - i12', # Voltage loops # top 'e1 + e2 - e4 - e3', # bottom 'e5 + e6 - e8 - e7', # 2 sides in background 'e9 + e1 - e10 - e5', 'e10 + e2 - e12 - e6', # 2 sides in foreground 'e9 + e3 - e11 - e7', 'e11 + e4 - e12 - e8', # Some elaborate loops. 'e8 - e6 + e10 + e2 - e4 - e3 - e9 + e7', 'e10 + e2 - e12 - e8 + e11 - e3 - e9 + e5', ) </syntaxhighlight> Result of each of the above calculations should be <math>0.</math> Because of small rounding errors, result may not be exactly <math>0.</math> See values_of_i and values_of_e above. This code verifies that result is close enough to <math>0</math> to be acceptable. For example: <math>\text{result} = e_{10} + e_2 - e_{12} - e_8 + e_{11} - e_3 - e_9 + e_5.</math> <math>\text{v1} = e_{10} + e_2 + e_{11} + e_5,</math> sum of positive values. <math>\text{status = (abs(result)} < \text{(v1}*\text{Tolerance)). status}</math> should be <math>\text{True.}</math> <syntaxhighlight lang=python> # python code import re for str1 in t1 : str2 = re.sub ('\+', ';+', str1) str2 = re.sub ('\-', ';-', str2) L1 = str2.split(';') positives = ''.join([ v for v in L1 if '-' not in v ]) result = eval(str1) v1 = eval( positives ) status = (abs(result) < (v1*Tolerance)) str3 = (str1+(' '*40))[:42] str4 = ((' '*10) + str(result))[-10:] str5 = '{}{} {}'.format(str3,str4,status) print ( str5 ) </syntaxhighlight> {| class="wikitable" |- ! Calculation || Result !! Result Acceptable |- | <math> i_1 + i_{10} - i_2 </math> | <math> -1.2E-28 </math> | <math>\text{True}</math> |- | <math> i_1 + i_3 - i_9 </math> | <math> -6E-29 </math> | <math>\text{True}</math> |- | <math> i_3 + i_{11} - i_4 </math> | <math> -3E-29 </math> | <math>\text{True}</math> |- | <math> i_{10} + i_6 - i_5 </math> | <math> 0E-29 </math> | <math>\text{True}</math> |- | <math> i_{11} + i_8 - i_7 </math> | <math> 0E-29 </math> | <math>\text{True}</math> |- | <math> i_6 + i_8 - i_{12} </math> | <math> -2E-29 </math> | <math>\text{True}</math> |- | <math> i_5 + i_7 + i_9 - i_2 - i_4 - i_{12} </math> | <math> -3E-29 </math> | <math>\text{True}</math> |- | <math> e_1 + e_2 - e_4 - e_3 </math> | <math> 0E-28 </math> | <math>\text{True}</math> |- | <math> e_5 + e_6 - e_8 - e_7 </math> | <math> 0E-27 </math> | <math>\text{True}</math> |- | <math> e_9 + e_1 - e_{10} - e_5 </math> | <math> 0E-27 </math> | <math>\text{True}</math> |- | <math> e_{10} + e_2 - e_{12} - e_6 </math> | <math> -1.3E-26 </math> | <math>\text{True}</math> |- | <math> e_9 + e_3 - e_{11} - e_7 </math> | <math> -1.3E-26 </math> | <math>\text{True}</math> |- | <math> e_{11} + e_4 - e_{12} - e_8 </math> | <math> 0E-27 </math> | <math>\text{True}</math> |- | <math> e_8 - e_6 + e_{10} + e_2 - e_4 - e_3 - e_9 + e_7 </math> | <math> 0E-27 </math> | <math>\text{True}</math> |- | <math> e_{10} + e_2 - e_{12} - e_8 + e_{11} - e_3 - e_9 + e_5 </math> | <math> 0E-27 </math> | <math>\text{True}</math> |} ===Big Matrix 64 by 65=== {{RoundBoxTop|theme=2}} [[File:0706matrix64_01.png|thumb|400px|'''Diagram of resistive network containing 64 resistors.''' </br> Positive current flow is assumed to be from bottom to top or from left to right. ]] A network containing 64 resistors is connected as shown in diagram. What is resistance R between points P1, P2? <syntaxhighlight lang=python> # python code values_of_R = ( R10, R11, R12, R13, R14, R15, R16, R17, R18, R19, R20, R21, R22, R23, R24, R25, R26, R27, R28, R29, R30, R31, R32, R33, R34, R35, R36, R37, R38, R39, R40, R41, R42, R43, R44, R45, R46, R47, R48, R49, R50, R51, R52, R53, R54, R55, R56, R57, R58, R59, R60, R61, R62, R63, R64, R65, R66, R67, R68, R69, R70, R71, R72, R73, ) = [ v for v in range (100,731,10) ] </syntaxhighlight> While this resistive circuit may be very theoretical, it lends itself well to the creation of a big matrix, 64 by 65, meaning that there are 64 resistors and 64 simultaneous equations to be solved. {{RoundBoxBottom}} ====Create matrix==== An examination of the circuit produces the following conditions: <syntaxhighlight lang=python> # python code iconditions = [ "+ i10 + i70 - i44" , "+ i11 - i10 - i49" , "+ i12 - i11 - i54", "+ i13 - i12 - i59" , "+ i14 - i13 - i64" , "+ i15 + i44 - i43", "+ i16 + i49 - i15 - i48 - i70" , "+ i17 + i54 - i16 - i53" , "+ i18 + i59 - i17 - i58", "+ i19 + i64 + i71 - i18 - i63" , "+ i69 - i19 - i68" , "+ i20 + i43 - i42", "+ i21 + i48 - i20 - i47" , "+ i22 + i53 - i21 - i52" , "+ i23 + i58 - i22 - i57", "+ i24 + i63 - i23 - i62" , "+ i68 - i24 - i67" , "+ i25 + i42 - i41", "+ i26 + i47 - i25 - i46" , "+ i27 + i52 - i26 - i51" , "+ i28 + i57 - i27 - i56", "+ i29 + i62 - i28 - i61" , "+ i67 - i29 - i66" , "+ i30 + i41 - i40", "+ i31 + i46 - i30 - i45 - i72" , "+ i32 + i51 - i31 - i50" , "+ i33 + i56 - i32 - i55", "+ i34 + i61 + i73 - i33 - i60" , "+ i66 - i34 - i65" , "+ i36 + i45 - i35", "+ i37 + i50 - i36" , "+ i38 + i55 - i37" , "+ i39 + i60 - i38", "+ i65 - i39 - i73" ] sx = 'len(iconditions)' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> len(iconditions) = 34 </syntaxhighlight> <syntaxhighlight lang=python> econditions = [ "+ e40 + e30 - e35 - e45" , "+ e41 + e25 - e30 - e46" , "+ e42 + e20 - e25 - e47", "+ e43 + e15 - e20 - e48" , "+ e44 + e10 - e15 - e49" , "+ e45 + e31 - e36 - e50", "+ e46 + e26 - e31 - e51" , "+ e47 + e21 - e26 - e52" , "+ e48 + e16 - e21 - e53", "+ e49 + e11 - e16 - e54" , "+ e50 + e32 - e37 - e55" , "+ e51 + e27 - e32 - e56", "+ e52 + e22 - e27 - e57" , "+ e53 + e17 - e22 - e58" , "+ e54 + e12 - e17 - e59", "+ e55 + e33 - e38 - e60" , "+ e56 + e28 - e33 - e61" , "+ e57 + e23 - e28 - e62", "+ e58 + e18 - e23 - e63" , "+ e59 + e13 - e18 - e64" , "+ e60 + e34 - e39 - e65", "+ e61 + e29 - e34 - e66" , "+ e62 + e24 - e29 - e67" , "+ e63 + e19 - e24 - e68", "+ e64 + e14 - e19 - e69" , "+ e44 + e70 - e15" , "+ e64 + e14 - e71", "+ e40 + e30 - e72" , "+ e60 + e73 - e39" ] sx = 'len(econditions)' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> len(econditions) = 29 </syntaxhighlight> In iconditions and econditions there are 63 conditions that include all values of i and e. These 63 conditions are used to create matrix. The 64th condition is added manually. The matrix is: <syntaxhighlight lang=python> matrix = [ [1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,], [-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,], [0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,], [0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,1,0,0,0,], [0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,], [0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], 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[0,0,0,0,140,0,0,0,0,-190,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,640,0,0,0,0,-690,0,0,0,0,0,], [0,0,0,0,0,-150,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,440,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,700,0,0,0,0,], [0,0,0,0,140,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,640,0,0,0,0,0,0,-710,0,0,0,], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,300,0,0,0,0,0,0,0,0,0,400,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-720,0,0,], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-390,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,600,0,0,0,0,0,0,0,0,0,0,0,0,730,0,], [1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,], ] sx = 'len(matrix)' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> len(matrix) = 64 </syntaxhighlight> Bottom line of matrix is equivalent to: <math>(1)i10 + (-1) = 0</math> or <math>i10 = 1.</math> ====First result==== Calculate values_of_i : <syntaxhighlight lang=python> print ('\nWhen ints become huge:') values_of_i = solveMbyN (matrix) sx = 'values_of_i' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> When ints become huge: solveMbyN (input_, level = -41) : <class 'OverflowError'> OverflowError('int too large to convert to float') Length of input = 23 input_[0] = Error in this row. input_[1] = Error in this row. input_[2] = Error in this row. input_[3] = [-7.048390979785929e+176, 1.1003906499643917e+176, 1.5070856217200028e+174, 1.955699032422673e+173, ...... 0.0] input_[4] = [510.0, 0.0, 0.0, 0.0, 320.0, -1150.0, 270.0, 0.0, 0.0, 320.0, -590.0, 270.0, 0.0, 0.0, 320.0, -590.0, ...... 0.0] input_[5] = [0.0, 520.0, 0.0, 0.0, 0.0, 270.0, -1060.0, 220.0, 0.0, 0.0, 270.0, -490.0, 220.0, 0.0, 0.0, 270.0, ...... 0.0] input_[6] = [0.0, 0.0, 530.0, 0.0, 0.0, 0.0, 220.0, -970.0, 170.0, 0.0, 0.0, 220.0, -390.0, 170.0, 0.0, 0.0, 220.0, ...... 0.0] input_[7] = Error in this row. values_of_i = None </syntaxhighlight> <syntaxhighlight lang=python> print ('\nConvert input to floats:') matrix1 = [ list(v) for v in matrix ] matrix1[0][0] = float(matrix1[0][0]) values_of_i = solveMbyN (matrix1) sx = 'values_of_i' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> Convert input to floats: solveMbyN (input_, level = -40) : <class 'KeyError'> KeyError('Internal error. input[1][0] = nan, should be 0.') Length of input = 24 input_[0] = [-1.7360455505275518e+174, 1.4096781959571856e+174, -2.2007812999287836e+173, -3.014171243439967e+171, ...... 0.0] input_[1] = [-3.7974175914221006e+162, 3.309163202261842e+161, 2.4114748810711523e+162, -4.426635506031073e+161, ...... 0.0] input_[2] = [-2.4975968400753463e+139, 5.704494025143264e+138, -2.7146889822895123e+138, 1.4057733058789272e+139, ...... 0.0] input_[3] = [7.667237322891148e+182, -1.7692205437935546e+182, -2.341735229706114e+180, 4.1615580570562045e+181, ...... -0.0] input_[4] = [-500.0, 0.0, 0.0, 0.0, 0.0, 1240.0, -320.0, 0.0, 0.0, 0.0, 690.0, -320.0, 0.0, 0.0, 0.0, 690.0, -320.0, ...... 0.0] input_[5] = [0.0, 510.0, 0.0, 0.0, 0.0, 320.0, -1150.0, 270.0, 0.0, 0.0, 320.0, -590.0, 270.0, 0.0, 0.0, 320.0, -590.0, ...... 0.0] input_[6] = [0.0, 0.0, 520.0, 0.0, 0.0, 0.0, 270.0, -1060.0, 220.0, 0.0, 0.0, 270.0, -490.0, 220.0, 0.0, 0.0, 270.0, ...... 0.0] input_[7] = [0.0, 0.0, 0.0, 530.0, 0.0, 0.0, 0.0, 220.0, -970.0, 170.0, 0.0, 0.0, 220.0, -390.0, 170.0, 0.0, 0.0, ...... 0.0] values_of_i = None </syntaxhighlight> =====Success===== <syntaxhighlight lang=python> print ('\nSet global variable enable_reduceRow:') enable_reduceRow = 1 values_of_i = solveMbyN (matrix1) </syntaxhighlight> Success: <syntaxhighlight> Set global variable enable_reduceRow: i10 = 1.0000000000000049 ; i11 = 1.643236374952256 ; i12 = 2.316468657232291 ; i13 = 3.0507456069545116 i14 = 3.908085797412319 ; i15 = 0.5970301043016677 ; i16 = 0.8274774533758196; i17 = 1.225283946841065 i18 = 1.5617922630400025 ; i19 = 0.369273540611037 ; i20 = 0.3858385105885722; i21 = 0.6270001063825295 i22 = 0.7040607630623028 ; i23 = 0.6129764173251202 ; i24 = 0.298576896960036 ; i25 = 0.44960726241462035 i26 = 0.7812212615819403 ; i27 = 0.7165761045550649 ; i28 = 0.5186812635664733; i29 = 0.266770119423805 i30 = 0.5896680016803755 ; i31 = 1.475274068751303 ; i32 = 0.9632057010422588; i33 = 0.5801910619990465 i34 = 0.30799558703953794; i35 = 2.4693659910366916 ; i36 = 1.583773707944257 ; i37 = 1.0123878002551232 i38 = 0.6135963601029517 ; i39 = 0.3175434839291887 ; i40 = 2.7147355593758107; i41 = 2.125067557695435 i42 = 1.6754602952808149 ; i43 = 1.2896217846922426 ; i44 = 0.692591680390575 ; i45 = 0.8855922830924343 i46 = 1.7538676385971101 ; i47 = 1.4222536394297902 ; i48 = 1.181092043635833 ; i49 = 0.6432363749522512 i50 = 0.5713859076891339 ; i51 = 1.0834542753981782 ; i52 = 1.1480994324250535; i53 = 1.0710387757452802 i54 = 0.6732322822800348 ; i55 = 0.39879144015217155; i56 = 0.7818060791953839; i57 = 0.9797009201839757 i58 = 1.0707852659211583 ; i59 = 0.7342769497222208 ; i60 = 0.2960528761737631; i61 = 0.6419329634235106 i62 = 0.8938441075661789 ; i63 = 1.2082436279312632 ; i64 = 0.8573401904578074; i65 = 0.2438588716389498 i66 = 0.5518544586784879 ; i67 = 0.8186245781022927 ; i68 = 1.1172014750623287; i69 = 1.4864750156733657 i70 = -0.3074083196094299; i71 = 1.5434221599024214 ; i72 = 1.7538814225756034; i73 = -0.07368461229023889 # Notice that i70, i73 are negative. </syntaxhighlight> =====Check all conditions===== The following conditions are included for testing: <syntaxhighlight lang=python> more_econditions = [ "+ e49 + e70 - e10", "+ e19 + e69 - e71", "+ e35 + e45 - e72", "+ e65 + e73 - e34", ] extra_test_conditions = [ "+ e40 + e41 + e42 + e43 + e44 + e10 - e35 - e45 - e46 - e47 - e48 - e49", "+ e45 + e46 + e47 + e48 + e49 + e11 - e36 - e50 - e51 - e52 - e53 - e54", "+ e50 + e51 + e52 + e53 + e54 + e12 - e37 - e55 - e56 - e57 - e58 - e59", "+ e55 + e56 + e57 + e58 + e59 + e13 - e38 - e60 - e61 - e62 - e63 - e64", "+ e60 + e61 + e62 + e63 + e64 + e14 - e39 - e65 - e66 - e67 - e68 - e69", "+ e44 + e10 + e11 + e12 + e13 + e14 - e69 - e15 - e16 - e17 - e18 - e19", "+ e43 + e15 + e16 + e17 + e18 + e19 - e68 - e20 - e21 - e22 - e23 - e24", "+ e42 + e20 + e21 + e22 + e23 + e24 - e67 - e25 - e26 - e27 - e28 - e29", "+ e41 + e25 + e26 + e27 + e28 + e29 - e66 - e30 - e31 - e32 - e33 - e34", "+ e40 + e30 + e31 + e32 + e33 + e34 - e65 - e35 - e36 - e37 - e38 - e39", "+ i35 + i40 + i72 - i14 - i69 - i71", """+ e40 + e41 + e42 + e43 + e44 + e10 + e11 + e12 + e13 + e14 = e35 + e36 + e37 + e38 + e39 + e65 + e66 + e67 + e68 + e69""", """+ e40 + e41 + e42 + e43 + e15 + e16 + e17 + e18 + e19 + e69 = e35 + e36 + e37 + e38 + e60 + e61 + e62 + e63 + e64 + e14""", """+ e40 + e41 + e42 + e20 + e21 + e22 + e23 + e24 + e68 + e69 = e35 + e36 + e37 + e55 + e56 + e57 + e58 + e59 + e13 + e14""", """+ e40 + e41 + e25 + e26 + e27 + e28 + e29 + e67 + e68 + e69 = e35 + e36 + e50 + e51 + e52 + e53 + e54 + e12 + e13 + e14""", """+ e40 + e30 + e31 + e32 + e33 + e34 + e66 + e67 + e68 + e69 = e35 + e45 + e46 + e47 + e48 + e49 + e11 + e12 + e13 + e14""" ] </syntaxhighlight> Two Auxiliary Functions: <syntaxhighlight lang=python> def sum_zero (values, tolerance = None) : ''' This function calculates sum of all values in input. If sum is very close to zero, sum is returned as zero. For example: sum_zero((2, -1.99999999999999999999999)) is returned as 0. ''' if tolerance == None : tolerance = Tolerance sump = sumn = 0 for v in values : if v > 0 : sump += v elif v < 0 : sumn -= v max = (sumn, sump)[sump > sumn] sum = sump - sumn if abs(sum) < tolerance: return type(sum)(0) if abs(sum) < tolerance*max : return type(sum)(0) return sum def convert_str_to_tuple (input_str) : ''' input is str like "+ i35 + i40 + i72 - i14 - i69 - i71" or "+ i35 + i40 + i72 == i14 + i69 + i71" This function returns tuple : (i35, i40, i72, - i14, - i69, - i71) ''' str0 = ' '.join(input_str.split()) if '=' in str0 : if '==' in str0 : splitter = '==' else : splitter = '=' str1,str2 = str0.split(splitter) t1 = convert_str_to_tuple (str1) t2 = convert_str_to_tuple (str2) return t1 + tuple(-v for v in t2) str1 = ';+'.join(str0.split('+')) str2 = ';-'.join(str1.split('-')) str3 = ','.join([ v for v in str2.split(';') if v.strip() ]) return eval(str3 + ',') </syntaxhighlight> Check 83 conditions: <syntaxhighlight lang=python> all_conditions = (iconditions + econditions + more_econditions + extra_test_conditions) # Following string is executable python code. exc_str_64ei = """ ( i10, i11, i12, i13, i14, i15, i16, i17, i18, i19, i20, i21, i22, i23, i24, i25, i26, i27, i28, i29, i30, i31, i32, i33, i34, i35, i36, i37, i38, i39, i40, i41, i42, i43, i44, i45, i46, i47, i48, i49, i50, i51, i52, i53, i54, i55, i56, i57, i58, i59, i60, i61, i62, i63, i64, i65, i66, i67, i68, i69, i70, i71, i72, i73, ) = values_of_i values_of_e = [ i*R for i,R in zip ( values_of_i, values_of_R ) ] ( e10, e11, e12, e13, e14, e15, e16, e17, e18, e19, e20, e21, e22, e23, e24, e25, e26, e27, e28, e29, e30, e31, e32, e33, e34, e35, e36, e37, e38, e39, e40, e41, e42, e43, e44, e45, e46, e47, e48, e49, e50, e51, e52, e53, e54, e55, e56, e57, e58, e59, e60, e61, e62, e63, e64, e65, e66, e67, e68, e69, e70, e71, e72, e73, ) = values_of_e """ exec(exc_str_64ei) tolerance = 1e-15 count = errors = 0 for condition in all_conditions : t1 = convert_str_to_tuple (condition) sum = sum_zero(t1, tolerance) count += 1 if sum : sx = 'sum, condition' ; print (sx, '=', eval(sx)) errors += 1 print ('Number of tests =', count) print ('Number of errors =', errors) </syntaxhighlight> With tolerance of <math>1e-15</math> there are 21 errors: <syntaxhighlight> sum, condition = (1.2505552149377763e-12, '+ e48 + e16 - e21 - e53') sum, condition = (1.2505552149377763e-12, '+ e49 + e11 - e16 - e54') sum, condition = (7.958078640513122e-13, '+ e52 + e22 - e27 - e57') sum, condition = (1.1368683772161603e-12, '+ e53 + e17 - e22 - e58') sum, condition = (2.2737367544323206e-12, '+ e54 + e12 - e17 - e59') ...... ...... Number of tests = 83 Number of errors = 21 </syntaxhighlight> With tolerance of <math>1e-14</math> there are no errors. ====Matrix corrected==== {{RoundBoxTop|theme=2}} [[File:0710matrix64_01.png|thumb|400px|'''Diagram of network containing 64 resistors''' </br> Diagram has been corrected to show positive direction of current through R70, R73. ]] Original assumptions were that currrent flow through 64 resistors would be from bottom to top or from left to right. Examination of results shows that flow through R70, R73 is from right to left. This is reflected in testing below. Corrected diagram conforms to assumption that all current flow is from bottom towards top or from left to right. {{RoundBoxBottom}} <syntaxhighlight lang=python> number_of_columns = 65 output = [] # # Test this matrix 64 times using # i10 = 1 # i11 = 1.1 # i12 = 1.2 # ....... # ....... # i70 = -7 # i71 = 7.1 # i72 = 7.2 # i73 = -7.3 # for I in range(10, 74): new_line = [ dD(0) ] * number_of_columns place_in_line = I - 10 new_line[place_in_line] = dD(1) i = dD(I)/10 if I in (70,73) : new_line[-1] = i else : new_line[-1] = -i matrix[-1] = new_line r = produce_result (matrix,1) if r : output += [ r ] sx = 'len(output)' ; print (sx, '=', eval(sx)) # Produce results with slightly reduced precision: dgt.prec -= 4 set2 = { r+0 for r in output } dgt.prec += 4 len2 = len(set2) if len2 == 1 : r, = set2 print ('R =', r) else : print (len2, 'values of R:') for v in set2 : print (' ', v) </syntaxhighlight> <syntaxhighlight> len(output) = 64 R = 723.92857598844254769973256333526566351583807510293750368 </syntaxhighlight> <math>\text{R}</math> is printed with precision of 56. With precision of 56 all 64 results are equal. [[Category:Equations]] thbv3luneyfs5b61wkgzfl227yrt5uy 2835285 2835284 2026-10-01T08:19:24Z ThaniosAkro 2805358 /* Matrix corrected */ 2835285 wikitext text/x-wiki ==Introduction== The word "simultaneous" implies that two or more equations exist in the same context at the same time. For example: <math>3x + 2y - 13 = 0\ \dots\ (1)</math> <math>2x - y - 4 = 0 \ \dots\ (2)</math> Equations <math>(1)</math> and <math>(2)</math> are 2 simultaneous equations. When we see two simultaneous equations, it's natural to ask the question: What are the values of <math>x</math> and <math>y</math> that satisfy both equations <math>(1)</math> and <math>(2)</math>? To calculate <math>(x,y)</math> common to both <math>(1)</math> and <math>(2)</math>: <math>(2)*2\ \dots\ 4x - 2y - 8 = 0 \ \dots\ (3)</math> <math>(3)+(1)\ \dots\ 7x - 21 = 0;\ x = 3.</math> Substitute <math>3</math> for <math>x</math> in <math>(2):\ 2(3) - y - 4 = 0;\ y = 2.</math> The values <math>(x,y)=(3,2)</math> satisfy both equations <math>(1)</math> and <math>(2).</math> In cartesian coordinate geometry of 2 dimensions, point <math>(3,2)</math> is the point of intersection of two lines <math>(1)</math> and <math>(2).</math> See Figure 1 below. If the 2 lines are parallel, there is no point of intersection. See Figure 2 below. The trivial solution <math>(0, 0)</math> is a valid solution. See Figure 3 below. {{RoundBoxTop|theme=2}} <gallery> File:0726_2lines.png|<small>Figure 1. 2 lines that intersect at point (3,2).</small> File:0726_2parallelLines.png|<small>Figure 2. When 2 lines are parallel, there is no point of intersection.</small> File:0729_2lines.png|<small>Figure 3. The trivial solution x=y=0 is a valid solution.</small> </gallery> {{RoundBoxBottom}} The information contained in equations <math>(1)</math> and <math>(2)</math> may constitute a matrix: <pre> [ [3, 2, -13], [2, -1, -4] ] </pre> In fact, in the python programming language, the following statement is valid code: <syntaxhighlight lang=python> data = [ [3, 2, -13], [2, -1, -4] ] </syntaxhighlight> For there to be a point of intersection, <code>data</code> must be valid. Here are examples of invalid data: <syntaxhighlight lang=python> data = [ [3, 2, -13], # Both lines are parallel. [6, 4, -5] # See Figure 2 above. ] </syntaxhighlight> <syntaxhighlight lang=python> data = [ [3, 2, -13], [0, 0, -4] # Empty row, representing equation 0x + 0y - 4 = 0. ] </syntaxhighlight> <syntaxhighlight lang=python> data = [ [3, 0, -13], # Empty column representing 2 parallel lines: [2, 0, -4] # 3x = 13 and 2x = 4. ] </syntaxhighlight> The matrix above with name "data" is described as matrix "2 by 3," meaning that it contains 2 rows with 3 columns or 3 members per row. ==Solving 2 by 3== ===Implementation=== Below is python code containing function <code>solve2by3 (input).</code> The function accepts as input a matrix like <code>data</code> above. After the code are examples of invocation with both good data and bad data. <syntaxhighlight lang=python> import sys import decimal dD = decimal.Decimal def solve2by3 (input_, level=0) : ''' input represents system: a1*x + b1*y + c1 = 0 a2*x + b2*y + c2 = 0 input = ( (a1,b1,c1), (a2,b2,c2), ) To invoke: x,y = solve2by3 (input) Function solve2by3 () may return None. input is not changed by this function. ''' if level : thisName = 'solve2by3 (input_, level = {}) :'.format(level) else : thisName = 'solve2by3 (input_) :' try : error = 0 try : input = [ list(v) for v in input_ ] (a1,b1,c1), (a2,b2,c2) = input except : input = 0 input or {}['input_ not recognized.'] # six_values = a1,b1,c1, a2,b2,c2 for v in six_values : isinstance(v, (int, float, dD)) or {}['Non-numeric value in input.'] set1 = { isinstance(v, dD) for v in six_values } if len(set1) == 2 : # Mix of Decimal and non-Decimal in input. Make all type Decimal. (a1,b1,c1, a2,b2,c2) = [ dD(str(v)) for v in six_values ] # a1 or b1 or {}['Row 1 empty.'] ; a1 or a2 or {}['Column 1 empty.'] a2 or b2 or {}['Row 2 empty.'] ; b1 or b2 or {}['Column 2 empty.'] # if not a1 : # Make a1 non-zero. (a1,b1,c1),(a2,b2,c2) = (a2,b2,c2), (a1,b1,c1) # if a2 : # Make a2 zero. if a2 == a1 : a2,b2,c2 = a1-a2, b1-b2, c1-c2 elif a2 == -a1 : a2,b2,c2 = a1+a2, b1+b2, c1+c2 else : list1 = [ a2*v for v in (a1,b1,c1) ] list2 = [ a1*v for v in (a2,b2,c2) ] a2,b2,c2 = [ (v1-v2) for v1,v2 in zip (list1, list2) ] a2 and {}['Internal error. a2 should be 0.'] b2 or {}['Parallel input.'] # The matrix is: # a1, b1, c1 with a1 non-zero # 0, b2, c2 and b2 non-zero. # 0 x + b2 y + c2 = 0 y = -c2/b2 # a1 x + b1 y + c1 = 0 x = -(b1*y + c1)/a1 # Here is why a1 must be non-zero. output = x,y except : error = str(sys.exc_info())[1:].split(',') ; error[1:] = [ ','.join(error[1:-1]) ] # if error : print (thisName) for v in error : print (' ', v.strip()) if input : print (' input of solve2by3() =') print (' ', input[0]) print (' ', input[1]) return None # return output </syntaxhighlight> ====Examples==== Invocation with good data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve2by3([ [3, 2, -13], [2, -1, -4] ]) print (output) </syntaxhighlight> <pre> (3.0, 2.0) </pre> {{RoundBoxBottom}} Invocation with bad or invalid data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve2by3([ [3, 2, -13], # Both lines are parallel. [6, 4, -5] # See Figure 2 above. ]) print (output) </syntaxhighlight> <pre> solve2by3 (input_) : <class 'KeyError'> KeyError('Parallel input.') input of solve2by3() = [3, 2, -13] [6, 4, -5] None </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve2by3([ [3, 2, -13, 7], # Input matrix not exactly 2 by 3. [6, 4, -5] ]) print (output) </syntaxhighlight> <pre> solve2by3 (input_) : <class 'KeyError'> KeyError('input_ not recognized.') None </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve2by3([ [3, 0, 2], [6, 0, 4] ]) print (output) </syntaxhighlight> <pre> solve2by3 (input_) : <class 'KeyError'> KeyError('Column 2 empty.') input of solve2by3() = [3, 0, 2] [6, 0, 4] None </pre> {{RoundBoxBottom}} ===Reversing the process=== ====Linear Function==== [[File:1212line01.png|thumb|400px|''' Figure 1. Diagram of line defined by 2 points.''' </br> 2 points are: <math>(-5,4), (3,1).</math> </br> Equation of line is: <math>3x + 8y - 17 = 0.</math> ]] Examples above calculate the point of intersection of 2 lines. An example of reversing the process is this task: Given two points <math>(x_1, y_1), (x_2, y_2)</math> calculate equation of line containing these 2 points. Equation of line is of format <math>Ax + By + C = 0,</math> For example: <math>3x + 2y + 10 = 0\ \dots\ (1).</math> Equation <math>(1)</math> can be expressed as <math>6x + 4y + 20 = 0</math> or <math>-9x - 6y - 30 = 0.</math> Also, there appear to be 3 unknowns, but only two sets of values are required to define the line. Assume <math>C = 1</math> and the 2 relevant equations are: <math>Ax_1 + By_1 + 1 = 0</math> <math>Ax_2 + By_2 + 1 = 0</math> To solve for <math>A, B:</math> <math>x_1A + y_1B + 1 = 0</math> <math>x_2A + y_2B + 1 = 0</math> Suppose the line is defined by points <math>(3,1), (-5,4):</math> <syntaxhighlight lang=python> # python code: input = [ [3,1,1], [-5,4,1], ] result = solve2by3 (input) print (result) </syntaxhighlight> <syntaxhighlight> (-0.17647058823529413, -0.47058823529411764) </syntaxhighlight> Desired equation is: <math>-0.17647058823529413\cdot x -0.47058823529411764\cdot y + 1 = 0\ \dots\ (2).</math> To improve appearance of <math>(2):</math> <syntaxhighlight lang=python> # python code: print (A/B) </syntaxhighlight> <syntaxhighlight> 0.37500000000000006 </syntaxhighlight> Let <math>A, B = 3, 8</math> and check: <syntaxhighlight lang=python> # python code A,B = 3,8 p1 = x1,y1 = 3,1 p2 = x2,y2 = -5,4 for v in (p1,p2) : x,y = v C = -(A*x + B*y) s1 = 'C' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> C -17 C -17 </syntaxhighlight> Desired equation <math>(2)</math> becomes <math>3x + 8y - 17 = 0\ \dots\ (3).</math> ====Wrong assumptions==== [[File:1212line02.png|thumb|400px|''' Figure 2. Diagram of line defined by 2 points and passing through origin.''' </br> 2 points are: <math>(3,2), (6,4).</math> </br> Equation of line is: <math>2x - 3y = 0.</math> </br> Non-zero value for coefficient <math>C</math> is impossible. ]] Sometimes you create a matrix that seems correct, but it fails to produce a result. Here is such an example: What is equation of line defined by points <math>(3, 2), (6, 4)?</math> As above assume that <math>C = 1.</math> <syntaxhighlight lang=python> # python code: p1 = x1,y1 = 3,2 p2 = x2,y2 = 6,4 input = [ [x1,y1,1], [x2,y2,1], ] result = solve2by3 (input) print (result) </syntaxhighlight> This assumption failed: <syntaxhighlight> solve2by3() : parallel input. input = [3, 2, 1] [6, 4, 1] None </syntaxhighlight> Assume that <math>A = 1.</math> <syntaxhighlight lang=python> # python code: # 1(x1) + B(y1) + 1(C) = 0 # 1(x2) + B(y2) + 1(c) = 0 # y1(B) + 1(C) + x1 = 0 # y2(B) + 1(C) + x2 = 0 input = [ [y1,1,x1], # Notice that input has been [y2,1,x2], # rotated left by one column. ] result = solve2by3 (input) print (result) </syntaxhighlight> <syntaxhighlight> (-1.5, 0.0) </syntaxhighlight> Equation of line is: <math>1\cdot x + (-1.5)\cdot y + 0 = 0</math> or <math>2x - 3y = 0</math> This line includes the origin. Therefore constant <math>C</math> cannot be non-zero. Generally: * Without rotation, <math>A, B = \text{result}</math> and <math>C = 1.</math> * With rotation left by one column, <math>B, C = \text{result}</math> and <math>A = 1.</math> In this case: <syntaxhighlight lang=python> # python code: >>> B,C = result ; A = 1 >>> A,B,C >>> 1,-1.5,0 </syntaxhighlight> For example of big matrix that failed the first time, but was successful the second time, see [https://en.wikiversity.org/wiki/Solving_simultaneous_equations#Cubic_Resistive_Network cubic resistive network] below. ==Solving 3 by 4== Below is python code containing function <code>solve3by4 (input).</code> The function accepts as input a 3 by 4 matrix like that described in the code comments. In 3d coordinate geometry the equations <code>(1), (2), (3)</code> are the equations of 3 planes and the solution of the system is the point of intersection of the 3 planes. Given 3 random planes, there are 2 conditions that do not produce a unique point of intersection: * If 2 of the planes are parallel. See Figure 1 below. * If the 3 planes form a "tent" or "delta." See Figure 2, 3 or 4 below. A special case of this condition occurs when size of "tent" is zero, in which case all three planes intersect on a common line and there is an infinite number of solutions. See Figure 5 below. The trivial solution <math>(0, 0, 0)</math> is valid. See Figure 6 below. <code></code> <code></code> {{RoundBoxTop|theme=2}} <gallery> File:0726_2parallelPlanes.png|<small>Figure 1. When 2 planes are parallel, there is no point of intersection.</small> File:0730triangularTube.png|<small>Figure 2. Triangular tube, 3 planes that never intersect.</small> File:0726_3planes0.png|<small>Figure 3. 3 planes that form a "tent," view 1. There is no point of intersection.</small> File:0726_3planes1.png|<small>Figure 4. 3 planes that form a "tent," view 2. There is no point of intersection.</small> File:1109_3planes1.png|<small>Figure 5. 3 planes that intersect on a common line. Points <math>(6,6,1),</math> <math>(7,7,4),</math> <math>(8,8,7)</math> are on this line and are common to all 3 planes.</small> File:0729_3planes.png|<small>Figure 6. 3 planes that intersect at origin (0, 0, 0).</small> </gallery> {{RoundBoxBottom}} ===Auxiliary functions=== <syntaxhighlight lang=python> def two_planes_parallel (plane1, plane2) : ''' status = two_planes_parallel (plane1, plane2) status = True if parallel. ''' A1,B1,C1 = plane1[:3] A2,B2,C2 = plane2[:3] A3 = B1*C2 - B2*C1 B3 = C1*A2 - C2*A1 C3 = A1*B2 - A2*B1 return ({ A3,B3,C3 } == {0}) def check_three_rows (input) : ''' result = check_three_rows (input) result is None or string. ''' row0,row1,row2 = input if two_planes_parallel (row0,row1) : return 'Two rows parallel: 0,1' if two_planes_parallel (row0,row2) : return 'Two rows parallel: 0,2' if two_planes_parallel (row1,row2) : return 'Two rows parallel: 1,2' A0,B0,C0 = row0[:3] ; A1,B1,C1 = row1[:3] ; A2,B2,C2 = row2[:3] # Line at intersection of planes 1,2 has direction numbers: A3 = B1*C2 - B2*C1 ; B3 = C1*A2 - C2*A1 ; C3 = A1*B2 - A2*B1 # Line at intersection of planes 0,2 has direction numbers: A4 = B0*C2 - B2*C0 ; B4 = C0*A2 - C2*A0 ; C4 = A0*B2 - A2*B0 # Are 2 lines of intersection parallel? if two_planes_parallel ((A3,B3,C3), (A4,B4,C4)) : return 'Three rows form tent.' return None </syntaxhighlight> ===Implementation=== <syntaxhighlight lang=python> def solve3by4 (input_, level=0) : ''' input_ is : [ [a0,b0,c0,d0], [a1,b1,c1,d1], [a2,b2,c2,d2] ] representing system: a0*x + b0*y + c0*z + d0 = 0 a1*x + b1*y + c1*z + d1 = 0 a2*x + b2*y + c2*z + d2 = 0 x,y,z = solve3by4 (input) Function solve3by4 () may return None. input is not changed by this function. ''' if level : thisName = 'solve3by4 (input_, level = {}) :'.format(level) else : thisName = 'solve3by4 (input_) :' try : error = 0 try : input = [ list(v) for v in input_ ] (a0,b0,c0,d0), (a1,b1,c1,d1), (a2,b2,c2,d2) = input except : input = 0 input or {}['input_ not recognized.'] # twelve_values = a0,b0,c0,d0, a1,b1,c1,d1, a2,b2,c2,d2 for v in twelve_values : isinstance(v, (int, float, dD)) or {}['Non-numeric value in input.'] set1 = { isinstance(v, dD) for v in twelve_values } if len(set1) == 2 : # Mix of Decimal and non-Decimal in input. Make all type Decimal. (a0,b0,c0,d0, a1,b1,c1,d1, a2,b2,c2,d2) = [ dD(str(v)) for v in twelve_values ] # a0 or b0 or c0 or {}['Row 0 empty.'] ; a0 or a1 or a2 or {}['Column 0 empty.'] a1 or b1 or c1 or {}['Row 1 empty.'] ; b0 or b1 or b2 or {}['Column 1 empty.'] a2 or b2 or c2 or {}['Row 2 empty.'] ; c0 or c1 or c2 or {}['Column 2 empty.'] # input = [ [a0,b0,c0,d0], [a1,b1,c1,d1], [a2,b2,c2,d2] ] result = check_three_rows (input) ; result and {}[result] # if not a0 : # Make a0 non-zero. if a1 : input[0],input[1] = input[1],input[0] else : input[0],input[2] = input[2],input[0] # # The matrix is: # a0, b0, c0, d0 with a0 non-zero. # a1, b1, c1, d1 # a2, b2, c2, d2 # Process rows so that a1, a2 become zero. row0 = input[0] ; a0 = row0[0] for p in (1,2) : rowp = input[p] ; ap = rowp[0] if ap : if ap == a0 : input[p] = [ (v1-v2) for (v1,v2) in zip(row0, rowp) ] elif ap == -a0: input[p] = [ (v1+v2) for (v1,v2) in zip(row0, rowp) ] else : input[p] = [ (v0*ap-vp*a0) for (v0,vp) in zip(row0, rowp) ] if input[p][0] : {}['Internal error. input[{}][0] should be 0.'.format(p)] (a0,b0,c0,d0), (a1,b1,c1,d1), (a2,b2,c2,d2) = input # The matrix is: # a0, b0, c0, d0 with a0 non-zero. # 0, b1, c1, d1 # 0, b2, c2, d2 two_rows = (b1,c1,d1), (b2,c2,d2) output = solve2by3 (two_rows, level-1) if output : y,z = output # a0 x + b0 y + c0 z + d0 = 0 x = -(b0*y + c0*z + d0)/a0 # Here is why a0 must be non-zero. output = x,y,z except : error = str(sys.exc_info())[1:].split(',') ; error[1:] = [ ','.join(error[1:-1]) ] # if error : print (thisName) for v in error : print (' ', v.strip()) if input : print (' input of solve3by4() =') print (' ', input[0]) print (' ', input[1]) print (' ', input[2]) return None # return output </syntaxhighlight> ====Examples==== Below are examples of invocation with both good data and bad data. Invocation with good data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve3by4([ [2, -1, 3, -17], [1, 3, 2, -25] , [3, 2, -1, -12] , ]) print (output) </syntaxhighlight> <pre> (3.0, 4.0, 5.0) </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve3by4([ [12, -12, -5, -24], [-6, 15, 8, 12] , [ 0, 10, 3, 0] , ]) print (output) </syntaxhighlight> <pre> (2.0, 0.0, -0.0) </pre> {{RoundBoxBottom}} Invocation with bad or invalid data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve3by4([ [20, 16, 2, 17], [-77, -27, -25, -24], [81, 45, 18, 43] ]) print (output) </syntaxhighlight> <pre> solve3by4 (input_) : <class 'KeyError'> KeyError('Three rows form tent.') input of solve3by4() = [20, 16, 2, 17] [-77, -27, -25, -24] [81, 45, 18, 43] None </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve3by4([ [34, -5, -21, 30], [-54, -33, 63, 62], [18, 11, -21, 38] ]) print (output) </syntaxhighlight> <pre> solve3by4 (input_) : <class 'KeyError'> KeyError('Two rows parallel: 1,2') input of solve3by4() = [34, -5, -21, 30] [-54, -33, 63, 62] [18, 11, -21, 38] None </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve3by4([ [20, 16, 2, 17], [-77, -27, '-25', -24], [81, 45, 18, 43] ]) print (output) </syntaxhighlight> <pre> solve3by4 (input_) : <class 'KeyError'> KeyError('Non-numeric value in input.') input of solve3by4() = [20, 16, 2, 17] [-77, -27, '-25', -24] [81, 45, 18, 43] None </pre> {{RoundBoxBottom}} ===Reversing the Process=== ====Quadratic function==== [[File:1212quadratic01.png|thumb|400px|''' Figure 1. Graph of quadratic function defined by 3 points.''' ]] A quadratic function <math>y = f(x) = Ax^2 + Bx + C</math> is defined by 3 points: <math>(-2, 9.0), (5, 4.8), (10, 13.8).</math> What is <math>f(x)?</math> <math>y = Ax^2 + Bx + C</math> <math>A, B, C</math> are 3 unknowns. <math>x^2(A) + x(B) + 1(C) - y = 0</math> <syntaxhighlight lang=python> # python code: x1,y1 = -2, 9 x2,y2 = 5, 4.8 x3,y3 = 10, 13.8 input = [ [x1**2, x1, 1, -y1], [x2**2, x2, 1, -y2], [x3**2, x3, 1, -y3], ] A, B, C = solve3by4 (input) s1 = 'A,B,C' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> A,B,C (0.2, -1.2, 5.8) </syntaxhighlight> <math>y = f(x) = 0.2x^2 - 1.2x + 5.8</math> ====Wrong assumptions==== [[File:1212plane02.png|thumb|400px|''' Figure 2. Graph of plane containing X axis.''' </br> Because plane passes through origin, non-zero value for coefficient <math>D</math> is impossible. </br> Because plane is parallel to <math>X</math> axis, non-zero value for coefficient <math>A</math> is impossible. ]] In 3 dimensions a plane (<math>Ax + By + Cz + D = 0</math>) is defined by 3 points: <math>(5, 3, -2), (-1, 12, -8), (37, 15, -10).</math> What is equation of plane? <math>Ax + By + Cz + D = 0</math> <math>xA + yB + zC + D = 0</math> Assume that <math>D = 1.</math> <math>xA + yB + zC + 1 = 0</math> <syntaxhighlight lang=python> # python code pt1 = x1,y1,z1 = (5, 3, -2) pt2 = x2,y2,z2 = (-1, 12, -8) pt3 = x3,y3,z3 = (37, 15, -10) input = [ [ 5, 3, -2, 1], [-1, 12, -8, 1], [37, 15, -10, 1], ] result = solve3by4 (input) s1 = 'result' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> solve2by3() : parallel input. input = (-63, 42, -6) (36, -24, 32) checkDirectionNumbers() : 3 rows form a tent. input of solve3by4() = (5, 3, -2, 1) (-1, 12, -8, 1) (37, 15, -10, 1) result None </syntaxhighlight> Input was invalid. Rotate input left and try again. <syntaxhighlight lang=python> # python code. input = [ [ 3, -2, 1, 5], [12, -8, 1, -1], [15, -10, 1, 37], ] result = solve3by4 (input) s1 = 'result' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> solve2by3() : empty column in input. input = (0, 9, 63) (0, 12, -36) checkDirectionNumbers() : 3 rows form a tent. input of solve3by4() = (3, -2, 1, 5) (12, -8, 1, -1) (15, -10, 1, 37) result None </syntaxhighlight> Input was invalid. Rotate input left and try again. <syntaxhighlight lang=python> input = [ [ -2, 1, 5, 3], [ -8, 1, -1, 12], [-10, 1, 37, 15], ] result = solve3by4 (input) s1 = 'result' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> result (1.5, 0, 0) </syntaxhighlight> Without rotation: <math>A, B, C = \text{result}</math> and <math>D = 1.</math> With rotation left: <math>B, C, D = \text{result}</math> and <math>A = 1.</math> With another rotation left: <math>C, D, A = \text{result}</math> and <math>B = 1.</math> <syntaxhighlight lang=python> # python code: C, D, A = (1.5, 0, 0) ; B = 1 A, B, C, D </syntaxhighlight> <syntaxhighlight> (0, 1, 1.5, 0) </syntaxhighlight> Equation of plane is: <math>0x + 1y + 1.5z + 0 = 0</math> or <math>2y + 3z = 0</math> =====A better method===== {{RoundBoxTop|theme=3}} There are four unknown values: <math>A,B,C,D.</math> Create matrix 4 by 5: <syntaxhighlight lang=python> # python code. pt1 = x1,y1,z1 = (5, 3, -2) pt2 = x2,y2,z2 = (-1, 12, -8) pt3 = x3,y3,z3 = (37, 15, -10) input = [] for (x_,y_,z_) in (pt1,pt2,pt3) : x,y,z = [ dD(v) for v in (x_,y_,z_) ] input += [ [ x,y,z,1,0 ] ] # For valid plane at least one of A,B,C must be non-zero. # For last condition let A + B + C = 5. input += [ [ 1,1,1,0,-5 ] ] A,B,C,D = solveMbyN(input) print (input) print ( '({})x + ({})y + ({})z + ({}) = 0'.format(A,B,C,D) ) </syntaxhighlight> <syntaxhighlight> [[ 5, 3, -2, 1, 0], # 5A + 3B - 2C + 1D + 0 = 0 [-1, 12, -8, 1, 0], # -1A + 12B - 8C + 1D + 0 = 0 [37, 15, -10, 1, 0], # 37A + 15B - 10C + 1D + 0 = 0 [ 1, 1, 1, 0, -5]] # 1A + 1B + 1C + 0D - 5 = 0 (0)x + (2)y + (3)z + (0) = 0 </syntaxhighlight> Equation of plane is: <math>2y + 3z = 0.</math> {{RoundBoxBottom}} ==Solving M by (M+1)== ===Implementation=== Below is python code containing function <code>solveMbyN (input).</code> The function accepts as input a 4 by 5 matrix (or greater) like that described in the code comments. This function is recursive, calling itself with M being reduced by 1 with each recursive invocation until the matrix is size 3 by 4 in which case function solve3by4() is called. <syntaxhighlight lang=python> # python code enable_reduceRow = 0 FPE = FloatingPointError # Not used by python. Used here as target of 'goto'. def solveMbyN (input_, level=0) : ''' Input represents system: a0*w + b0*x + c0*y + d0*z + e0 = 0 a1*w + b1*x + c1*y + d1*z + e1 = 0 a2*w + b2*x + c2*y + d2*z + e2 = 0 a3*w + b3*x + c3*y + d3*z + e3 = 0 or greater. This solves a matrix of M rows by N columns where N = M+1 and M >= 2 input = [ (a0,b0,c0,d0,e0), (a1,b1,c1,d1,e1), (a2,b2,c2,d2,e2), (a3,b3,c3,d3,e3), ] To invoke: w,x,y,z = solveMbyN (input [, level]) Function solveMbyN () may return None. If input is size 15 by 16: v1,v2,v3, .... ,v14,v15 = solveMbyN (input) Input is not changed by this function. ''' thisName = 'solveMbyN (input_, level = {}) :'.format(level) try : error = 0 try: input = [ list(v) for v in input_ ] except : input = 0 input or {}['input_ not recognized.'] number_of_rows = len(input) (number_of_rows > 1) or {}['number_of_rows must be > 1.'] if number_of_rows == 2 : output = solve2by3(input, level) raise FPE # Equivalent to goto. if number_of_rows == 3 : output = solve3by4(input, level) raise FPE # Equivalent to goto. number_of_columns = number_of_rows + 1 if level == 0 : dD_count = other_count = 0 for row_number in range (number_of_rows-1,-1,-1) : row = input[row_number] # Check that each row is correct length. if (len(row) != number_of_columns) : error = [ 'row # {} has bad length: {}'.format(row_number, len(row))] error += [ 'Correct length is : {}'.format(number_of_columns)] raise FPE for v in row : # Check that all data is numeric. isinstance(v, (int,float,dD)) or {}['Non-numeric value in input.'] # Record if type dD or not. if isinstance(v, dD) : dD_count += 1 else : other_count += 1 if dD_count and other_count : # Mix of types Decimal and non-Decimal in input. Make all values type Decimal. input = [ [ dD(str(p)) for p in row ] for row in input ] # Each row must not be empty. for row_number in range (number_of_rows-1,-1,-1) : found = 0 for v in input[row_number][:-1]: if v : found = 1 ; break if not found : {}['Empty row in input: # {} of {} rows.'.format(row_number, number_of_rows)] # Arrange input if necessary so that a0 is non-zero. if not input[0][0] : for p in range (1, number_of_rows) : if input[p][0] : input[p], input[0] = input[0], input[p] break # The matrix is: # [a0,b0,c0,d0,e0], with a0 non-zero, # [a1,b1,c1,d1,e1], # [a2,b2,c2,d2,e2], # [a3,b3,c3,d3,e3], # If abs(level) is large, following test can produce error: # OverflowError('int too large to convert to float') # Solution is to convert values in input to type float or Decimal. dD(input[0][0]) ; float(input[0][0]) # Each column must not be empty. for column_number in range (number_of_columns-2,-1,-1) : found = 0 for row in input : if row[column_number] : found = 1 ; break if not found : {}['Empty column in input: # {} of {} columns.'.format(column_number, number_of_columns)] if enable_reduceRow : # global variable # For matrices greater than 10 by 11 enable this piece of code. # This code calculates the max(abs) of all values in row, # divides all values by the max(abs) and updates row with result. # [27, -15, 42] becomes [27/42, -15/42, 42/42]. # Without this code you may see: # solveMbyN (input, level = -52) : # <class 'decimal.Overflow'> # Overflow([<class 'decimal.Overflow'>]) for row in input : max = 0 for v in row : if abs(v) > max : max = abs(v) if max < 1e100 : continue for column_number in range (number_of_columns-1,-1,-1) : if row[column_number] : row[column_number] /= max # Process rows so that a1, a2, a3, .... become zero. row0 = input[0] ; a0 = row0[0] for p in range (1, number_of_rows) : rowp = input[p] ; ap = rowp[0] if ap : if ap == a0 : input[p] = [ (v1-v2) for (v1,v2) in zip(row0, rowp) ] elif ap == -a0: input[p] = [ (v1+v2) for (v1,v2) in zip(row0, rowp) ] else : input[p] = [ (v0*ap-vp*a0) for (v0,vp) in zip(row0, rowp) ] if input[p][0] : try: str1 = str(float(input[p][0])) except : str1 = 'Error' {}['Internal error. input[{}][0] = {}, should be 0.'.format(p,str1)] # The matrix is: # [a0, b0, c0, d0, e0], with a0 non-zero, # [ 0, b1, c1, d1, e1], # [ 0, b2, c2, d2, e2], # [ 0, b3, c3, d3, e3], next_input = [ row[1:] for row in input[1:] ] # next_input is : # [ b1, c1, d1, e1], # [ b2, c2, d2, e2], # [ b3, c3, d3, e3], output = solveMbyN (next_input, level-1) # Here is where function solveMbyN() calls itself. if output : # input[0] = a0, b0, c0, d0, e0 # output = x, y, z (len(input[0][1:-1]) == len(output)) or {}["Internal error. Inputs to zip() don't match."] listOfProducts = [ v1*v2 for v1,v2 in zip(input[0][1:-1], output) ] # listOfProducts = [ b0*x, c0*y, d0*z ] sumOfProducts = input[0][-1] for v in listOfProducts : sumOfProducts += v # sumOfProducts = b0*x + c0*y + d0*z + e0 # a0*w + b0*x + c0*y + d0*z + e0 = 0 # a0*w + sumOfProducts = 0 w = -sumOfProducts/a0 # Here is why a0 must be non-zero. output = (w,) + output except FPE : pass # Target of 'goto'. except : error = str(sys.exc_info())[1:].split(',') ; error[1:] = [ ','.join(error[1:-1]) ] # if error : print (thisName) for v in error : print (' ', v.strip()) if input : print (' Length of input =', len(input)) for p in range (0, len(input)) : if p >= 8 : break try : row = [ float(v) for v in input_[p] ] except : row = 'Error in this row.' print (' input_[{}] ='.format(p), row) return None # return output </syntaxhighlight> ===Examples=== Below are examples of invocation with both good data and bad data. Invocation with good data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> L1 = [ [Decimal('-870442133162'), Decimal('239132906684'), Decimal('397660499756'), Decimal('788825405004'), Decimal('156830886652'), Decimal('-87096140169')], [Decimal('-112130420352'), Decimal('-93605595828'), Decimal('-185262083472'), Decimal('-93369903383'), Decimal('-497973505065'), Decimal('-766710012513')], [Decimal('-142983492168'), Decimal('619713461197'), Decimal('-608752759383'), Decimal('-448477443042'), Decimal('-281161661751'), Decimal('-799463977245')], [Decimal('572854919541'), Decimal('-148673693908'), Decimal('341291756040'), Decimal('362403188059'), Decimal('-202136092949'), Decimal('-429932229578')], [Decimal('157632861972'), Decimal('330790263276'), Decimal('-836474627955'), Decimal('644295395386'), Decimal('-595590967129'), Decimal('-392835045727')] ] output = solveMbyN(L1) print (output) </syntaxhighlight> The following results were produced with decimal precision set at 50: <pre> ( Decimal('-0.06331410760212760088313271882866553044211194694576'), Decimal('1.0969089506763419155148060427588009931309074487534'), Decimal('1.0837038580207682607126722016017867670831200359767'), Decimal('-0.42989566124678842791674322699930461340596671792215'), Decimal('-2.0541601084281682582146753421426610779297051535362') ) </pre> {{RoundBoxBottom}} Invocation with bad or invalid data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solveMbyN([ [-4, -6, 3, -4, -8, -8], [1, 0, 2, 5, 1, 7], [9, -3, -8, 4, 7, -5], [1, -9, 5, -2, 5, -2], [1, -3, -6, -3, -6, 6] ]) print (output) </syntaxhighlight> <pre> # With each step towards solve2by3() the length of each number in digits can theoretically double. solve2by3() : parallel input. input = (-181440, 181440, -101088) (90720, -90720, 406944) checkDirectionNumbers() : 3 rows form a tent. input of solve3by4() = [-756, -1176, 0, -1872] [-324, -744, 240, -936] [-324, -384, -120, -264] input of solveMbyN() with 4 rows = [-6, 11, 16, -4, 20] [-66, -5, -20, -44, -92] [-42, 23, -12, 12, -16] [-18, -21, -16, -32, 16] input of solveMbyN() with 5 rows = [-4, -6, 3, -4, -8, -8] [1, 0, 2, 5, 1, 7] [9, -3, -8, 4, 7, -5] [1, -9, 5, -2, 5, -2] [1, -3, -6, -3, -6, 6] None </pre> Provided that numbers are small, integers, floats and Decimal objects produce the same results: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solveMbyN([ [-4.0, -6.0, 3.0, -4.0, -8.0, -8.0], [1.0, 0.0, 2.0, 5.0, 1.0, 7.0], [9.0, -3.0, -8.0, 4.0, 7.0, -5.0], [1.0, -9.0, 5.0, -2.0, 5.0, -2.0], [1.0, -3.0, -6.0, -3.0, -6.0, 6.0] ]) print (output) </syntaxhighlight> <pre> solve2by3() : parallel input. input = (-181440.0, 181440.0, -101088.0) (90720.0, -90720.0, 406944.0) checkDirectionNumbers() : 3 rows form a tent. input of solve3by4() = [-756.0, -1176.0, 0.0, -1872.0] [-324.0, -744.0, 240.0, -936.0] [-324.0, -384.0, -120.0, -264.0] input of solveMbyN() with 4 rows = [-6.0, 11.0, 16.0, -4.0, 20.0] [-66.0, -5.0, -20.0, -44.0, -92.0] [-42.0, 23.0, -12.0, 12.0, -16.0] [-18.0, -21.0, -16.0, -32.0, 16.0] input of solveMbyN() with 5 rows = [-4.0, -6.0, 3.0, -4.0, -8.0, -8.0] [1.0, 0.0, 2.0, 5.0, 1.0, 7.0] [9.0, -3.0, -8.0, 4.0, 7.0, -5.0] [1.0, -9.0, 5.0, -2.0, 5.0, -2.0] [1.0, -3.0, -6.0, -3.0, -6.0, 6.0] None </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solveMbyN([ [Decimal('-4'), Decimal('-6'), Decimal('3'), Decimal('-4'), Decimal('-8'), Decimal('-8')], [Decimal('1'), Decimal('0'), Decimal('2'), Decimal('5'), Decimal('1'), Decimal('7')], [Decimal('9'), Decimal('-3'), Decimal('-8'), Decimal('4'), Decimal('7'), Decimal('-5')], [Decimal('1'), Decimal('-9'), Decimal('5'), Decimal('-2'), Decimal('5'), Decimal('-2')], [Decimal('1'), Decimal('-3'), Decimal('-6'), Decimal('-3'), Decimal('-6'), Decimal('6')] ]) print (output) </syntaxhighlight> <pre> solve2by3() : parallel input. input = (Decimal('-181440'), Decimal('181440'), Decimal('-101088')) (Decimal('90720'), Decimal('-90720'), Decimal('406944')) checkDirectionNumbers() : 3 rows form a tent. input of solve3by4() = [Decimal('-756'), Decimal('-1176'), Decimal('0'), Decimal('-1872')] [Decimal('-324'), Decimal('-744'), Decimal('240'), Decimal('-936')] [Decimal('-324'), Decimal('-384'), Decimal('-120'), Decimal('-264')] input of solveMbyN() with 4 rows = [Decimal('-6'), Decimal('11'), Decimal('16'), Decimal('-4'), Decimal('20')] [Decimal('-66'), Decimal('-5'), Decimal('-20'), Decimal('-44'), Decimal('-92')] [Decimal('-42'), Decimal('23'), Decimal('-12'), Decimal('12'), Decimal('-16')] [Decimal('-18'), Decimal('-21'), Decimal('-16'), Decimal('-32'), Decimal('16')] input of solveMbyN() with 5 rows = [Decimal('-4'), Decimal('-6'), Decimal('3'), Decimal('-4'), Decimal('-8'), Decimal('-8')] [Decimal('1'), Decimal('0'), Decimal('2'), Decimal('5'), Decimal('1'), Decimal('7')] [Decimal('9'), Decimal('-3'), Decimal('-8'), Decimal('4'), Decimal('7'), Decimal('-5')] [Decimal('1'), Decimal('-9'), Decimal('5'), Decimal('-2'), Decimal('5'), Decimal('-2')] [Decimal('1'), Decimal('-3'), Decimal('-6'), Decimal('-3'), Decimal('-6'), Decimal('6')] None </pre> {{RoundBoxBottom}} {{RoundBoxBottom}} ===Sphere=== In cartesian coordinate geometry of three dimensions a sphere is represented by equation: <math>x^2 + y^2 + z^2 + Ax + By + Cz + D = 0.</math> On the surface of a certain sphere there are 4 known points: <syntaxhighlight lang=python> # python code point1 = (13,7,20) point2 = (13,7,4) point3 = (13,-17,4) point4 = (16,4,4) </syntaxhighlight> What is equation of sphere? Rearrange equation of sphere to prepare for creation of input matrix: <math>(x)A + (y)B + (z)C + (1)D + (x^2 + y^2 + z^2) = 0.</math> Create input matrix of size 4 by 5: <syntaxhighlight lang=python> # python code input = [] for (x,y,z) in (point1, point2, point3, point4) : input += [ ( x, y, z, 1, (x**2 + y**2 + z**2) ) ] print (input) </syntaxhighlight> <syntaxhighlight> [ (13, 7, 20, 1, 618), (13, 7, 4, 1, 234), (13, -17, 4, 1, 474), (16, 4, 4, 1, 288), ] # Matrix containing 4 rows with 5 members per row. </syntaxhighlight> <syntaxhighlight lang=python> # python code result = solveMbyN(input) print (result) </syntaxhighlight> <syntaxhighlight> (-8.0, 10.0, -24.0, -104.0) </syntaxhighlight> Equation of sphere is : <math>x^2 + y^2 + z^2 - 8x + 10y - 24z - 104 = 0</math> ===Quintic function=== [[File:1212quintic01.png|thumb|400px|''' Figure 4. Graph of quintic function defined by 6 points.''' ]] A quintic function <math>y = f(x) = Ax^5 + Bx^4 + Cx^3 + Dx^2 + Ex + F</math> is defined by 6 points: <math>(-8, 0), (-6, 0), (-3, 0), (1,0), (3,0), (5,10).</math> What is <math>f(x)?</math> <math>y = f(x) = Ax^5 + Bx^4 + Cx^3 + Dx^2 + Ex + F</math> <math>A, B, C, D, E, F</math> are 6 unknowns. <math>x^5(A) + x^4(B) + x^3(C) + x^2(D) + x(E) + 1(F) - y = 0</math> <syntaxhighlight lang=python> # python code: pt1 = x1,y1 = -8,0 pt2 = x2,y2 = -6,0 pt3 = x3,y3 = -3,0 pt4 = x4,y4 = 1,0 pt5 = x4,y5 = 3,0 pt6 = x6,y6 = 5,10 input = [] for pt in (pt1,pt2,pt3,pt4,pt5,pt6) : x,y = pt input += [[ x**5, x**4, x**3, x**2, x, 1, -y ]] print (input) </syntaxhighlight> <syntaxhighlight> [[-32768, 4096, -512, 64, -8, 1, 0], [ -7776, 1296, -216, 36, -6, 1, 0], [ -243, 81, -27, 9, -3, 1, 0], [ 1, 1, 1, 1, 1, 1, 0], [ 243, 81, 27, 9, 3, 1, 0], [ 3125, 625, 125, 25, 5, 1, -10]] </syntaxhighlight> <syntaxhighlight> result = solveMbyN (input) s1 = 'result' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> result (0.0010926573426573423, 0.014204545454545447, 0.027316433566433533, -0.18028846153846156, -0.3343531468531468, 0.47202797202797203) </syntaxhighlight> From these results the following ratios may be deduced: <math>\frac{1}{A} = 915.2;\ </math> <math>\frac{B}{A} = 13;\ </math> <math>\frac{C}{A} = 25;\ </math> <math>\frac{D}{A} = -165;\ </math> <math>\frac{E}{A} = -306;\ </math> <math>\frac{F}{A} = 432.</math> <math>y = f(x) = \frac{x^5 + 13x^4 + 25x^3 - 165x^2 - 306x + 432}{915.2}</math> ===Resistive network=== {{RoundBoxTop|theme=2}} [[File:1127network01.png|thumb|400px|''' Figure 1. Diagram of resistive network containing 8 resistors.''' ]] A resistive network containing 8 resistors is connected as shown in Figure 1. What is resistance <math>R</math> between points <math>P_1, P_3?</math> {{RoundBoxBottom}} ====Solve for 8 Branch Currents==== {{RoundBoxTop|theme=2}} [[File:1127network02.png|thumb|400px|''' Figure 2. Diagram of resistive network showing all branch currents.''' </br> </br> At any point to which 3 or more conductors are connected, sum of currents = 0. </br> At point <math>P_4</math> currents <math>i_1, i_7</math> flow towards point; current <math>i_4</math> flows away from point. </br> <math>i_1 + i_7 - i_4 = 0.</math> </br> </br> In any closed loop sum of voltages = 0. </br> In loop containing points <math>P_1, P_2</math> voltages <math>e_2, e_8</math> are clockwise; voltage <math>e_3</math> is counter-clockwise. <math></math> </br> <math>e_2 + e_8 - e_3 = 0.</math><math></math><math></math> </br> </br> Direction of flow through <math>r_7, r_8</math> is assumed and is subject to correction. ]] Voltage across <math>r_1:</math> Using <math>E = IR,\ e_1 = i_1\cdot r_1 = r_1\cdot a.</math> Similarly: <math>e_2 = r_2\cdot b.</math> <math>e_3 = r_3\cdot c.</math> <math>\dots\dots</math> <math>e_8 = r_8\cdot h.</math> Build a matrix size 8 by 9 which will be input to function solveMbyN(). <syntaxhighlight lang=python> # Python code: r1,r2,r3,r4,r5,r6,r7,r8 = 10,20,30,40,50,60,70,80 input = [] # e1 = e2 + e7 # 10a = 20b + 70g # 10a - 20b + 0c + 0d + 0e + 0f - 70g + 0h + 0 = 0 input += [[r1, - r2, 0, 0, 0, 0, - r7, 0, 0]] # e3 = e2 + e8 # 30c = 20b + 80h # 0a - 20b + 30c + 0d + 0e + 0f + 0g - 80h + 0 = 0 input += [[0, - r2, r3, 0, 0, 0, 0, - r8, 0]] # e5 = e7 + e4 # 50e = 70g + 40d # 0a + 0b + 0c - 40d + 50e + 0f - 70g + 0h + 0 = 0 input += [[0, 0, 0, - r4, r5, 0, - r7, 0, 0]] # e5 = e8 + e6 # 50e = 80h + 60f # 0a + 0b + 0c + 0d + 50e - 60f + 0g - 80h + 0 = 0 input += [[0, 0, 0, 0, r5, - r6, 0, - r8, 0]] # i7 + i5 + i8 = i2 # g + e + h = b # 0a - 1b + 0c + 0d + 1e + 0f + 1g + 1h + 0 = 0 input += [[0 ,- 1, 0, 0, 1, 0, 1, 1, 0]] # i4 = i1 + i7 # d = a + g # -1a + 0b + 0c + 1d + 0e + 0f - 1g + 0h + 0 = 0 input += [[-1, 0, 0, 1, 0, 0, - 1, 0, 0]] # i6 = i3 + i8 # f = c + h # 0a + 0b - 1c + 0d + 0e + 1f + 0g - 1h + 0 = 0 input += [[0, 0, - 1, 0, 0, 1, 0, - 1, 0]] # Total input current = 1 # a + b + c = 1 # 1a + 1b + 1c + 0d + 0e + 0f + 0g + 0h - 1 = 0 input += [[1, 1, 1, 0, 0, 0, 0, 0, - 1]] </syntaxhighlight> This last entry can contain almost any arbitrary values. For example: <syntaxhighlight lang=python> # Python code: # i7 = 2.3 input += [[0, 0, 0, 0, 0, 0, 1, 0, - 2.3]] # e5 = 1.9 input += [[0, 0, 0, 0, r5, 0, 0, 0, - 1.9]] </syntaxhighlight> Changing this last entry changes all values of <math>e_x, i_x.</math> However, the ratio <math>\frac{e_x}{i_x} = r_x</math> remains constant. {{RoundBoxTop|theme=3}} input is matrix of size 8 by 9: <syntaxhighlight> [ [10, -20, 0, 0, 0, 0, -70, 0, 0], # e1 = e2 + e7, or r1(i1) - r2(i2) - r7(i7) = 0 [ 0, -20, 30, 0, 0, 0, 0, -80, 0], # e3 = e2 + e8, or r3(i3) - r2(i2) - r8(i8) = 0 [ 0, 0, 0, -40, 50, 0, -70, 0, 0], # e5 = e4 + e7, or r5(i5) - r4(i4) - r7(i7) = 0 [ 0, 0, 0, 0, 50, -60, 0, -80, 0], # e5 = e6 + e8, or r5(i5) - r6(i6) - r8(i8) = 0 [ 0, -1, 0, 0, 1, 0, 1, 1, 0], # i2 = i5 + i7 + i8, or 1(i5) + 1(i7) + 1(i8) - 1(i2) = 0 [-1, 0, 0, 1, 0, 0, -1, 0, 0], # i4 = i1 + i7, or 1(i4) - 1(i1) - 1(i7) = 0 [ 0, 0, -1, 0, 0, 1, 0, -1, 0], # i6 = i3 + i8, or 1(i6) - 1(i3) - 1(i8) = 0 [ 1, 1, 1, 0, 0, 0, 0, 0, -1] # i1 + i2 + i3 = 1, or 1(i1) + 1(i2) + 1(i3) - 1 = 0 ] </syntaxhighlight> {{RoundBoxBottom}} <syntaxhighlight lang=python> i1,i2,i3,i4,i5,i6,i7,i8 = values_of_i = solveMbyN (input) s1 = 'values_of_i' ; print(s1,eval(s1)) s1 = 'i1 + i2 + i3' ; print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> values_of_i (0.45727389222364606, 0.3065353746543468, 0.23619073312200717, 0.4350171983543536, 0.31685438726647336, 0.24812841437917316, -0.022256693869292507, 0.011937681257165982) i1 + i2 + i3 1.0 </syntaxhighlight> <math>i_7</math> has negative value. Reverse <math>i_7</math> to make all branch currents positive. {{RoundBoxBottom}} ====Make all Branch Currents positive==== {{RoundBoxTop|theme=2}} [[File:1127network03.png|thumb|400px|''' Figure 3. Diagram of resistive network showing all branch currents positive.''' ]] Make <math>i_7</math> positive and check results. <syntaxhighlight lang=python> # Python code i7 *= -1 values_of_e = e1,e2,e3,e4,e5,e6,e7,e8 = [ eval(s1) for s in '12345678' for s1 in [ 'i' + s + '*r' + s ] ] s1 = 'values_of_e' print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> values_of_e [ 4.572738922236461, 6.130707493086937, 7.085721993660215, 17.400687934174144, 15.842719363323669, 14.88770486275039, 1.5579685708504756, 0.9550145005732785] </syntaxhighlight> <syntaxhighlight lang=python> # python code t1 = ( 'e1+e7-e2', # e1 + e7 should equal e2 'e2+e8-e3', # e2 + e8 should equal e3 'e7+e5-e4', # e7 + e5 should equal e4 'e8+e6-e5', # e8 + e6 should equal e5 'e1+e4-(e2+e5)', # e1 + e4 should equal e2 + e5 'e1+e4-(e3+e6)', # e1 + e4 should equal e3 + e6 'e1+e7+e8-e3', # e1 + e7 + e8 should equal e3 'e7+e8+e6-e4', # e7 + e8 + e6 should equal e4 'i1-i7-i4', # i1 should equal i7 + i4 'i6-i3-i8', # i6 should equal i3 + i8 'i2+i7-(i8+i5)', # i2 + i7 should equal i8 + i5 'i1+i2+i3 - (i4+i5+i6)', # Total input current should # equal total output current. ) for s1 in t1 : print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> e1+e7-e2 -8.881784197001252e-16 e2+e8-e3 0.0 e7+e5-e4 0.0 e8+e6-e5 0.0 e1+e4-(e2+e5) 0.0 e1+e4-(e3+e6) 0.0 e1+e7+e8-e3 -8.881784197001252e-16 e7+e8+e6-e4 0.0 i1-i7-i4 -5.551115123125783e-17 i6-i3-i8 6.938893903907228e-18 i2+i7-(i8+i5) 0.0 i1+i2+i3 - (i4+i5+i6) 0.0 </syntaxhighlight> {{RoundBoxBottom}} ====Compute R==== {{RoundBoxTop|theme=8}} <syntaxhighlight lang=python> # Python code E1 = e3+e6 I1 = i1 + i2 + i3 R1 = E1/I1 s1 = 'R1' ; print(s1,eval(s1)) E2 = e1 + e7 + e5 I2 = i4 + i5 + i6 R2 = E2/I2 s1 = 'R2' ; print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> R1 21.973426856410605 R2 21.973426856410605 </syntaxhighlight> <math>R = R_1 = R_2</math> {{RoundBoxBottom}} ==Solving big matrices== A big matrix is one of size greater than 10 by 11. With each recursive call of solveMbyN() the size of each value in decimal digits can theoretically double. Python's integer math enjoys infinite precision. If your original matrix is of size 32 by 33, and each value in the matrix is an int of 1 decimal digit, function solve2by3() can be called with ints of size 2**30 (1,073,741,824) decimal digits. Floats can be used instead of ints, but the limited precision of floats may not provide a desirable level of accuracy in the result. Python's decimal objects are a good compromise and function reduceRow() above is an attempt to keep the size of each member manageable. Function reduceRow() works well. However, as with all operations involving python's decimal objects, you need to pay careful attention to precision and accuracy of the results. On my Mac the following python code generates a matrix of size 100 by 101 and calculates the result containing 100 values in about 1.5 seconds, including the time to generate 10,100 random numbers, each containing up to 12 decimal digits with the decimal point in a random position, and including the time to test output over 100 rows to verify that all calculated values of the solution satisfy each row. In function solveMbyN() above find line: <syntaxhighlight lang=python> if 0 : # For matrices greater than 10 by 11 enable this piece of code. </syntaxhighlight> Change it to: <syntaxhighlight lang=python> if 1 : # For matrices greater than 10 by 11 enable this piece of code. </syntaxhighlight> Then: <syntaxhighlight lang=python> from random import getrandbits from decimal import * import sys getcontext().prec=50 # Set precision to 50. numRows=100 def randomNumber(): # 1 invocation in 256 returns 0. if not (getrandbits(10) & 0xFF) : return Decimal(0) return [ w for q in [ getrandbits(10) & 1] for sign in [ (-1,1)[q] ] for numberOfDecimalPlaces in [ getrandbits(10) & 0xF ] for s1 in [ str(getrandbits(50))[-12:] ] for s2 in [ '0'*12+s1 ] for posn in [ len(s2)-numberOfDecimalPlaces ] for w in [ sign*Decimal(s2[:posn]+'.'+s2[posn:]) ] ][0] data = [[ randomNumber() for p in range(numRows+1) ] for p in range (numRows) ] datan = sorted([ v for row in data for v in row if v < 0 ]) datap = sorted([ v for row in data for v in row if v >= 0 ]) print ('A small sample of the random numbers in data:') print ('+ve values:',len(datap), ',', datap[:2],'\n ',datap[-2:]) print ('-ve values:',len(datan), ',', datan[:2],'\n ',datan[-2:]) output = solveMbyN(data) print ('A small sample of the solutions:') print ('output[0] =', output[0]) print ('output[19] =', output[19]) print ('output[59] =', output[59]) print ('output[99] =', output[99]) </syntaxhighlight> <pre> A small sample of the random numbers in data: +ve values: 5021 , [Decimal('1.16871265E-7'), Decimal('1.73721245E-7')] [Decimal('998523464710'), Decimal('999768605679')] -ve values: 5079 , [Decimal('-991079944209'), Decimal('-989786083110')] [Decimal('-4.10272824E-7'), Decimal('-2.38664537E-7')] A small sample of the solutions: output[0] = 0.43689400018920695253771832432651757885163362928745 output[19] = 0.19867480862268284151047885891372314311902973127033 output[59] = 0.46169681824826309421940885550155275946668017604646 output[99] = -0.020598220802233733529683040085023443421113627790464 </pre> ===Testing results=== Data input to function solveMbyN() is an array of 100 rows, each row containing 101 numbers. <pre> [ [v0_0, v0_1, v0_2, ..... v0_98,v0_99,v0_100], ....... [v99_0,v99_1,v99_2, ...... v99_98,v99_99,v99_100],] ] </pre> Data received from function solveMbyN() is an array of 100 numbers. <pre> [ s0,s1,s2, ...... s98,s99 ] </pre> The first row is tested with the solutions by; <pre> L2 = [ v0_0*s0, v0_1*s1, v0_2*s2, ..... v0_98*s98,v0_99*s99,v0_100 ] </pre> sum is the sum of all items in L2. sum is appended to L1 and the process is repeated for all 100 rows. <syntaxhighlight lang=python> L1 = [] for row in data : # a, b, c, d, e, f, g ....... # row # u, v, w, x, y, z # output L2 = [ row[p]*t1[p] for t1 in (output+(1,),) for p in range (0, len(row)) ] # L2 = [a*u , b*v , c*w , d*x , e*y , f*z , g] sum = [ sum for sum in [0] for p in L2 for sum in [sum+p] ][-1] # sum = [a*u, a*u + b*v, a*u + b*v + c*w, a*u + b*v + c*w + d*x, a*u + b*v + c*w + d*x + e*y, # a*u + b*v + c*w + d*x + e*y + f*z, a*u + b*v + c*w + d*x + e*y + f*z + g][-1] # sum = a*u + b*v + c*w + d*x + e*y + f*z + g # sum is the sum of all items in L2 L1 += [abs(sum)] L1a = sorted(L1) print (len(L1a), L1a[0], L1a[-1]) </syntaxhighlight> Ideally sum should be zero. In practice it's extremely unlikely that sum will be zero. My results typically gave values close to <pre> 100 4.1065149609E-38 9.6425614873452398368906E-25 </pre> The worst of the results above was 23 zeroes after the decimal point. Better results can be achieved by increasing precision. ===Cubic Resistive Network=== {{RoundBoxTop|theme=2}} [[File:1129network01.png|thumb|400px|''' Figure 1. Diagram of resistive network containing 12 resistors.''' </br> Blue arrows show assumed direction of current. ]] A resistive network containing 12 resistors is connected as shown in Figure 1. The network is called "cubic" because, in 3 dimensions, each resistor is located on one edge of a cube. What is resistance <math>R</math> between points <math>P_1, P_2?</math> <syntaxhighlight lang=python> # Python code: values_of_r = r1,r2,r3,r4,r5,r6,r7,r8,r9,r10,r11,r12 = 10,20,30,40,50,60,70,80,90,100,110,120 </syntaxhighlight> {{RoundBoxBottom}} ====Solve for 12 Branch Currents==== =====Create matrix 12 by 13===== <syntaxhighlight lang=python> # Python code: input = [ [10, 20, -30, -40, 0, 0, 0, 0, 0, 0, 0, 0, 0], # e1 + e2 = e3 + e4 [ 0, 0, 0, 0, 50, 60, -70, -80, 0, 0, 0, 0, 0], # e5 + e6 = e7 + e8 [ 0, 0, 0, 40, 0, 0, 0, -80, 0, 0, 110, -120, 0], # e11 + e4 = e8 + e12 [10, 0, 0, 0, -50, 0, 0, 0, 90, -100, 0, 0, 0], # e9 + e1 = e5 + e10 [ 0, 0, 0, 0, 1, -1, 0, 0, 0, -1, 0, 0, 0], # i5 = i10 + i6 [ 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, -1, 0, 0], # i7 = i11 + i8 [-1, 0, -1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0], # i9 = i1 + i3 [ 0, 0, -1, 1, 0, 0, 0, 0, 0, 0, -1, 0, 0], # i4 = i3 + i11 [-1, 1, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0], # i2 = i1 + i10 [ 0, 0, 0, 0, 0, -1, 0, -1, 0, 0, 0, 1, 0], # i12 = i6 + i8 [ 0, -1, 0, -1, 1, 0, 1, 0, 1, 0, 0, -1, 0], # i9 + i5 + i7 = i2 + i4 + i12 [ 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1.6] # i3 = 1.6 ] i1,i2,i3,i4,i5,i6,i7,i8,i9,i10,i11,i12 = values_of_i = solveMbyN (input) s1 = 'values_of_i' print(s1,eval(s1)) </syntaxhighlight> This matrix failed: <syntaxhighlight> solve2by3() : empty row in input. input = (0, 0, 0) (90533116137774317568000000000000000000000000000000000000000000, -84449318308603494400000000000000000000000000000000000000000000, 1.4228848407261846e+61) checkDirectionNumbers() : 2 rows parallel, 1 and 2. input of solve3by4() = [38760268800000000000000000000, 593753233920000000000000000000, -569385344000000000000000000000, 0] [620164300800000000000000000000000000, 9500051742720000000000000000000000000, -9110165504000000000000000000000000000, 0] [153839206400000000000000000000000, 20882470400000000000000000000000, -81126144000000000000000000000000, -3.67098806272e+32] </syntaxhighlight> =====Try again===== <syntaxhighlight lang=python> # Python code: input = [ [10, 20, -30, -40, 0, 0, 0, 0, 0, 0, 0, 0, 0], # e1 + e2 = e3 + e4 [ 0, 0, 0, 0, 50, 60, -70, -80, 0, 0, 0, 0, 0], # e5 + e6 = e7 + e8 [ 0, 0, 0, 40, 0, 0, 0, -80, 0, 0, 110, -120, 0], # e11 + e4 = e8 + e12 [10, 0, 0, 0, -50, 0, 0, 0, 90, -100, 0, 0, 0], # e9 + e1 = e5 + e10 [ 0, 0, 0, 0, 1, -1, 0, 0, 0, -1, 0, 0, 0], # i5 = i10 + i6 [ 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, -1, 0, 0], # i7 = i11 + i8 [-1, 0, -1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0], # i9 = i1 + i3 [ 0, 0, -1, 1, 0, 0, 0, 0, 0, 0, -1, 0, 0], # i4 = i3 + i11 [-1, 1, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0], # i2 = i1 + i10 [ 0, 0, 0, 0, 0, -1, 0, -1, 0, 0, 0, 1, 0], # i12 = i6 + i8 #[ 0, -1, 0, -1, 1, 0, 1, 0, 1, 0, 0, -1, 0], # i9 + i5 + i7 = i2 + i4 + i12 DELETED. [10, 20, 0, 0, 0, 0, -70, -80, 90, 0, 0, -120, 0], # e9 + e1 + e2 = e7 + e8 + e12 ADDED. [ 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1.6] # i3 = 1.6 ] import decimal dD = decimal.Decimal dgt = decimal.getcontext() Precision = dgt.prec = 30 Tolerance = dD("1e-" + str(Precision-2)) # Convert all values in input to decimal objects with precision of 30. input = [ [ dD(str(p)) for p in v ] for v in input ] i1,i2,i3,i4,i5,i6,i7,i8,i9,i10,i11,i12 = values_of_i = solveMbyN (input) </syntaxhighlight> <syntaxhighlight> # values_of_i 5.5027171492204899777282850777 9.3809275973899113038721525414 1.5999999999999999999999999999 # i3 should be 1.6. 4.8661430860000781463681475402 6.12901340210213730316883522816 2.25080295393271597702496776458 4.68526862814050716992927753670 1.41912554214042902356112999643 7.10271714922048997772828507766 3.87821044816942132614386746358 3.26614308600007814636814754027 3.66992849607314500058609776103 </syntaxhighlight> ====Compute R==== {{RoundBoxTop|theme=8}} <syntaxhighlight lang=python> # python code values_of_e = e1,e2,e3,e4,e5,e6,e7,e8,e9,e10,e11,e12 = [ (i*r) for (i,r) in zip(values_of_i, values_of_r) ] </syntaxhighlight> <syntaxhighlight> values_of_e 55.0271714922048997772828507770 187.618551947798226077443050828 47.9999999999999999999999999970 194.645723440003125854725901608 306.450670105106865158441761408 135.048177235962958621498065875 327.968803969835501895049427569 113.530043371234321884890399714 639.244543429844097995545656989 387.821044816942132614386746358 359.275739460008596100496229430 440.391419528777400070331731324 </syntaxhighlight> <math>e_3</math> should be <math>48,\ i_3*r_3</math> or <math>1.6*30.</math> <syntaxhighlight lang=python> E1 = e5 + e10 + e2 I1 = i9 + i5 + i7 R1 = E1/I1 s1 = 'R1' ; print(s1,eval(s1)) E2 = e7 + e8 - e6 + e10 - e1 + e3 + e4 I2 = i2 + i4 + i12 R2 = E2/I2 s1 = 'R2' ; print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> R1 49.2208688540148837936367036806 R2 49.2208688540148837936367036803 </syntaxhighlight> Display results with precision of 28: <syntaxhighlight lang=python> dgt.prec = 28 R1 += 0 ; R2 += 0 dgt.prec = Precision s1 = 'R1' ; print(s1,eval(s1)) s1 = 'R2' ; print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> R1 49.22086885401488379363670368 R2 49.22086885401488379363670368 </syntaxhighlight> <math>R = R_1 = R_2.</math> {{RoundBoxBottom}} ====Review==== In matrix all values <math>i_1, i_2, \dots, i_{11}, i_{12}</math> and <math>e_1, e_2, \dots, e_{11}, e_{12}</math> are included. Testing was done with the following lines substituted for last line of matrix: <syntaxhighlight lang=python> # python code [ 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, -3.15] # i7 = 3.15 [ 0, 0, 0, r4, 0, 0, 0, 0, 0, 0, 0, 0, -6 ] # e4 = 6 [ 0, 0, r3, 0, 0, 0, 0, r8, 0, 0, 0, 0, -5 ] # e3 + e8 = 5 </syntaxhighlight> All tests produced a consistent value of <math>R.</math> ====Checking==== =====Examples of current nodes===== {{RoundBoxTop|theme=2}} <gallery> File:0101network01.png|<small><math>i_1 + i_{10} = i_2</math></small> File:0101network02.png|<small><math>i_6 + i_8 = i_{12}</math></small> </gallery> {{RoundBoxBottom}} =====Examples of voltage loops===== {{RoundBoxTop|theme=2}} <gallery> File:0108network00.png|<small>Top and Bottom.<math>e_1 + e_2 - e_4 - e_3 = 0</math><math>e_5 + e_6 - e_8 - e_7 = 0</math></small> File:0108network01.png|<small>Two sides in background.<math>e_5 + e_{10} - e_1 - e_9 = 0</math><math>e_6 + e_{12} - e_2 - e_{10} = 0</math></small> File:0108network02.png|<small>Two sides in foreground.<math>e_7 + e_{11} - e_3 - e_9 = 0</math><math>e_8 + e_{12} - e_4 - e_{11} = 0</math></small> </gallery> {{RoundBoxBottom}} =====Python code===== <syntaxhighlight lang=python> t1 = ( # 3 nodes on top 'i1 + i10 - i2', 'i1 + i3 - i9', 'i3 + i11 - i4', # 3 nodes on bottom 'i10 + i6 - i5', 'i11 + i8 - i7', 'i6 + i8 - i12', # Total input current equals total output current. 'i5 + i7 + i9 - i2 - i4 - i12', # Voltage loops # top 'e1 + e2 - e4 - e3', # bottom 'e5 + e6 - e8 - e7', # 2 sides in background 'e9 + e1 - e10 - e5', 'e10 + e2 - e12 - e6', # 2 sides in foreground 'e9 + e3 - e11 - e7', 'e11 + e4 - e12 - e8', # Some elaborate loops. 'e8 - e6 + e10 + e2 - e4 - e3 - e9 + e7', 'e10 + e2 - e12 - e8 + e11 - e3 - e9 + e5', ) </syntaxhighlight> Result of each of the above calculations should be <math>0.</math> Because of small rounding errors, result may not be exactly <math>0.</math> See values_of_i and values_of_e above. This code verifies that result is close enough to <math>0</math> to be acceptable. For example: <math>\text{result} = e_{10} + e_2 - e_{12} - e_8 + e_{11} - e_3 - e_9 + e_5.</math> <math>\text{v1} = e_{10} + e_2 + e_{11} + e_5,</math> sum of positive values. <math>\text{status = (abs(result)} < \text{(v1}*\text{Tolerance)). status}</math> should be <math>\text{True.}</math> <syntaxhighlight lang=python> # python code import re for str1 in t1 : str2 = re.sub ('\+', ';+', str1) str2 = re.sub ('\-', ';-', str2) L1 = str2.split(';') positives = ''.join([ v for v in L1 if '-' not in v ]) result = eval(str1) v1 = eval( positives ) status = (abs(result) < (v1*Tolerance)) str3 = (str1+(' '*40))[:42] str4 = ((' '*10) + str(result))[-10:] str5 = '{}{} {}'.format(str3,str4,status) print ( str5 ) </syntaxhighlight> {| class="wikitable" |- ! Calculation || Result !! Result Acceptable |- | <math> i_1 + i_{10} - i_2 </math> | <math> -1.2E-28 </math> | <math>\text{True}</math> |- | <math> i_1 + i_3 - i_9 </math> | <math> -6E-29 </math> | <math>\text{True}</math> |- | <math> i_3 + i_{11} - i_4 </math> | <math> -3E-29 </math> | <math>\text{True}</math> |- | <math> i_{10} + i_6 - i_5 </math> | <math> 0E-29 </math> | <math>\text{True}</math> |- | <math> i_{11} + i_8 - i_7 </math> | <math> 0E-29 </math> | <math>\text{True}</math> |- | <math> i_6 + i_8 - i_{12} </math> | <math> -2E-29 </math> | <math>\text{True}</math> |- | <math> i_5 + i_7 + i_9 - i_2 - i_4 - i_{12} </math> | <math> -3E-29 </math> | <math>\text{True}</math> |- | <math> e_1 + e_2 - e_4 - e_3 </math> | <math> 0E-28 </math> | <math>\text{True}</math> |- | <math> e_5 + e_6 - e_8 - e_7 </math> | <math> 0E-27 </math> | <math>\text{True}</math> |- | <math> e_9 + e_1 - e_{10} - e_5 </math> | <math> 0E-27 </math> | <math>\text{True}</math> |- | <math> e_{10} + e_2 - e_{12} - e_6 </math> | <math> -1.3E-26 </math> | <math>\text{True}</math> |- | <math> e_9 + e_3 - e_{11} - e_7 </math> | <math> -1.3E-26 </math> | <math>\text{True}</math> |- | <math> e_{11} + e_4 - e_{12} - e_8 </math> | <math> 0E-27 </math> | <math>\text{True}</math> |- | <math> e_8 - e_6 + e_{10} + e_2 - e_4 - e_3 - e_9 + e_7 </math> | <math> 0E-27 </math> | <math>\text{True}</math> |- | <math> e_{10} + e_2 - e_{12} - e_8 + e_{11} - e_3 - e_9 + e_5 </math> | <math> 0E-27 </math> | <math>\text{True}</math> |} ===Big Matrix 64 by 65=== {{RoundBoxTop|theme=2}} [[File:0706matrix64_01.png|thumb|400px|'''Diagram of resistive network containing 64 resistors.''' </br> Positive current flow is assumed to be from bottom to top or from left to right. ]] A network containing 64 resistors is connected as shown in diagram. What is resistance R between points P1, P2? <syntaxhighlight lang=python> # python code values_of_R = ( R10, R11, R12, R13, R14, R15, R16, R17, R18, R19, R20, R21, R22, R23, R24, R25, R26, R27, R28, R29, R30, R31, R32, R33, R34, R35, R36, R37, R38, R39, R40, R41, R42, R43, R44, R45, R46, R47, R48, R49, R50, R51, R52, R53, R54, R55, R56, R57, R58, R59, R60, R61, R62, R63, R64, R65, R66, R67, R68, R69, R70, R71, R72, R73, ) = [ v for v in range (100,731,10) ] </syntaxhighlight> While this resistive circuit may be very theoretical, it lends itself well to the creation of a big matrix, 64 by 65, meaning that there are 64 resistors and 64 simultaneous equations to be solved. {{RoundBoxBottom}} ====Create matrix==== An examination of the circuit produces the following conditions: <syntaxhighlight lang=python> # python code iconditions = [ "+ i10 + i70 - i44" , "+ i11 - i10 - i49" , "+ i12 - i11 - i54", "+ i13 - i12 - i59" , "+ i14 - i13 - i64" , "+ i15 + i44 - i43", "+ i16 + i49 - i15 - i48 - i70" , "+ i17 + i54 - i16 - i53" , "+ i18 + i59 - i17 - i58", "+ i19 + i64 + i71 - i18 - i63" , "+ i69 - i19 - i68" , "+ i20 + i43 - i42", "+ i21 + i48 - i20 - i47" , "+ i22 + i53 - i21 - i52" , "+ i23 + i58 - i22 - i57", "+ i24 + i63 - i23 - i62" , "+ i68 - i24 - i67" , "+ i25 + i42 - i41", "+ i26 + i47 - i25 - i46" , "+ i27 + i52 - i26 - i51" , "+ i28 + i57 - i27 - i56", "+ i29 + i62 - i28 - i61" , "+ i67 - i29 - i66" , "+ i30 + i41 - i40", "+ i31 + i46 - i30 - i45 - i72" , "+ i32 + i51 - i31 - i50" , "+ i33 + i56 - i32 - i55", "+ i34 + i61 + i73 - i33 - i60" , "+ i66 - i34 - i65" , "+ i36 + i45 - i35", "+ i37 + i50 - i36" , "+ i38 + i55 - i37" , "+ i39 + i60 - i38", "+ i65 - i39 - i73" ] sx = 'len(iconditions)' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> len(iconditions) = 34 </syntaxhighlight> <syntaxhighlight lang=python> econditions = [ "+ e40 + e30 - e35 - e45" , "+ e41 + e25 - e30 - e46" , "+ e42 + e20 - e25 - e47", "+ e43 + e15 - e20 - e48" , "+ e44 + e10 - e15 - e49" , "+ e45 + e31 - e36 - e50", "+ e46 + e26 - e31 - e51" , "+ e47 + e21 - e26 - e52" , "+ e48 + e16 - e21 - e53", "+ e49 + e11 - e16 - e54" , "+ e50 + e32 - e37 - e55" , "+ e51 + e27 - e32 - e56", "+ e52 + e22 - e27 - e57" , "+ e53 + e17 - e22 - e58" , "+ e54 + e12 - e17 - e59", "+ e55 + e33 - e38 - e60" , "+ e56 + e28 - e33 - e61" , "+ e57 + e23 - e28 - e62", "+ e58 + e18 - e23 - e63" , "+ e59 + e13 - e18 - e64" , "+ e60 + e34 - e39 - e65", "+ e61 + e29 - e34 - e66" , "+ e62 + e24 - e29 - e67" , "+ e63 + e19 - e24 - e68", "+ e64 + e14 - e19 - e69" , "+ e44 + e70 - e15" , "+ e64 + e14 - e71", "+ e40 + e30 - e72" , "+ e60 + e73 - e39" ] sx = 'len(econditions)' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> len(econditions) = 29 </syntaxhighlight> In iconditions and econditions there are 63 conditions that include all values of i and e. These 63 conditions are used to create matrix. The 64th condition is added manually. The matrix is: <syntaxhighlight lang=python> matrix = [ [1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,], [-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,], [0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], 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[0,0,0,0,140,0,0,0,0,-190,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,640,0,0,0,0,-690,0,0,0,0,0,], [0,0,0,0,0,-150,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,440,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,700,0,0,0,0,], [0,0,0,0,140,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,640,0,0,0,0,0,0,-710,0,0,0,], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,300,0,0,0,0,0,0,0,0,0,400,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-720,0,0,], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-390,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,600,0,0,0,0,0,0,0,0,0,0,0,0,730,0,], [1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,], ] sx = 'len(matrix)' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> len(matrix) = 64 </syntaxhighlight> Bottom line of matrix is equivalent to: <math>(1)i10 + (-1) = 0</math> or <math>i10 = 1.</math> ====First result==== Calculate values_of_i : <syntaxhighlight lang=python> print ('\nWhen ints become huge:') values_of_i = solveMbyN (matrix) sx = 'values_of_i' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> When ints become huge: solveMbyN (input_, level = -41) : <class 'OverflowError'> OverflowError('int too large to convert to float') Length of input = 23 input_[0] = Error in this row. input_[1] = Error in this row. input_[2] = Error in this row. input_[3] = [-7.048390979785929e+176, 1.1003906499643917e+176, 1.5070856217200028e+174, 1.955699032422673e+173, ...... 0.0] input_[4] = [510.0, 0.0, 0.0, 0.0, 320.0, -1150.0, 270.0, 0.0, 0.0, 320.0, -590.0, 270.0, 0.0, 0.0, 320.0, -590.0, ...... 0.0] input_[5] = [0.0, 520.0, 0.0, 0.0, 0.0, 270.0, -1060.0, 220.0, 0.0, 0.0, 270.0, -490.0, 220.0, 0.0, 0.0, 270.0, ...... 0.0] input_[6] = [0.0, 0.0, 530.0, 0.0, 0.0, 0.0, 220.0, -970.0, 170.0, 0.0, 0.0, 220.0, -390.0, 170.0, 0.0, 0.0, 220.0, ...... 0.0] input_[7] = Error in this row. values_of_i = None </syntaxhighlight> <syntaxhighlight lang=python> print ('\nConvert input to floats:') matrix1 = [ list(v) for v in matrix ] matrix1[0][0] = float(matrix1[0][0]) values_of_i = solveMbyN (matrix1) sx = 'values_of_i' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> Convert input to floats: solveMbyN (input_, level = -40) : <class 'KeyError'> KeyError('Internal error. input[1][0] = nan, should be 0.') Length of input = 24 input_[0] = [-1.7360455505275518e+174, 1.4096781959571856e+174, -2.2007812999287836e+173, -3.014171243439967e+171, ...... 0.0] input_[1] = [-3.7974175914221006e+162, 3.309163202261842e+161, 2.4114748810711523e+162, -4.426635506031073e+161, ...... 0.0] input_[2] = [-2.4975968400753463e+139, 5.704494025143264e+138, -2.7146889822895123e+138, 1.4057733058789272e+139, ...... 0.0] input_[3] = [7.667237322891148e+182, -1.7692205437935546e+182, -2.341735229706114e+180, 4.1615580570562045e+181, ...... -0.0] input_[4] = [-500.0, 0.0, 0.0, 0.0, 0.0, 1240.0, -320.0, 0.0, 0.0, 0.0, 690.0, -320.0, 0.0, 0.0, 0.0, 690.0, -320.0, ...... 0.0] input_[5] = [0.0, 510.0, 0.0, 0.0, 0.0, 320.0, -1150.0, 270.0, 0.0, 0.0, 320.0, -590.0, 270.0, 0.0, 0.0, 320.0, -590.0, ...... 0.0] input_[6] = [0.0, 0.0, 520.0, 0.0, 0.0, 0.0, 270.0, -1060.0, 220.0, 0.0, 0.0, 270.0, -490.0, 220.0, 0.0, 0.0, 270.0, ...... 0.0] input_[7] = [0.0, 0.0, 0.0, 530.0, 0.0, 0.0, 0.0, 220.0, -970.0, 170.0, 0.0, 0.0, 220.0, -390.0, 170.0, 0.0, 0.0, ...... 0.0] values_of_i = None </syntaxhighlight> =====Success===== <syntaxhighlight lang=python> print ('\nSet global variable enable_reduceRow:') enable_reduceRow = 1 values_of_i = solveMbyN (matrix1) </syntaxhighlight> Success: <syntaxhighlight> Set global variable enable_reduceRow: i10 = 1.0000000000000049 ; i11 = 1.643236374952256 ; i12 = 2.316468657232291 ; i13 = 3.0507456069545116 i14 = 3.908085797412319 ; i15 = 0.5970301043016677 ; i16 = 0.8274774533758196; i17 = 1.225283946841065 i18 = 1.5617922630400025 ; i19 = 0.369273540611037 ; i20 = 0.3858385105885722; i21 = 0.6270001063825295 i22 = 0.7040607630623028 ; i23 = 0.6129764173251202 ; i24 = 0.298576896960036 ; i25 = 0.44960726241462035 i26 = 0.7812212615819403 ; i27 = 0.7165761045550649 ; i28 = 0.5186812635664733; i29 = 0.266770119423805 i30 = 0.5896680016803755 ; i31 = 1.475274068751303 ; i32 = 0.9632057010422588; i33 = 0.5801910619990465 i34 = 0.30799558703953794; i35 = 2.4693659910366916 ; i36 = 1.583773707944257 ; i37 = 1.0123878002551232 i38 = 0.6135963601029517 ; i39 = 0.3175434839291887 ; i40 = 2.7147355593758107; i41 = 2.125067557695435 i42 = 1.6754602952808149 ; i43 = 1.2896217846922426 ; i44 = 0.692591680390575 ; i45 = 0.8855922830924343 i46 = 1.7538676385971101 ; i47 = 1.4222536394297902 ; i48 = 1.181092043635833 ; i49 = 0.6432363749522512 i50 = 0.5713859076891339 ; i51 = 1.0834542753981782 ; i52 = 1.1480994324250535; i53 = 1.0710387757452802 i54 = 0.6732322822800348 ; i55 = 0.39879144015217155; i56 = 0.7818060791953839; i57 = 0.9797009201839757 i58 = 1.0707852659211583 ; i59 = 0.7342769497222208 ; i60 = 0.2960528761737631; i61 = 0.6419329634235106 i62 = 0.8938441075661789 ; i63 = 1.2082436279312632 ; i64 = 0.8573401904578074; i65 = 0.2438588716389498 i66 = 0.5518544586784879 ; i67 = 0.8186245781022927 ; i68 = 1.1172014750623287; i69 = 1.4864750156733657 i70 = -0.3074083196094299; i71 = 1.5434221599024214 ; i72 = 1.7538814225756034; i73 = -0.07368461229023889 # Notice that i70, i73 are negative. </syntaxhighlight> =====Check all conditions===== The following conditions are included for testing: <syntaxhighlight lang=python> more_econditions = [ "+ e49 + e70 - e10", "+ e19 + e69 - e71", "+ e35 + e45 - e72", "+ e65 + e73 - e34", ] extra_test_conditions = [ "+ e40 + e41 + e42 + e43 + e44 + e10 - e35 - e45 - e46 - e47 - e48 - e49", "+ e45 + e46 + e47 + e48 + e49 + e11 - e36 - e50 - e51 - e52 - e53 - e54", "+ e50 + e51 + e52 + e53 + e54 + e12 - e37 - e55 - e56 - e57 - e58 - e59", "+ e55 + e56 + e57 + e58 + e59 + e13 - e38 - e60 - e61 - e62 - e63 - e64", "+ e60 + e61 + e62 + e63 + e64 + e14 - e39 - e65 - e66 - e67 - e68 - e69", "+ e44 + e10 + e11 + e12 + e13 + e14 - e69 - e15 - e16 - e17 - e18 - e19", "+ e43 + e15 + e16 + e17 + e18 + e19 - e68 - e20 - e21 - e22 - e23 - e24", "+ e42 + e20 + e21 + e22 + e23 + e24 - e67 - e25 - e26 - e27 - e28 - e29", "+ e41 + e25 + e26 + e27 + e28 + e29 - e66 - e30 - e31 - e32 - e33 - e34", "+ e40 + e30 + e31 + e32 + e33 + e34 - e65 - e35 - e36 - e37 - e38 - e39", "+ i35 + i40 + i72 - i14 - i69 - i71", """+ e40 + e41 + e42 + e43 + e44 + e10 + e11 + e12 + e13 + e14 = e35 + e36 + e37 + e38 + e39 + e65 + e66 + e67 + e68 + e69""", """+ e40 + e41 + e42 + e43 + e15 + e16 + e17 + e18 + e19 + e69 = e35 + e36 + e37 + e38 + e60 + e61 + e62 + e63 + e64 + e14""", """+ e40 + e41 + e42 + e20 + e21 + e22 + e23 + e24 + e68 + e69 = e35 + e36 + e37 + e55 + e56 + e57 + e58 + e59 + e13 + e14""", """+ e40 + e41 + e25 + e26 + e27 + e28 + e29 + e67 + e68 + e69 = e35 + e36 + e50 + e51 + e52 + e53 + e54 + e12 + e13 + e14""", """+ e40 + e30 + e31 + e32 + e33 + e34 + e66 + e67 + e68 + e69 = e35 + e45 + e46 + e47 + e48 + e49 + e11 + e12 + e13 + e14""" ] </syntaxhighlight> Two Auxiliary Functions: <syntaxhighlight lang=python> def sum_zero (values, tolerance = None) : ''' This function calculates sum of all values in input. If sum is very close to zero, sum is returned as zero. For example: sum_zero((2, -1.99999999999999999999999)) is returned as 0. ''' if tolerance == None : tolerance = Tolerance sump = sumn = 0 for v in values : if v > 0 : sump += v elif v < 0 : sumn -= v max = (sumn, sump)[sump > sumn] sum = sump - sumn if abs(sum) < tolerance: return type(sum)(0) if abs(sum) < tolerance*max : return type(sum)(0) return sum def convert_str_to_tuple (input_str) : ''' input is str like "+ i35 + i40 + i72 - i14 - i69 - i71" or "+ i35 + i40 + i72 == i14 + i69 + i71" This function returns tuple : (i35, i40, i72, - i14, - i69, - i71) ''' str0 = ' '.join(input_str.split()) if '=' in str0 : if '==' in str0 : splitter = '==' else : splitter = '=' str1,str2 = str0.split(splitter) t1 = convert_str_to_tuple (str1) t2 = convert_str_to_tuple (str2) return t1 + tuple(-v for v in t2) str1 = ';+'.join(str0.split('+')) str2 = ';-'.join(str1.split('-')) str3 = ','.join([ v for v in str2.split(';') if v.strip() ]) return eval(str3 + ',') </syntaxhighlight> Check 83 conditions: <syntaxhighlight lang=python> all_conditions = (iconditions + econditions + more_econditions + extra_test_conditions) # Following string is executable python code. exc_str_64ei = """ ( i10, i11, i12, i13, i14, i15, i16, i17, i18, i19, i20, i21, i22, i23, i24, i25, i26, i27, i28, i29, i30, i31, i32, i33, i34, i35, i36, i37, i38, i39, i40, i41, i42, i43, i44, i45, i46, i47, i48, i49, i50, i51, i52, i53, i54, i55, i56, i57, i58, i59, i60, i61, i62, i63, i64, i65, i66, i67, i68, i69, i70, i71, i72, i73, ) = values_of_i values_of_e = [ i*R for i,R in zip ( values_of_i, values_of_R ) ] ( e10, e11, e12, e13, e14, e15, e16, e17, e18, e19, e20, e21, e22, e23, e24, e25, e26, e27, e28, e29, e30, e31, e32, e33, e34, e35, e36, e37, e38, e39, e40, e41, e42, e43, e44, e45, e46, e47, e48, e49, e50, e51, e52, e53, e54, e55, e56, e57, e58, e59, e60, e61, e62, e63, e64, e65, e66, e67, e68, e69, e70, e71, e72, e73, ) = values_of_e """ exec(exc_str_64ei) tolerance = 1e-15 count = errors = 0 for condition in all_conditions : t1 = convert_str_to_tuple (condition) sum = sum_zero(t1, tolerance) count += 1 if sum : sx = 'sum, condition' ; print (sx, '=', eval(sx)) errors += 1 print ('Number of tests =', count) print ('Number of errors =', errors) </syntaxhighlight> With tolerance of <math>1e-15</math> there are 21 errors: <syntaxhighlight> sum, condition = (1.2505552149377763e-12, '+ e48 + e16 - e21 - e53') sum, condition = (1.2505552149377763e-12, '+ e49 + e11 - e16 - e54') sum, condition = (7.958078640513122e-13, '+ e52 + e22 - e27 - e57') sum, condition = (1.1368683772161603e-12, '+ e53 + e17 - e22 - e58') sum, condition = (2.2737367544323206e-12, '+ e54 + e12 - e17 - e59') ...... ...... Number of tests = 83 Number of errors = 21 </syntaxhighlight> With tolerance of <math>1e-14</math> there are no errors. ====Calculate R==== =====matrix corrected===== {{RoundBoxTop|theme=2}} [[File:0710matrix64_01.png|thumb|400px|'''Diagram of network containing 64 resistors''' </br> Diagram has been corrected to show positive direction of current through R70, R73. ]] Original assumptions were that currrent flow through 64 resistors would be from bottom to top or from left to right. Examination of results shows that flow through R70, R73 is from right to left. Corrected diagram conforms to assumption that all current flow is from bottom towards top or from left to right. <syntaxhighlight lang=python> matrix1 = [ list(v) for v in matrix ] # Deep copy. # e70, i70 are at position 60 in each row of matrix1. # e73, i73 are at position 63 in each row of matrix1. for row in matrix1 : for p in (60,63) : if row[p] : row[p] *= -1 </syntaxhighlight> <code>matrix1</code> is corrected version of <code>matrix</code>. {{RoundBoxBottom}} =====Circuit parameters===== <syntaxhighlight> values_of_circuit_current = ('i40 + i72 + i35', 'i14 + i71 + i69') values_of_circuit_voltage = ( 'e72 + e46 + e47 + e48 + e70 + e10 + e11 + e12 + e13 + e14', 'e35 + e36 + e37 + e38 + e39 + e73 + e61 + e62 + e63 + e71', 'e40 + e41 + e42 + e43 + e44 + e10 + e11 + e12 + e13 + e14', 'e35 + e36 + e37 + e38 + e39 + e65 + e66 + e67 + e68 + e69', 'e40 + e41 + e42 + e43 + e15 + e16 + e17 + e18 + e19 + e69', 'e40 + e41 + e42 + e20 + e21 + e22 + e23 + e24 + e68 + e69', 'e40 + e41 + e25 + e26 + e27 + e28 + e29 + e67 + e68 + e69', 'e40 + e30 + e31 + e32 + e33 + e34 + e66 + e67 + e68 + e69', 'e35 + e45 + e46 + e47 + e48 + e49 + e11 + e12 + e13 + e14', 'e35 + e36 + e50 + e51 + e52 + e53 + e54 + e12 + e13 + e14', 'e35 + e36 + e37 + e55 + e56 + e57 + e58 + e59 + e13 + e14', 'e35 + e36 + e37 + e38 + e60 + e61 + e62 + e63 + e64 + e14', 'e72 + e31 - e50 + e37 + e38 + e39 + e73 + e61 - e28 + e57' + ( '- e22 + e53 - e16 + e70 + e10 + e11 + e12 + e13 + e14') ) </syntaxhighlight> =====Using floating point numbers:===== <syntaxhighlight lang=python> # python code: number_of_columns = 65 one = 1 ; Tolerance = 1e-14 # Following string is executable python code: exc_str1 = """ Values_of_R = [] for I in range(10, 74): new_line = [ 0 ] * number_of_columns place_in_line = I - 10 new_line[place_in_line] = one i = (I)/10 new_line[-1] = -i matrix1[-1] = new_line values_of_i = solveMbyN (matrix1) exec(exc_str_64ei) for Istr in values_of_circuit_current : I = eval(Istr) for Estr in values_of_circuit_voltage : E = eval(Estr) ; R = E/I ; Values_of_R += [R] print ('Number of calculations =', len(Values_of_R)) tmp = sorted(Values_of_R) minR = tmp[0] ; maxR = tmp[-1] s1 = 'minR' ; print(s1,'=',eval(s1)) s1 = 'maxR' ; print(s1,'=',eval(s1)) sum = sum_zero((minR, -maxR)) s1 = 'sum' ; print(s1,'=',eval(s1)) if not sum : print ('With Tolerance of {}, both minR and maxR are equal.'.format(Tolerance)) """ exec(exc_str1) </syntaxhighlight> <syntaxhighlight> Number of calculations = 1664 minR = 723.9285759884408 maxR = 723.9285759884439 sum = 0.0 With Tolerance of 1e-14, both minR and maxR are equal. </syntaxhighlight> This code produced 1664 values of R from minR through maxR, both included. With tolerance of <math>1e-14</math> all values of resistance R = 723.92857598844. =====Using Decimal numbers:===== With <code>enable_reduceRow</code> clear : <syntaxhighlight lang=python> enable_reduceRow = 0 Precision = dgt.prec = 60 Tolerance = dD('1e-' + str(Precision-3)) one = dD(1) try : exec(exc_str1) except : pass </syntaxhighlight> <syntaxhighlight> solveMbyN (input_, level = -52) : <class 'decimal.Overflow'> Overflow([<class 'decimal.Overflow'>]) Length of input = 12 input_[0] = [-inf, inf, -inf, inf, inf, -inf, inf, -inf, inf, -inf, -inf, inf, 0.0] input_[1] = [inf, -inf, -inf, -inf, -inf, inf, -inf, -inf, -inf, -inf, inf, -inf, 0.0] input_[2] = [-inf, inf, inf, inf, -inf, -inf, inf, inf, -inf, inf, inf, inf, 0.0] input_[3] = [inf, -inf, -inf, inf, -inf, inf, -inf, -inf, inf, -inf, -inf, inf, 0.0] input_[4] = [620.0, 0.0, 0.0, 0.0, 290.0, -1200.0, 240.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] input_[5] = [0.0, 630.0, 0.0, 0.0, 0.0, 240.0, -1110.0, 190.0, 0.0, 0.0, 0.0, 0.0, 0.0] input_[6] = [inf, -inf, inf, -inf, -inf, inf, -inf, -inf, inf, -inf, inf, -inf, 0.0] input_[7] = [-inf, inf, inf, inf, inf, -inf, inf, inf, inf, inf, -inf, inf, 0.0] </syntaxhighlight> With <code>enable_reduceRow</code> set : <syntaxhighlight lang=python> enable_reduceRow = 1 exec(exc_str1) </syntaxhighlight> <syntaxhighlight> Number of calculations = 1664 minR = 723.928575988442547699732563335265663515838075102937503680560 maxR = 723.928575988442547699732563335265663515838075102937503680663 sum = 0 With Tolerance of 1E-57, both minR and maxR are equal. </syntaxhighlight> With tolerance of <math>1e-57</math> all values of resistance R = 723.928575988442547699732563335265663515838075102937503681. [[Category:Equations]] ejwn07ka2hoe5l9igsn18ej2p5ymx39 14 273009 2835216 2834177 2026-09-30T17:40:31Z DavidMCEddy 218607 /* Table of episodes */ fix KKFI date 2835216 wikitext text/x-wiki A number of seemingly credible sources are describing an increase in political polarization worldwide. [[w:Maria Ressa|Maria Ressa]] describes how [[w:Rodrigo Duterte|Rodrigo Duterte]], former President of the [[w:Philippines|Philippines]] "started ... with five hundred volunteers<ref>Ressa (2022, pp. 147-8).</ref> (1) creating “sock puppets,” or fake accounts that attack or praise; (2) “mass reporting,” or organizing to negatively impact a targeted account; and (3) “astroturfing,” or fake posts or lies designed to look like grassroots support or interest.<ref>Ressa (2022, pp. 152-3).</ref> These actions tricked the algorithms of social media companies like Facebook and Twitter into amplifying fraudulent messages including incitements to violence and criminal prosecutions based on trumped up charges. The results easily overwhelmed honest media. [[w:Leila de Lima|Leila de Lima]], a Senator and former Secretary of Justice of the Philippines, spent years in pretrial detention before the charges were dropped for lack of evidence.<ref>Ressa (2022, p. 158ff) and Wikipedia, "[[w:Leila de Lima|Leila de Lima]]", accessed 2024-07-22.</ref> Ressa's news organization, [[w:Rappler|Rappler]].com, was ordered to close. Ressa herself was convicted on questionable charges. Both continued operating while the legal procedures against them were appealed.<ref>Ressa (2022, pp. 152-3) and Wikipedia, "[[w:Maria Ressa|Maria Ressa]]", accessed 2024-07-22.</ref> Ressa says similar procedures are making major contributions to the rise of fascism and far-right nationalist populists in the US, Europe, Turkey, India, Russia, and elsewhere.<ref>Ressa (2022, pp. 152-3).</ref> [[w:H. R. McMaster|H. R. McMaster]], former President Trump's second National Security advisor, said that "The internet and social media thus provided [Russia] with a low-cost, easy way to divide and weaken America from within."<ref>McMaster (2020, pp. 47-48).</ref> The [[w:2021 Facebook leak|2021 Facebook leak]] documented how executives of [[w:Facebook|Facebook]] and [[w:Meta Platforms|Meta]] knowingly prioritized profits over action to limit incitements to violence, even facilitating the [[w:Rohingya genocide|Rohingya genocide]] in [[w:Myanmar|Myanmar]], because doing otherwise would have reduced their profits. This "Category:Media reform to improve democracy" include videos of experts and activists working this issue along with 29:00 mm:ss audio files submitted to a ''Media & Democracy'' series syndicated on the [[w:List of Pacifica Radio stations and affiliates|Pacifica radio network]]<ref><!--Media & Democracy on Audioport-->{{cite Q|Q127839818}}</ref> plus text and space for moderated discussions. Some of this work is cited in the book on ''[[Media Literacy and You]]'', which is being written -- [[w:Crowdsourcing|crowdsourced]] -- to help humans better understand how they can counter the trend toward increasing political polarization and violence by talking politics, calmly, with respect and humility, with others with whom they may vehemently disagree, because the alternative is killing humans over misunderstanding. The goal is ''not'' to convince anyone that they are wrong. Rather it is to build relationships where humans can agree to disagree agreeably and collaborate to improve issues of common concern. == Table of episodes == {| class="wikitable sortable" |+ Episodes of "Media & Democracy" for the [[w:List of Pacifica Radio stations and affiliates|Pacifica Radio Network]] |- ! !! colspan=3 | Date !! colspan=2 | Guest(s) !! !! |- ! no. || recorded !! broadcasted on [[w:KKFI|KKFI]] !! released to Pacifica !! given name !! surname !! Organization(s) !!Episode |- | 62 || 2026-09-18 || 2026-10-06 || 2026-10-17 || Rainey || Reitman<ref><!--Rainey Reitman-->{{cite Q|Q28778243}}</ref> || [[w:Freedom of the Press Foundation|Freedom of the Press Foundation]] || [[Rainey Reitman on how finance companies punish speech]] |- | 61 || 2026-09-03 || 2026-09-22 || 2026-10-03 || [[w:Nolan Higdon|Nolan]] || [[w:Nolan Higdon|Higdon]] || [[w:California State University, East Bay|California State University, East Bay]] & [[w:University of California, Santa Cruz|University of California, Santa Cruz]] || [[Media literacy and why you should care]] |- | 60 || 2026-08-31 || 2026-09-08 || 2026-09-19 || Rachel || Clark<ref><!--Rachel Clark-->{{cite Q|Q141168609}}</ref> || [[w:Veterans for Peace|Veterans for Peace]] || [[The impact of news media on the Japanese political economy]] |- | 59 || 2026-08-27 || 2026-09-01 || 2026-09-05 || [[w:Renée DiResta|Renée]] || [[w:Renée DiResta|DiResta]] || [[w:Georgetown University|Georgetown University]] || [[Managing the good and the evils of social media]] |- | 58 || 2026-08-13 || 2026-08-18 || 2026-08-22 || {| | Teresa |- | Ann |} | {| | Wilke<ref><!--Teresa Wilke-->{{cite Q|Q141110943}}</ref> |- | Suellentrop<ref><!--Ann Suellentrop-->{{cite Q|Q104978249}}</ref> |} | {| | [[w:KKFI|KKFI]] |- | PeaceWorks Kansas City,<ref><!-- PeaceWorks Kansas City-->{{cite Q|Q64287449}}</ref> ... |} | [[How to expose media lies and have fun doing it]] |- | 57 || 2026-07-31 || 2026-08-11 || 2026-08-08 || Yonty || Friesem<ref><!--Yonty Friesem-->{{cite Q|Q140685186}}</ref> || Media Education Lab,<ref><!--Media Education Lab-->{{cite Q|Q140686986}}</ref> || [[Yonty Friesem on media education]] |- | 56 || 2026-07-01 || 2026-07-21 || 2026-07-25 || Dimitar || Zagorski<ref><!--Dimitar Zagorski, 3rd-->{{cite Q|Q130719781}}</ref> || [[w:Wikimedia Foundation|Wikimedia Foundation]] || [[Wikimedia concerns with European copyright rules including AI and scientific research]] |- | 55 || 2026-07-02 || 2026-07-14 || 2026-07-11 || [[w:Robert Corn-Revere|Robert]] || [[w:Robert Corn-Revere|Corn-Revere]] || [[w:Foundation for Individual Rights and Expression|Foundation for Individual Rights and Expression]] (FIRE) || [[Foundation for Individual Rights and Expression]] |- | 54 || 2026-06-20 || 2026-06-23 || 2026-06-27 || Katerina || Canyon<ref><!--Katerina Canyon-->{{cite Q|Q140290658}}</ref> || Peace Economy Project,<ref><!--Peace Economy Project-->{{cite Q|Q140290765}}</ref> || [[Peace Economy Project]] |- | 53 || 2026-05-29 || 2026-06-09 || 2026-06-13 || [[w:Nolan Higdon|Nolan]] || [[w:Nolan Higdon|Higdon]] || [[w:California State University, East Bay|California State University, East Bay]] & [[w:University of California, Santa Cruz|University of California, Santa Cruz]] || [[Let's agree to disagree and seek common ground]] |- | 52 || 2026-05-14 || 2026-05-26 ||2026-05-30 || Allison || Butler<ref><!--Allison Butler-->{{cite Q|Q132918386}}</ref> || [[w:University of Massachusetts Amherst|University of Massachusetts Amherst]] || [[How women are centered and silenced in the major media]] |- | 51 || 2026-05-06 || 2026-05-12 || 2026-05-16 || [[w:Yael Eisenstat|Yaël]] || [[w:Yael Eisenstat|Eisenstat]] || Cybersecurity for Democracy (C4D),<ref><!--Cybersecurity for Democracy-->{{cite Q|Q139568543}}</ref> || [[Online platforms' effects on public health, safety and democracy]] |- | 50 || 2026-04-09 || 2026-04-28 || 2026-05-02 || Stephen || Bezruchka<ref name=Bezruchka><!--Stephen Bezruchka-->{{cite Q|Q118236581}}</ref> || [[w:University of Washington School of Public Health|University of Washington School of Public Health]] || [[How US media threaten the health of all]] |- | 49 || 2026-04-06 || 2026-04-14 || 2026-04-18 || Mickey ||Huff<ref><!--Mickey Huff-->{{cite Q|Q104530435}}</ref> || [[w:Project Censored|Project Censored]] & [[w:Ithaca College|Ithaca College]] || [[News suppressed for those who control money for the media]] |- | 48 || 2026-03-27 || 2026-03-31 || 2026-04-04 || [[w:Robin Andersen|Robin]] || [[w:Robin Andersen|Andersen]] || [[w:Fordham University|Fordham University]] || [[Media and war]] |- | 47 || 2026-03-12 || 2026-03-17 || 2026-03-21 || Bill || Yousman<ref><!--Bill Yousman-->{{cite Q|Q138604097}}</ref> || [[w:Sacred Heart University|Sacred Heart University]] || [[Media literacy to dispel myths and improve public policy]] |- | 46 || 2026-02-26 || 2026-03-03 || 2026-03-07 || Stephan || Russ-Mohl<ref><!--Stephan Russ-Mohl-->{{cite Q|Q2343781}}</ref> || [[w:University of Lugano|University of Lugano]] || [[Concerns about media, especially in Germany]] |- | 45 || 2026-02-12 || 2026-02-17 || 2026-02-21 || Paul || Bame<ref><!--Paul Bame-->{{cite Q|Q138057986}}</ref> || [[w:Prometheus Radio Project|Prometheus Radio Project]] || [[Underserved serve themselves with low-power FM]] |- | 44 || 2026-01-30 || 2026-02-03 || 2026-02-07 || Anthony || Nadler<ref><!--Anthony Nadler-->{{cite Q|Q135514734}}</ref> || [[w:Ursinus College|Ursinus College]] || [[Conservative media are different]] |- | 43 || 2026-01-15 || 2026-01-20 || 2026-01-24 || {| | Tim |- | Zach |} | {| | Franklin<ref><!-- Tim Franklin-->{{cite Q|Q137763244}}</ref> |- | Metzger<ref><!--Zach Metzger-->{{cite Q|Q137803164}}</ref> |} | [[w:Northwestern University|Northwestern University]] || [[Medill says you can help yourself by helping improve local media]] |- | 42 || 2026-01-03 || 2026-01-06 || 2026-01-10 || Lisa || Loving<ref>{{cite Q|Q65115420}}</ref> || [[w:KBOO|KBOO]] || [[Lisa Loving on media literacy and how you can report for your community]] |- | 41 || 2015-12-11 || 2025-12-23 || 2025-12-27 || [[w:John Maxwell Hamilton|John Maxwell]] || [[w:John Maxwell Hamilton|Hamilton]] || [[w:Louisiana State University|Louisiana State University]] || [[John Maxwell Hamilton on American propaganda]] |- | 40 || 2025-12-05 || 2025-12-09 || 2025-12-13 || Mark || Hurst<ref><!--Mark Hurst-->{{cite Q|Q65030170}}</ref> || Techtonic<ref><!--Techtonic-->{{cite Q|Q137087746}}</ref> || [[You can better protect yourself from Big Tech]] |- | 39 || 2025-11-20 || 2025-11-25 || 2025-11-29 || Kareem || El Damanhoury<ref><!--Kareem El Damanhoury-->{{cite Q|Q113752441}}</ref> || [[w:University of Denver|University of Denver]] || [[Differences between media outlets including coverage of Gaza]] |- | 38 || 2025-11-06 || 2025-11-11 || 2025-11-15 || Spencer || Graves<ref><!--Spencer Graves-->{{cite Q|Q56452480}}</ref> || [[w:KKFI|KKFI]] || [[Media & Democracy lessons for the future]] |- | 37 || 2025-10-23 || 2025-20-28 || 2025-11-01 || [[w:Kwame Karikari (journalist)|Kwame ]] || [[w:Kwame Karikari (journalist)|Karikari]] || [[w:Media Foundation for West Africa|Media Foundation for West Africa (MFWA)]] || [[Media reform initiatives in West Africa]] |- | 36 || 2025-10-03 || 2025-10-14 || 2025-10-18 || Seth || Radwell<ref name=Radwell><!--Seth David Radwell-->{{cite Q|Q136406332}}</ref> || || [[Seth Radwell says that the two Enlightenments tell us how to heal US political polarization]] |- | 35 || 2025-09-25 || 2025-09-30 || 2025-10-04 || Dan || Hind<ref><!--Dan Hind-->{{cite Q|Q136393606}}</ref> || Media Reform Coalition (MRC).<ref><!--Media Reform Coalition-->{{cite Q|Q135440829}}</ref> || [[Media Reform Coalition challenges anti-democratic media bias in the UK]] |- | 34 || 2025-09-12 || 2025-09-16 || 2025-09-20 || [[w:Anna M. Gomez|Anna]] || [[w:Anna M. Gomez|Gomez]] || [[w:Federal Communications Commission|Federal Communications Commission]] || [[Fighting back against the campaign of censorship and control]] |- | 33 || 2025-08-28 || 2025-09-02 || 2025-09-06 || Doug || Samuelson<ref name=Samuelson><!--Douglas A. Samuelson-->{{cite Q|Q89781201}}</ref> || [[w:Trevor N. Dupuy#Academic and research career|Dupuy Institute]]<ref name=Dupuy><!--Dupuy Institute-->{{cite Q|Q135969462}}</ref> || [[The role of the media in conflict]] |- | 32 || 2025-07-31 || 2025-08-19 || 2025-08-21 || Nick || Hart<ref><!--Nick Hart-->{{cite Q|Q135663983}}</ref> || Data Foundation<ref><!--Data Foundation-->{{cite Q|Q134705118}}</ref> || [[Evidence-informed public policy]] |- | 31 || 2025-08-01 || 2025-08-05 || 2025-08-09 || Reece || Peck<ref><!--Reece Peck-->{{cite Q|Q131374387}}</ref> || [[w:City University of New York|City University of New York (CUNY)]] || [[What the Left can learn from Fox]] |- | 30 || 2025-07-17 || 2025-07-22 || 2025-07-26 || Natalie || Fenton<ref><!--Natalie Fenton-->{{cite Q|Q112529317}}</ref> || [[w:Goldsmiths, University of London|Goldsmiths, University of London]] || [[Democratic delusions: Fix the media to fix democracy]] |- | 29 || 2025-07-03 || 2025-07-08 || 2025-07-12 || Heidi J.S. || Tworek<ref><!--Heidi J.S. Tworek-->{{cite Q|Q135116400}}</ref> || [[w:University of British Columbia|University of British Columbia]] || [[News from Germany 1900-1945 and implications for today]] |- | 28 || 2025-06-12 || 2025-06-24 || 2025-06-28 || Nik || Usher<ref name=Usher><!--Nik Usher-->{{cite Q|Q134715348}}</ref> || [[w:University of San Diego|University of San Diego]] || [[How news impacts democracy per USD Communications Professor Nik Usher]] |- | 27 || 2025-06-08 || 2025-06-10 || 2025-06-14 || [[w:Richard R. John|Richard R.]] || [[w:Richard R. John|John]] || [[w:Columbia University|Columbia University]] || [[Media concentration per Columbia History Professor Richard John]] |- | 26 || 2025-05-21 || 2025-05-27 || 2025-05-31 || Dean || Starkman<ref><!--Dean Starkman-->{{cite Q|Q17036928}}</ref> || [[w:International Consortium of Investigative Journalists|International Consortium of Investigative Journalists]] (ICIJ) || [[Dean Starkman and the watchdog that didn't bark]] |- | 25 || 2025-05-08 || 2025-05-13 || 2025-05-17 || {| | Seth |- | Lauren |} | {| | Stern<ref><!--Seth Stern-->{{cite Q|Q134333839}}</ref> |- | Harper<ref><!--Lauren Harper-->{{cite Q|Q134371468}}</ref> |} | [[w:Freedom of the Press Foundation|Freedom of the Press Foundation]] || [[Freedom of the Press Foundation says...]] |- | 24 || 2025-04-24 || 2025-04-29 || 2025-05-03 || Marc || Edge<ref><!--Marc Edge-->{{cite Q|Q127419557}}</ref> || || [[Canadian journalist Marc Edge on media reform to improve democracy]] |- | 23 || 2025-04-10 || 2025-04-15 || 2025-04-19 || Katie || Moylan<ref><!--Katie Moylan-->{{cite Q|Q133832220}}</ref> || [[w:University of Leicester|University of Leicester]] || [[The value of indigenous and community radio]] |- | 22 || 2025-03-28 || 2025-04-01 || 2025-04-05 || Amy || O’Hara<ref><!--Amy O'Hara-->{{cite Q|Q133554516}}</ref> || [[w:Georgetown University|Georgetown University]] & Association of Public Data Users (APDU),<ref><!--APDU-->{{cite Q|Q131542415}}</ref> || [[Trump ordered changes in public data]] |- | 21 || 2025-03-06 || 2025-03-11 || 2025-03-22 || Rick || Goldsmith,<ref><!--Rick Goldsmith-->{{cite Q|Q1792246}}</ref> || || [[Vulture capitalists destroying newspapers]] |- | 20 || 2025-02-25 || 2025-02-25 || 2025-03-08 || Roger M. || White<ref><!--Roger M. White-->{{cite Q|Q132460597}}</ref> || [[w:Arizona State University|Arizona State University]] || [[Local newspapers limit malfeasance]] |- | 19 || 2025-02-06 || 2025-02-11 || 2025-02-22 || [[w:Greg Palast|Greg]] || [[w:Greg Palast|Palast]] || || [[Palast says Trump lost, vote suppression won the 2024 elections]] |- | 18 || 2025-01-25 || 2025-02-04 || 2025-02-12 || {| | Omali |- | Elisa |- | Gerald |} | {| | Yeshitela |- | Mejia |- | Horne |} | Friends of Community Media,<ref><!--Friends of Community Media-->{{cite Q|Q100167560}}</ref>, Pacifica Fightback,<ref><!--Pacifica Fightback-->{{cite Q|Q132035380}}</ref>, ... || [[Defend free speech hybrid town hall]] |- | 17 || 2025-01-13 || 2025-01-14 || 2025-01-25 || Bulgarova || Bella Akhmedovna<ref><!--Bulgarova Bella Akhmedovna-->{{cite Q|Q131737349}}</ref> || [[w:Patrice Lumumba Peoples' Friendship University of Russia|Patrice Lumumba Peoples' Friendship University of Russia]] || [[Media in the Syrian conflict]] |- | 16 || 2024-12-20 || 2024-12-31 || 2025-01-04 || Michael || Novick || || [[HR 9495, the nonprofit-killer bill, per Michael Novick]] |- | 15 || 2024-12-13 || 2024-12-24 || 2024-12-21 || [[w:Victor Pickard (professor)|Victor]] || [[w:Victor Pickard (professor)|Pickard]] || [[w:Annenberg School for Communication at the University of Pennsylvania|Annenberg School for Communication at the University of Pennsylvania]] || [[Information is a public good per communications prof Pickard]] |- | 14 || 2024-12-02 || 2024-12-10 || 2024-12-07 || Ahmed || Al-Rawi<ref name=AlRawiSFU><!--SFU homepage of Ahmed Al-Rawi-->{{cite Q|Q131349551}}</ref> || [[w:Simon Fraser University|Simon Fraser University]] || [[Media literacy for the Arab World per Ahmed Al-Rawi]] |- | 13 || 2024-11-21 || 2024-11-26 || 2024-11-23 || [[w:Thom Hartmann|Thom]] || [[w:Thom Hartmann|Hartmann]] || || [[Thom Hartmann on The Hidden History of the American Dream]] |- | 12 || 2024-10-25 || 2024-11-05 || 2024-11-09 || Dimi || Dimitrov.<ref><!-- Dimi Dimitrov-->{{cite Q|Q130719781}}</ref> || [[meta:Wikimedia Europe|Wikimedia Europe]] || [[Legal concerns of Wikimedia Europe]] |- | 11 || 2024-10-26 || 2024-10-19 || 2024-10-27 || Karl || Brooks<ref name=Brooks><!--Karl Boyd Brooks-->{{cite Q|Q128214400}}</ref> || [[w:University of Kansas|University of Kansas]] || [[Project 2025 per Professor Brooks]] |- | 10 || 2024-10-01 || 2024-10-01 || 2024-10-12 || Jacob || Ware<ref><!--Jacob Ware-->{{cite Q|Q130315296}}</ref> || [[w:Council on Foreign Relations|Council on Foreign Relations]] (CFR) & [[w:Georgetown University|Georgetown University]] || [[Jacob Ware on far-right terrorism in the US]] |- | 9 || 2024-09-13 || 2024-09-17 || 2024-09-29 || Patricia Weems || Gaston.<ref name=Gaston><!--Patricia Weems Gaston-->{{cite Q|Q130215888}}</ref> || [[w:University of Kansas|University of Kansas]] || [[Dis- and misinformation and their threats to democracy]] |- | 8 || 2024-09-11 || 2024-11-12 || 2024-09-14 || Jiva || Manske<ref><!--Jiva Manske-->{{cite Q|Q130287696}}</ref> || 22nd Century Initiative<ref><!--22nd CI-->{{cite Q|Q129361855}}</ref> || [[22nd Century Initiative]] |- | 7 || 2024-08-22|| 2024-08-27 || 2024-08-31 || Heidi || Beirich,<ref><!-- Heidi Beirich-->{{cite Q|Q128844587}}</ref> || Global Project Against Hate & Extremism (GPAHE).<ref><!-- GPAHE-->{{cite Q|Q125952435}}</ref> || [[Global Project Against Hate & Extremism (GPAHE)]] |- | 6 || 2024-08-19 || 2024-08-20 || 2024-08-24 || [[w:Frances Haugen|Frances]] || [[w:Frances Haugen|Haugen]] || || [[Facebook whistleblower Frances Haugen says]] |- | 5 || 2024-08-13 || 2024-08-13 || 2024-08-17 || Matt || Wood<ref><!--Matt Wood-->{{cite Q|Q128630750}}</ref> || [[w:Free Press (advocacy group)|Free Press]] || [[Legal concerns of Free Press including Section 230]] |- | 4 || 2024-08-02 || 2024-08-06 || 2024-08-10 || Ian Axel || Anderson<ref><!--Ian Axel Anderson-->{{cite Q|Q128639294}}</ref> || [[w:California Institute of Technology|Caltech]] || [[How psychological and interpersonal processes are influenced by human-computer interactions]] |- | 3 || 2024-07-30 || 2024-07-30 || 2024-08-03 || [[w:Dean Baker|Dean]] || [[w:Dean Baker|Baker]] || [[w:Center for Economic and Policy Research|Center for Economic and Policy Research]] || [[Dean Baker on Internet companies threatening democracy internationally and how to fix that]] |- | 2 || 2021-04-29 || 2021-04-29 || 2021-05-16 || Craig || Aaron,<ref>{{cite Q|Q104624986}}<!-- Craig Aaron --></ref> || [[w:Free Press (organization)|Free Press (Freepress.net)]] || [[Media reform per Freepress.net]] |- | 1 || 2021-02-23 || 2021-02-23 || 2021-03-17 || [[w:Dean Baker|Dean]] || [[w:Dean Baker|Baker]] || [[w:Center for Economic and Policy Research|Center for Economic and Policy Research]] ||[[Unrigging the media and the economy]] |} == Notes == {{reflist}} == Bibliography == * <!-- H. R. McMaster (2020) Battlegrounds: The Fight to Defend the Free World-->{{cite Q|Q104774898}} * <!--Maria Ressa (2022) How to Stand Up To a Dictator-->{{cite Q|Q117559286}} [[Category:Interdisciplinary studies]] [[Category:Political science]] [[Category:Economics]] [[Category:Freedom and abundance]] [[Category:Videoconferences on media and democracy]] 94m1kc9m0r90xkaac2yiqvf6zb1ymfi 0 285380 2835160 2834152 2026-09-30T12:38:46Z Young1lim 21186 /* Applications */ 2835160 wikitext text/x-wiki === Introduction === * Overview ([[Media:C01.Intro1.Overview.1.A.20170925.pdf |A.pdf]], [[Media:C01.Intro1.Overview.1.B.20170901.pdf |B.pdf]], [[Media:C01.Intro1.Overview.1.C.20170904.pdf |C.pdf]]) * Number System ([[Media:C01.Intro2.Number.1.A.20171023.pdf |A.pdf]], [[Media:C01.Intro2.Number.1.B.20170909.pdf |B.pdf]], [[Media:C01.Intro2.Number.1.C.20170914.pdf |C.pdf]]) * Memory System ([[Media:C01.Intro2.Memory.1.A.20170907.pdf |A.pdf]], [[Media:C01.Intro3.Memory.1.B.20170909.pdf |B.pdf]], [[Media:C01.Intro3.Memory.1.C.20170914.pdf |C.pdf]]) === Handling Repetition === * Control ([[Media:C02.Repeat1.Control.1.A.20170925.pdf |A.pdf]], [[Media:C02.Repeat1.Control.1.B.20170918.pdf |B.pdf]], [[Media:C02.Repeat1.Control.1.C.20170926.pdf |C.pdf]]) * Loop ([[Media:C02.Repeat2.Loop.1.A.20170925.pdf |A.pdf]], [[Media:C02.Repeat2.Loop.1.B.20170918.pdf |B.pdf]]) === Handling a Big Work === * Function Overview ([[Media:C03.Func1.Overview.1.A.20171030.pdf |A.pdf]], [[Media:C03.Func1.Oerview.1.B.20161022.pdf |B.pdf]]) * Functions & Variables ([[Media:C03.Func2.Variable.1.A.20161222.pdf |A.pdf]], [[Media:C03.Func2.Variable.1.B.20161222.pdf |B.pdf]]) * Functions & Pointers ([[Media:C03.Func3.Pointer.1.A.20161122.pdf |A.pdf]], [[Media:C03.Func3.Pointer.1.B.20161122.pdf |B.pdf]]) * Functions & Recursions ([[Media:C03.Func4.Recursion.1.A.20161214.pdf |A.pdf]], [[Media:C03.Func4.Recursion.1.B.20161214.pdf |B.pdf]]) === Handling Series of Data === ==== Background ==== * Background ([[Media:C04.Series0.Background.1.A.20180727.pdf |A.pdf]]) ==== Basics ==== * Pointers ([[Media:C04.S1.Pointer.1A.20240524.pdf |A.pdf]], [[Media:C04.Series2.Pointer.1.B.20161115.pdf |B.pdf]]) * Arrays ([[Media:C04.S2.Array.1A.20240514.pdf |A.pdf]], [[Media:C04.Series1.Array.1.B.20161115.pdf |B.pdf]]) * Array Pointers ([[Media:C04.S3.ArrayPointer.1A.20240208.pdf |A.pdf]], [[Media:C04.Series3.ArrayPointer.1.B.20181203.pdf |B.pdf]]) * Multi-dimensional Arrays ([[Media:C04.Series4.MultiDim.1.A.20221130.pdf |A.pdf]], [[Media:C04.Series4.MultiDim.1.B.1111.pdf |B.pdf]]) * Array Access Methods ([[Media:C04.Series4.ArrayAccess.1.A.20190511.pdf |A.pdf]], [[Media:C04.Series3.ArrayPointer.1.B.20181203.pdf |B.pdf]]) * Structures ([[Media:C04.Series3.Structure.1.A.20171204.pdf |A.pdf]], [[Media:C04.Series2.Structure.1.B.20161130.pdf |B.pdf]]) ==== Examples ==== * Spreadsheet Example Programs :: Example 1 ([[Media:C04.Series7.Example.1.A.20171213.pdf |A.pdf]], [[Media:C04.Series7.Example.1.C.20171213.pdf |C.pdf]]) :: Example 2 ([[Media:C04.Series7.Example.2.A.20171213.pdf |A.pdf]], [[Media:C04.Series7.Example.2.C.20171213.pdf |C.pdf]]) :: Example 3 ([[Media:C04.Series7.Example.3.A.20171213.pdf |A.pdf]], [[Media:C04.Series7.Example.3.C.20171213.pdf |C.pdf]]) :: Bubble Sort ([[Media:C04.Series7.BubbleSort.1.A.20171211.pdf |A.pdf]]) ==== Applications ==== * Address-of and de-reference operators ([[Media:C04.SA0.PtrOperator.1A.20260928.pdf |A.pdf]]) * Applications of Pointers ([[Media:C04.SA1.AppPointer.1A.20241121.pdf |A.pdf]]) * Applications of Arrays ([[Media:C04.SA2.AppArray.1A.20240715.pdf |A.pdf]]) * Applications of Array Pointers ([[Media:C04.SA3.AppArrayPointer.1A.20240210.pdf |A.pdf]]) * Applications of Multi-dimensional Arrays ([[Media:C04.Series4App.MultiDim.1.A.20210719.pdf |A.pdf]]) * Applications of Array Access Methods ([[Media:C04.Series9.AppArrAcess.1.A.20190511.pdf |A.pdf]]) * Applications of Structures ([[Media:C04.Series6.AppStruct.1.A.20190423.pdf |A.pdf]]) === Handling Various Kinds of Data === * Types ([[Media:C05.Data1.Type.1.A.20180217.pdf |A.pdf]], [[Media:C05.Data1.Type.1.B.20161212.pdf |B.pdf]]) * Typecasts ([[Media:C05.Data2.TypeCast.1.A.20180217.pdf |A.pdf]], [[Media:C05.Data2.TypeCast.1.B.20161216.pdf |A.pdf]]) * Operators ([[Media:C05.Data3.Operators.1.A.20161219.pdf |A.pdf]], [[Media:C05.Data3.Operators.1.B.20161216.pdf |B.pdf]]) * Files ([[Media:C05.Data4.File.1.A.20161124.pdf |A.pdf]], [[Media:C05.Data4.File.1.B.20161212.pdf |B.pdf]]) === Handling Low Level Operations === * Bitwise Operations ([[Media:BitOp.1.B.20161214.pdf |A.pdf]], [[Media:BitOp.1.B.20161203.pdf |B.pdf]]) * Bit Field ([[Media:BitField.1.A.20161214.pdf |A.pdf]], [[Media:BitField.1.B.20161202.pdf |B.pdf]]) * Union ([[Media:Union.1.A.20161221.pdf |A.pdf]], [[Media:Union.1.B.20161111.pdf |B.pdf]]) * Accessing IO Registers ([[Media:IO.1.A.20141215.pdf |A.pdf]], [[Media:IO.1.B.20161217.pdf |B.pdf]]) === Declarations === * Type Specifiers and Qualifiers ([[Media:C07.Spec1.Type.1.A.20171004.pdf |pdf]]) * Storage Class Specifiers ([[Media:C07.Spec2.Storage.1.A.20171009.pdf |pdf]]) * Scope === Class Notes === * TOC ([[Media:TOC.20171007.pdf |TOC.pdf]]) * Day01 ([[Media:Day01.A.20171007.pdf |A.pdf]], [[Media:Day01.B.20171209.pdf |B.pdf]], [[Media:Day01.C.20171211.pdf |C.pdf]]) ...... Introduction (1) Standard Library * Day02 ([[Media:Day02.A.20171007.pdf |A.pdf]], [[Media:Day02.B.20171209.pdf |B.pdf]], [[Media:Day02.C.20171209.pdf |C.pdf]]) ...... Introduction (2) Basic Elements * Day03 ([[Media:Day03.A.20171007.pdf |A.pdf]], [[Media:Day03.B.20170908.pdf |B.pdf]], [[Media:Day03.C.20171209.pdf |C.pdf]]) ...... Introduction (3) Numbers * Day04 ([[Media:Day04.A.20171007.pdf |A.pdf]], [[Media:Day04.B.20170915.pdf |B.pdf]], [[Media:Day04.C.20171209.pdf |C.pdf]]) ...... Structured Programming (1) Flowcharts * Day05 ([[Media:Day05.A.20171007.pdf |A.pdf]], [[Media:Day05.B.20170915.pdf |B.pdf]], [[Media:Day05.C.20171209.pdf |C.pdf]]) ...... Structured Programming (2) Conditions and Loops * Day06 ([[Media:Day06.A.20171007.pdf |A.pdf]], [[Media:Day06.B.20170923.pdf |B.pdf]], [[Media:Day06.C.20171209.pdf |C.pdf]]) ...... Program Control * Day07 ([[Media:Day07.A.20171007.pdf |A.pdf]], [[Media:Day07.B.20170926.pdf |B.pdf]], [[Media:Day07.C.20171209.pdf |C.pdf]]) ...... Function (1) Definitions * Day08 ([[Media:Day08.A.20171028.pdf |A.pdf]], [[Media:Day08.B.20171016.pdf |B.pdf]], [[Media:Day08.C.20171209.pdf |C.pdf]]) ...... Function (2) Storage Class and Scope * Day09 ([[Media:Day09.A.20171007.pdf |A.pdf]], [[Media:Day09.B.20171017.pdf |B.pdf]], [[Media:Day09.C.20171209.pdf |C.pdf]]) ...... Function (3) Recursion * Day10 ([[Media:Day10.A.20171209.pdf |A.pdf]], [[Media:Day10.B.20171017.pdf |B.pdf]], [[Media:Day10.C.20171209.pdf |C.pdf]]) ...... Arrays (1) Definitions * Day11 ([[Media:Day11.A.20171024.pdf |A.pdf]], [[Media:Day11.B.20171017.pdf |B.pdf]], [[Media:Day11.C.20171212.pdf |C.pdf]]) ...... Arrays (2) Applications * Day12 ([[Media:Day12.A.20171024.pdf |A.pdf]], [[Media:Day12.B.20171020.pdf |B.pdf]], [[Media:Day12.C.20171209.pdf |C.pdf]]) ...... Pointers (1) Definitions * Day13 ([[Media:Day13.A.20171025.pdf |A.pdf]], [[Media:Day13.B.20171024.pdf |B.pdf]], [[Media:Day13.C.20171209.pdf |C.pdf]]) ...... Pointers (2) Applications * Day14 ([[Media:Day14.A.20171226.pdf |A.pdf]], [[Media:Day14.B.20171101.pdf |B.pdf]], [[Media:Day14.C.20171209.pdf |C.pdf]]) ...... C String (1) * Day15 ([[Media:Day15.A.20171209.pdf |A.pdf]], [[Media:Day15.B.20171124.pdf |B.pdf]], [[Media:Day15.C.20171209.pdf |C.pdf]]) ...... C String (2) * Day16 ([[Media:Day16.A.20171208.pdf |A.pdf]], [[Media:Day16.B.20171114.pdf |B.pdf]], [[Media:Day16.C.20171209.pdf |C.pdf]]) ...... C Formatted IO * Day17 ([[Media:Day17.A.20171031.pdf |A.pdf]], [[Media:Day17.B.20171111.pdf |B.pdf]], [[Media:Day17.C.20171209.pdf |C.pdf]]) ...... Structure (1) Definitions * Day18 ([[Media:Day18.A.20171206.pdf |A.pdf]], [[Media:Day18.B.20171128.pdf |B.pdf]], [[Media:Day18.C.20171212.pdf |C.pdf]]) ...... Structure (2) Applications * Day19 ([[Media:Day19.A.20171205.pdf |A.pdf]], [[Media:Day19.B.20171121.pdf |B.pdf]], [[Media:Day19.C.20171209.pdf |C.pdf]]) ...... Union, Bitwise Operators, Enum * Day20 ([[Media:Day20.A.20171205.pdf |A.pdf]], [[Media:Day20.B.20171201.pdf |B.pdf]], [[Media:Day20.C.20171212.pdf |C.pdf]]) ...... Linked List * Day21 ([[Media:Day21.A.20171206.pdf |A.pdf]], [[Media:Day21.B.20171208.pdf |B.pdf]], [[Media:Day21.C.20171212.pdf |C.pdf]]) ...... File Processing * Day22 ([[Media:Day22.A.20171212.pdf |A.pdf]], [[Media:Day22.B.20171213.pdf |B.pdf]], [[Media:Day22.C.20171212.pdf |C.pdf]]) ...... Preprocessing <!----------------------------------------------------------------------> </br> See also https://cprogramex.wordpress.com/ == '''Old Materials '''== until 201201 * Intro.Overview.1.A ([[Media:C.Intro.Overview.1.A.20120107.pdf |pdf]]) * Intro.Memory.1.A ([[Media:C.Intro.Memory.1.A.20120107.pdf |pdf]]) * Intro.Number.1.A ([[Media:C.Intro.Number.1.A.20120107.pdf |pdf]]) * Repeat.Control.1.A ([[Media:C.Repeat.Control.1.A.20120109.pdf |pdf]]) * Repeat.Loop.1.A ([[Media:C.Repeat.Loop.1.A.20120113.pdf |pdf]]) * Work.Function.1.A ([[Media:C.Work.Function.1.A.20120117.pdf |pdf]]) * Work.Scope.1.A ([[Media:C.Work.Scope.1.A.20120117.pdf |pdf]]) * Series.Array.1.A ([[Media:Series.Array.1.A.20110718.pdf |pdf]]) * Series.Pointer.1.A ([[Media:Series.Pointer.1.A.20110719.pdf |pdf]]) * Series.Structure.1.A ([[Media:Series.Structure.1.A.20110805.pdf |pdf]]) * Data.Type.1.A ([[Media:C05.Data2.TypeCast.1.A.20130813.pdf |pdf]]) * Data.TypeCast.1.A ([[Media:Data.TypeCast.1.A.pdf |pdf]]) * Data.Operators.1.A ([[Media:Data.Operators.1.A.20110712.pdf |pdf]]) <br> until 201107 * Intro.1.A ([[Media:Intro.1.A.pdf |pdf]]) * Control.1.A ([[Media:Control.1.A.20110706.pdf |pdf]]) * Iteration.1.A ([[Media:Iteration.1.A.pdf |pdf]]) * Function.1.A ([[Media:Function.1.A.20110705.pdf |pdf]]) * Variable.1.A ([[Media:Variable.1.A.20110708.pdf |pdf]]) * Operators.1.A ([[Media:Operators.1.A.20110712.pdf |pdf]]) * Pointer.1.A ([[Media:Pointer.1.A.pdf |pdf]]) * Pointer.2.A ([[Media:Pointer.2.A.pdf |pdf]]) * Array.1.A ([[Media:Array.1.A.pdf |pdf]]) * Type.1.A ([[Media:Type.1.A.pdf |pdf]]) * Structure.1.A ([[Media:Structure.1.A.pdf |pdf]]) go to [ [[C programming in plain view]] ] [[Category:C programming language]] </br> eiofmny1uokl21h2slvoujbhg15xrtc 2835162 2835160 2026-09-30T12:39:54Z Young1lim 21186 /* Applications */ 2835162 wikitext text/x-wiki === Introduction === * Overview ([[Media:C01.Intro1.Overview.1.A.20170925.pdf |A.pdf]], [[Media:C01.Intro1.Overview.1.B.20170901.pdf |B.pdf]], [[Media:C01.Intro1.Overview.1.C.20170904.pdf |C.pdf]]) * Number System ([[Media:C01.Intro2.Number.1.A.20171023.pdf |A.pdf]], [[Media:C01.Intro2.Number.1.B.20170909.pdf |B.pdf]], [[Media:C01.Intro2.Number.1.C.20170914.pdf |C.pdf]]) * Memory System ([[Media:C01.Intro2.Memory.1.A.20170907.pdf |A.pdf]], [[Media:C01.Intro3.Memory.1.B.20170909.pdf |B.pdf]], [[Media:C01.Intro3.Memory.1.C.20170914.pdf |C.pdf]]) === Handling Repetition === * Control ([[Media:C02.Repeat1.Control.1.A.20170925.pdf |A.pdf]], [[Media:C02.Repeat1.Control.1.B.20170918.pdf |B.pdf]], [[Media:C02.Repeat1.Control.1.C.20170926.pdf |C.pdf]]) * Loop ([[Media:C02.Repeat2.Loop.1.A.20170925.pdf |A.pdf]], [[Media:C02.Repeat2.Loop.1.B.20170918.pdf |B.pdf]]) === Handling a Big Work === * Function Overview ([[Media:C03.Func1.Overview.1.A.20171030.pdf |A.pdf]], [[Media:C03.Func1.Oerview.1.B.20161022.pdf |B.pdf]]) * Functions & Variables ([[Media:C03.Func2.Variable.1.A.20161222.pdf |A.pdf]], [[Media:C03.Func2.Variable.1.B.20161222.pdf |B.pdf]]) * Functions & Pointers ([[Media:C03.Func3.Pointer.1.A.20161122.pdf |A.pdf]], [[Media:C03.Func3.Pointer.1.B.20161122.pdf |B.pdf]]) * Functions & Recursions ([[Media:C03.Func4.Recursion.1.A.20161214.pdf |A.pdf]], [[Media:C03.Func4.Recursion.1.B.20161214.pdf |B.pdf]]) === Handling Series of Data === ==== Background ==== * Background ([[Media:C04.Series0.Background.1.A.20180727.pdf |A.pdf]]) ==== Basics ==== * Pointers ([[Media:C04.S1.Pointer.1A.20240524.pdf |A.pdf]], [[Media:C04.Series2.Pointer.1.B.20161115.pdf |B.pdf]]) * Arrays ([[Media:C04.S2.Array.1A.20240514.pdf |A.pdf]], [[Media:C04.Series1.Array.1.B.20161115.pdf |B.pdf]]) * Array Pointers ([[Media:C04.S3.ArrayPointer.1A.20240208.pdf |A.pdf]], [[Media:C04.Series3.ArrayPointer.1.B.20181203.pdf |B.pdf]]) * Multi-dimensional Arrays ([[Media:C04.Series4.MultiDim.1.A.20221130.pdf |A.pdf]], [[Media:C04.Series4.MultiDim.1.B.1111.pdf |B.pdf]]) * Array Access Methods ([[Media:C04.Series4.ArrayAccess.1.A.20190511.pdf |A.pdf]], [[Media:C04.Series3.ArrayPointer.1.B.20181203.pdf |B.pdf]]) * Structures ([[Media:C04.Series3.Structure.1.A.20171204.pdf |A.pdf]], [[Media:C04.Series2.Structure.1.B.20161130.pdf |B.pdf]]) ==== Examples ==== * Spreadsheet Example Programs :: Example 1 ([[Media:C04.Series7.Example.1.A.20171213.pdf |A.pdf]], [[Media:C04.Series7.Example.1.C.20171213.pdf |C.pdf]]) :: Example 2 ([[Media:C04.Series7.Example.2.A.20171213.pdf |A.pdf]], [[Media:C04.Series7.Example.2.C.20171213.pdf |C.pdf]]) :: Example 3 ([[Media:C04.Series7.Example.3.A.20171213.pdf |A.pdf]], [[Media:C04.Series7.Example.3.C.20171213.pdf |C.pdf]]) :: Bubble Sort ([[Media:C04.Series7.BubbleSort.1.A.20171211.pdf |A.pdf]]) ==== Applications ==== * Address-of and de-reference operators ([[Media:C04.SA0.PtrOperator.1A.20260929.pdf |A.pdf]]) * Applications of Pointers ([[Media:C04.SA1.AppPointer.1A.20241121.pdf |A.pdf]]) * Applications of Arrays ([[Media:C04.SA2.AppArray.1A.20240715.pdf |A.pdf]]) * Applications of Array Pointers ([[Media:C04.SA3.AppArrayPointer.1A.20240210.pdf |A.pdf]]) * Applications of Multi-dimensional Arrays ([[Media:C04.Series4App.MultiDim.1.A.20210719.pdf |A.pdf]]) * Applications of Array Access Methods ([[Media:C04.Series9.AppArrAcess.1.A.20190511.pdf |A.pdf]]) * Applications of Structures ([[Media:C04.Series6.AppStruct.1.A.20190423.pdf |A.pdf]]) === Handling Various Kinds of Data === * Types ([[Media:C05.Data1.Type.1.A.20180217.pdf |A.pdf]], [[Media:C05.Data1.Type.1.B.20161212.pdf |B.pdf]]) * Typecasts ([[Media:C05.Data2.TypeCast.1.A.20180217.pdf |A.pdf]], [[Media:C05.Data2.TypeCast.1.B.20161216.pdf |A.pdf]]) * Operators ([[Media:C05.Data3.Operators.1.A.20161219.pdf |A.pdf]], [[Media:C05.Data3.Operators.1.B.20161216.pdf |B.pdf]]) * Files ([[Media:C05.Data4.File.1.A.20161124.pdf |A.pdf]], [[Media:C05.Data4.File.1.B.20161212.pdf |B.pdf]]) === Handling Low Level Operations === * Bitwise Operations ([[Media:BitOp.1.B.20161214.pdf |A.pdf]], [[Media:BitOp.1.B.20161203.pdf |B.pdf]]) * Bit Field ([[Media:BitField.1.A.20161214.pdf |A.pdf]], [[Media:BitField.1.B.20161202.pdf |B.pdf]]) * Union ([[Media:Union.1.A.20161221.pdf |A.pdf]], [[Media:Union.1.B.20161111.pdf |B.pdf]]) * Accessing IO Registers ([[Media:IO.1.A.20141215.pdf |A.pdf]], [[Media:IO.1.B.20161217.pdf |B.pdf]]) === Declarations === * Type Specifiers and Qualifiers ([[Media:C07.Spec1.Type.1.A.20171004.pdf |pdf]]) * Storage Class Specifiers ([[Media:C07.Spec2.Storage.1.A.20171009.pdf |pdf]]) * Scope === Class Notes === * TOC ([[Media:TOC.20171007.pdf |TOC.pdf]]) * Day01 ([[Media:Day01.A.20171007.pdf |A.pdf]], [[Media:Day01.B.20171209.pdf |B.pdf]], [[Media:Day01.C.20171211.pdf |C.pdf]]) ...... Introduction (1) Standard Library * Day02 ([[Media:Day02.A.20171007.pdf |A.pdf]], [[Media:Day02.B.20171209.pdf |B.pdf]], [[Media:Day02.C.20171209.pdf |C.pdf]]) ...... Introduction (2) Basic Elements * Day03 ([[Media:Day03.A.20171007.pdf |A.pdf]], [[Media:Day03.B.20170908.pdf |B.pdf]], [[Media:Day03.C.20171209.pdf |C.pdf]]) ...... Introduction (3) Numbers * Day04 ([[Media:Day04.A.20171007.pdf |A.pdf]], [[Media:Day04.B.20170915.pdf |B.pdf]], [[Media:Day04.C.20171209.pdf |C.pdf]]) ...... Structured Programming (1) Flowcharts * Day05 ([[Media:Day05.A.20171007.pdf |A.pdf]], [[Media:Day05.B.20170915.pdf |B.pdf]], [[Media:Day05.C.20171209.pdf |C.pdf]]) ...... Structured Programming (2) Conditions and Loops * Day06 ([[Media:Day06.A.20171007.pdf |A.pdf]], [[Media:Day06.B.20170923.pdf |B.pdf]], [[Media:Day06.C.20171209.pdf |C.pdf]]) ...... Program Control * Day07 ([[Media:Day07.A.20171007.pdf |A.pdf]], [[Media:Day07.B.20170926.pdf |B.pdf]], [[Media:Day07.C.20171209.pdf |C.pdf]]) ...... Function (1) Definitions * Day08 ([[Media:Day08.A.20171028.pdf |A.pdf]], [[Media:Day08.B.20171016.pdf |B.pdf]], [[Media:Day08.C.20171209.pdf |C.pdf]]) ...... Function (2) Storage Class and Scope * Day09 ([[Media:Day09.A.20171007.pdf |A.pdf]], [[Media:Day09.B.20171017.pdf |B.pdf]], [[Media:Day09.C.20171209.pdf |C.pdf]]) ...... Function (3) Recursion * Day10 ([[Media:Day10.A.20171209.pdf |A.pdf]], [[Media:Day10.B.20171017.pdf |B.pdf]], [[Media:Day10.C.20171209.pdf |C.pdf]]) ...... Arrays (1) Definitions * Day11 ([[Media:Day11.A.20171024.pdf |A.pdf]], [[Media:Day11.B.20171017.pdf |B.pdf]], [[Media:Day11.C.20171212.pdf |C.pdf]]) ...... Arrays (2) Applications * Day12 ([[Media:Day12.A.20171024.pdf |A.pdf]], [[Media:Day12.B.20171020.pdf |B.pdf]], [[Media:Day12.C.20171209.pdf |C.pdf]]) ...... Pointers (1) Definitions * Day13 ([[Media:Day13.A.20171025.pdf |A.pdf]], [[Media:Day13.B.20171024.pdf |B.pdf]], [[Media:Day13.C.20171209.pdf |C.pdf]]) ...... Pointers (2) Applications * Day14 ([[Media:Day14.A.20171226.pdf |A.pdf]], [[Media:Day14.B.20171101.pdf |B.pdf]], [[Media:Day14.C.20171209.pdf |C.pdf]]) ...... C String (1) * Day15 ([[Media:Day15.A.20171209.pdf |A.pdf]], [[Media:Day15.B.20171124.pdf |B.pdf]], [[Media:Day15.C.20171209.pdf |C.pdf]]) ...... C String (2) * Day16 ([[Media:Day16.A.20171208.pdf |A.pdf]], [[Media:Day16.B.20171114.pdf |B.pdf]], [[Media:Day16.C.20171209.pdf |C.pdf]]) ...... C Formatted IO * Day17 ([[Media:Day17.A.20171031.pdf |A.pdf]], [[Media:Day17.B.20171111.pdf |B.pdf]], [[Media:Day17.C.20171209.pdf |C.pdf]]) ...... Structure (1) Definitions * Day18 ([[Media:Day18.A.20171206.pdf |A.pdf]], [[Media:Day18.B.20171128.pdf |B.pdf]], [[Media:Day18.C.20171212.pdf |C.pdf]]) ...... Structure (2) Applications * Day19 ([[Media:Day19.A.20171205.pdf |A.pdf]], [[Media:Day19.B.20171121.pdf |B.pdf]], [[Media:Day19.C.20171209.pdf |C.pdf]]) ...... Union, Bitwise Operators, Enum * Day20 ([[Media:Day20.A.20171205.pdf |A.pdf]], [[Media:Day20.B.20171201.pdf |B.pdf]], [[Media:Day20.C.20171212.pdf |C.pdf]]) ...... Linked List * Day21 ([[Media:Day21.A.20171206.pdf |A.pdf]], [[Media:Day21.B.20171208.pdf |B.pdf]], [[Media:Day21.C.20171212.pdf |C.pdf]]) ...... File Processing * Day22 ([[Media:Day22.A.20171212.pdf |A.pdf]], [[Media:Day22.B.20171213.pdf |B.pdf]], [[Media:Day22.C.20171212.pdf |C.pdf]]) ...... Preprocessing <!----------------------------------------------------------------------> </br> See also https://cprogramex.wordpress.com/ == '''Old Materials '''== until 201201 * Intro.Overview.1.A ([[Media:C.Intro.Overview.1.A.20120107.pdf |pdf]]) * Intro.Memory.1.A ([[Media:C.Intro.Memory.1.A.20120107.pdf |pdf]]) * Intro.Number.1.A ([[Media:C.Intro.Number.1.A.20120107.pdf |pdf]]) * Repeat.Control.1.A ([[Media:C.Repeat.Control.1.A.20120109.pdf |pdf]]) * Repeat.Loop.1.A ([[Media:C.Repeat.Loop.1.A.20120113.pdf |pdf]]) * Work.Function.1.A ([[Media:C.Work.Function.1.A.20120117.pdf |pdf]]) * Work.Scope.1.A ([[Media:C.Work.Scope.1.A.20120117.pdf |pdf]]) * Series.Array.1.A ([[Media:Series.Array.1.A.20110718.pdf |pdf]]) * Series.Pointer.1.A ([[Media:Series.Pointer.1.A.20110719.pdf |pdf]]) * Series.Structure.1.A ([[Media:Series.Structure.1.A.20110805.pdf |pdf]]) * Data.Type.1.A ([[Media:C05.Data2.TypeCast.1.A.20130813.pdf |pdf]]) * Data.TypeCast.1.A ([[Media:Data.TypeCast.1.A.pdf |pdf]]) * Data.Operators.1.A ([[Media:Data.Operators.1.A.20110712.pdf |pdf]]) <br> until 201107 * Intro.1.A ([[Media:Intro.1.A.pdf |pdf]]) * Control.1.A ([[Media:Control.1.A.20110706.pdf |pdf]]) * Iteration.1.A ([[Media:Iteration.1.A.pdf |pdf]]) * Function.1.A ([[Media:Function.1.A.20110705.pdf |pdf]]) * Variable.1.A ([[Media:Variable.1.A.20110708.pdf |pdf]]) * Operators.1.A ([[Media:Operators.1.A.20110712.pdf |pdf]]) * Pointer.1.A ([[Media:Pointer.1.A.pdf |pdf]]) * Pointer.2.A ([[Media:Pointer.2.A.pdf |pdf]]) * Array.1.A ([[Media:Array.1.A.pdf |pdf]]) * Type.1.A ([[Media:Type.1.A.pdf |pdf]]) * Structure.1.A ([[Media:Structure.1.A.pdf |pdf]]) go to [ [[C programming in plain view]] ] [[Category:C programming language]] </br> t4ych9f6o5k1m1hf9dxep85u8epohza 2835164 2835162 2026-09-30T12:40:42Z Young1lim 21186 /* Applications */ 2835164 wikitext text/x-wiki === Introduction === * Overview ([[Media:C01.Intro1.Overview.1.A.20170925.pdf |A.pdf]], [[Media:C01.Intro1.Overview.1.B.20170901.pdf |B.pdf]], [[Media:C01.Intro1.Overview.1.C.20170904.pdf |C.pdf]]) * Number System ([[Media:C01.Intro2.Number.1.A.20171023.pdf |A.pdf]], [[Media:C01.Intro2.Number.1.B.20170909.pdf |B.pdf]], [[Media:C01.Intro2.Number.1.C.20170914.pdf |C.pdf]]) * Memory System ([[Media:C01.Intro2.Memory.1.A.20170907.pdf |A.pdf]], [[Media:C01.Intro3.Memory.1.B.20170909.pdf |B.pdf]], [[Media:C01.Intro3.Memory.1.C.20170914.pdf |C.pdf]]) === Handling Repetition === * Control ([[Media:C02.Repeat1.Control.1.A.20170925.pdf |A.pdf]], [[Media:C02.Repeat1.Control.1.B.20170918.pdf |B.pdf]], [[Media:C02.Repeat1.Control.1.C.20170926.pdf |C.pdf]]) * Loop ([[Media:C02.Repeat2.Loop.1.A.20170925.pdf |A.pdf]], [[Media:C02.Repeat2.Loop.1.B.20170918.pdf |B.pdf]]) === Handling a Big Work === * Function Overview ([[Media:C03.Func1.Overview.1.A.20171030.pdf |A.pdf]], [[Media:C03.Func1.Oerview.1.B.20161022.pdf |B.pdf]]) * Functions & Variables ([[Media:C03.Func2.Variable.1.A.20161222.pdf |A.pdf]], [[Media:C03.Func2.Variable.1.B.20161222.pdf |B.pdf]]) * Functions & Pointers ([[Media:C03.Func3.Pointer.1.A.20161122.pdf |A.pdf]], [[Media:C03.Func3.Pointer.1.B.20161122.pdf |B.pdf]]) * Functions & Recursions ([[Media:C03.Func4.Recursion.1.A.20161214.pdf |A.pdf]], [[Media:C03.Func4.Recursion.1.B.20161214.pdf |B.pdf]]) === Handling Series of Data === ==== Background ==== * Background ([[Media:C04.Series0.Background.1.A.20180727.pdf |A.pdf]]) ==== Basics ==== * Pointers ([[Media:C04.S1.Pointer.1A.20240524.pdf |A.pdf]], [[Media:C04.Series2.Pointer.1.B.20161115.pdf |B.pdf]]) * Arrays ([[Media:C04.S2.Array.1A.20240514.pdf |A.pdf]], [[Media:C04.Series1.Array.1.B.20161115.pdf |B.pdf]]) * Array Pointers ([[Media:C04.S3.ArrayPointer.1A.20240208.pdf |A.pdf]], [[Media:C04.Series3.ArrayPointer.1.B.20181203.pdf |B.pdf]]) * Multi-dimensional Arrays ([[Media:C04.Series4.MultiDim.1.A.20221130.pdf |A.pdf]], [[Media:C04.Series4.MultiDim.1.B.1111.pdf |B.pdf]]) * Array Access Methods ([[Media:C04.Series4.ArrayAccess.1.A.20190511.pdf |A.pdf]], [[Media:C04.Series3.ArrayPointer.1.B.20181203.pdf |B.pdf]]) * Structures ([[Media:C04.Series3.Structure.1.A.20171204.pdf |A.pdf]], [[Media:C04.Series2.Structure.1.B.20161130.pdf |B.pdf]]) ==== Examples ==== * Spreadsheet Example Programs :: Example 1 ([[Media:C04.Series7.Example.1.A.20171213.pdf |A.pdf]], [[Media:C04.Series7.Example.1.C.20171213.pdf |C.pdf]]) :: Example 2 ([[Media:C04.Series7.Example.2.A.20171213.pdf |A.pdf]], [[Media:C04.Series7.Example.2.C.20171213.pdf |C.pdf]]) :: Example 3 ([[Media:C04.Series7.Example.3.A.20171213.pdf |A.pdf]], [[Media:C04.Series7.Example.3.C.20171213.pdf |C.pdf]]) :: Bubble Sort ([[Media:C04.Series7.BubbleSort.1.A.20171211.pdf |A.pdf]]) ==== Applications ==== * Address-of and de-reference operators ([[Media:C04.SA0.PtrOperator.1A.20260930.pdf |A.pdf]]) * Applications of Pointers ([[Media:C04.SA1.AppPointer.1A.20241121.pdf |A.pdf]]) * Applications of Arrays ([[Media:C04.SA2.AppArray.1A.20240715.pdf |A.pdf]]) * Applications of Array Pointers ([[Media:C04.SA3.AppArrayPointer.1A.20240210.pdf |A.pdf]]) * Applications of Multi-dimensional Arrays ([[Media:C04.Series4App.MultiDim.1.A.20210719.pdf |A.pdf]]) * Applications of Array Access Methods ([[Media:C04.Series9.AppArrAcess.1.A.20190511.pdf |A.pdf]]) * Applications of Structures ([[Media:C04.Series6.AppStruct.1.A.20190423.pdf |A.pdf]]) === Handling Various Kinds of Data === * Types ([[Media:C05.Data1.Type.1.A.20180217.pdf |A.pdf]], [[Media:C05.Data1.Type.1.B.20161212.pdf |B.pdf]]) * Typecasts ([[Media:C05.Data2.TypeCast.1.A.20180217.pdf |A.pdf]], [[Media:C05.Data2.TypeCast.1.B.20161216.pdf |A.pdf]]) * Operators ([[Media:C05.Data3.Operators.1.A.20161219.pdf |A.pdf]], [[Media:C05.Data3.Operators.1.B.20161216.pdf |B.pdf]]) * Files ([[Media:C05.Data4.File.1.A.20161124.pdf |A.pdf]], [[Media:C05.Data4.File.1.B.20161212.pdf |B.pdf]]) === Handling Low Level Operations === * Bitwise Operations ([[Media:BitOp.1.B.20161214.pdf |A.pdf]], [[Media:BitOp.1.B.20161203.pdf |B.pdf]]) * Bit Field ([[Media:BitField.1.A.20161214.pdf |A.pdf]], [[Media:BitField.1.B.20161202.pdf |B.pdf]]) * Union ([[Media:Union.1.A.20161221.pdf |A.pdf]], [[Media:Union.1.B.20161111.pdf |B.pdf]]) * Accessing IO Registers ([[Media:IO.1.A.20141215.pdf |A.pdf]], [[Media:IO.1.B.20161217.pdf |B.pdf]]) === Declarations === * Type Specifiers and Qualifiers ([[Media:C07.Spec1.Type.1.A.20171004.pdf |pdf]]) * Storage Class Specifiers ([[Media:C07.Spec2.Storage.1.A.20171009.pdf |pdf]]) * Scope === Class Notes === * TOC ([[Media:TOC.20171007.pdf |TOC.pdf]]) * Day01 ([[Media:Day01.A.20171007.pdf |A.pdf]], [[Media:Day01.B.20171209.pdf |B.pdf]], [[Media:Day01.C.20171211.pdf |C.pdf]]) ...... Introduction (1) Standard Library * Day02 ([[Media:Day02.A.20171007.pdf |A.pdf]], [[Media:Day02.B.20171209.pdf |B.pdf]], [[Media:Day02.C.20171209.pdf |C.pdf]]) ...... Introduction (2) Basic Elements * Day03 ([[Media:Day03.A.20171007.pdf |A.pdf]], [[Media:Day03.B.20170908.pdf |B.pdf]], [[Media:Day03.C.20171209.pdf |C.pdf]]) ...... Introduction (3) Numbers * Day04 ([[Media:Day04.A.20171007.pdf |A.pdf]], [[Media:Day04.B.20170915.pdf |B.pdf]], [[Media:Day04.C.20171209.pdf |C.pdf]]) ...... Structured Programming (1) Flowcharts * Day05 ([[Media:Day05.A.20171007.pdf |A.pdf]], [[Media:Day05.B.20170915.pdf |B.pdf]], [[Media:Day05.C.20171209.pdf |C.pdf]]) ...... Structured Programming (2) Conditions and Loops * Day06 ([[Media:Day06.A.20171007.pdf |A.pdf]], [[Media:Day06.B.20170923.pdf |B.pdf]], [[Media:Day06.C.20171209.pdf |C.pdf]]) ...... Program Control * Day07 ([[Media:Day07.A.20171007.pdf |A.pdf]], [[Media:Day07.B.20170926.pdf |B.pdf]], [[Media:Day07.C.20171209.pdf |C.pdf]]) ...... Function (1) Definitions * Day08 ([[Media:Day08.A.20171028.pdf |A.pdf]], [[Media:Day08.B.20171016.pdf |B.pdf]], [[Media:Day08.C.20171209.pdf |C.pdf]]) ...... Function (2) Storage Class and Scope * Day09 ([[Media:Day09.A.20171007.pdf |A.pdf]], [[Media:Day09.B.20171017.pdf |B.pdf]], [[Media:Day09.C.20171209.pdf |C.pdf]]) ...... Function (3) Recursion * Day10 ([[Media:Day10.A.20171209.pdf |A.pdf]], [[Media:Day10.B.20171017.pdf |B.pdf]], [[Media:Day10.C.20171209.pdf |C.pdf]]) ...... Arrays (1) Definitions * Day11 ([[Media:Day11.A.20171024.pdf |A.pdf]], [[Media:Day11.B.20171017.pdf |B.pdf]], [[Media:Day11.C.20171212.pdf |C.pdf]]) ...... Arrays (2) Applications * Day12 ([[Media:Day12.A.20171024.pdf |A.pdf]], [[Media:Day12.B.20171020.pdf |B.pdf]], [[Media:Day12.C.20171209.pdf |C.pdf]]) ...... Pointers (1) Definitions * Day13 ([[Media:Day13.A.20171025.pdf |A.pdf]], [[Media:Day13.B.20171024.pdf |B.pdf]], [[Media:Day13.C.20171209.pdf |C.pdf]]) ...... Pointers (2) Applications * Day14 ([[Media:Day14.A.20171226.pdf |A.pdf]], [[Media:Day14.B.20171101.pdf |B.pdf]], [[Media:Day14.C.20171209.pdf |C.pdf]]) ...... C String (1) * Day15 ([[Media:Day15.A.20171209.pdf |A.pdf]], [[Media:Day15.B.20171124.pdf |B.pdf]], [[Media:Day15.C.20171209.pdf |C.pdf]]) ...... C String (2) * Day16 ([[Media:Day16.A.20171208.pdf |A.pdf]], [[Media:Day16.B.20171114.pdf |B.pdf]], [[Media:Day16.C.20171209.pdf |C.pdf]]) ...... C Formatted IO * Day17 ([[Media:Day17.A.20171031.pdf |A.pdf]], [[Media:Day17.B.20171111.pdf |B.pdf]], [[Media:Day17.C.20171209.pdf |C.pdf]]) ...... Structure (1) Definitions * Day18 ([[Media:Day18.A.20171206.pdf |A.pdf]], [[Media:Day18.B.20171128.pdf |B.pdf]], [[Media:Day18.C.20171212.pdf |C.pdf]]) ...... Structure (2) Applications * Day19 ([[Media:Day19.A.20171205.pdf |A.pdf]], [[Media:Day19.B.20171121.pdf |B.pdf]], [[Media:Day19.C.20171209.pdf |C.pdf]]) ...... Union, Bitwise Operators, Enum * Day20 ([[Media:Day20.A.20171205.pdf |A.pdf]], [[Media:Day20.B.20171201.pdf |B.pdf]], [[Media:Day20.C.20171212.pdf |C.pdf]]) ...... Linked List * Day21 ([[Media:Day21.A.20171206.pdf |A.pdf]], [[Media:Day21.B.20171208.pdf |B.pdf]], [[Media:Day21.C.20171212.pdf |C.pdf]]) ...... File Processing * Day22 ([[Media:Day22.A.20171212.pdf |A.pdf]], [[Media:Day22.B.20171213.pdf |B.pdf]], [[Media:Day22.C.20171212.pdf |C.pdf]]) ...... Preprocessing <!----------------------------------------------------------------------> </br> See also https://cprogramex.wordpress.com/ == '''Old Materials '''== until 201201 * Intro.Overview.1.A ([[Media:C.Intro.Overview.1.A.20120107.pdf |pdf]]) * Intro.Memory.1.A ([[Media:C.Intro.Memory.1.A.20120107.pdf |pdf]]) * Intro.Number.1.A ([[Media:C.Intro.Number.1.A.20120107.pdf |pdf]]) * Repeat.Control.1.A ([[Media:C.Repeat.Control.1.A.20120109.pdf |pdf]]) * Repeat.Loop.1.A ([[Media:C.Repeat.Loop.1.A.20120113.pdf |pdf]]) * Work.Function.1.A ([[Media:C.Work.Function.1.A.20120117.pdf |pdf]]) * Work.Scope.1.A ([[Media:C.Work.Scope.1.A.20120117.pdf |pdf]]) * Series.Array.1.A ([[Media:Series.Array.1.A.20110718.pdf |pdf]]) * Series.Pointer.1.A ([[Media:Series.Pointer.1.A.20110719.pdf |pdf]]) * Series.Structure.1.A ([[Media:Series.Structure.1.A.20110805.pdf |pdf]]) * Data.Type.1.A ([[Media:C05.Data2.TypeCast.1.A.20130813.pdf |pdf]]) * Data.TypeCast.1.A ([[Media:Data.TypeCast.1.A.pdf |pdf]]) * Data.Operators.1.A ([[Media:Data.Operators.1.A.20110712.pdf |pdf]]) <br> until 201107 * Intro.1.A ([[Media:Intro.1.A.pdf |pdf]]) * Control.1.A ([[Media:Control.1.A.20110706.pdf |pdf]]) * Iteration.1.A ([[Media:Iteration.1.A.pdf |pdf]]) * Function.1.A ([[Media:Function.1.A.20110705.pdf |pdf]]) * Variable.1.A ([[Media:Variable.1.A.20110708.pdf |pdf]]) * Operators.1.A ([[Media:Operators.1.A.20110712.pdf |pdf]]) * Pointer.1.A ([[Media:Pointer.1.A.pdf |pdf]]) * Pointer.2.A ([[Media:Pointer.2.A.pdf |pdf]]) * Array.1.A ([[Media:Array.1.A.pdf |pdf]]) * Type.1.A ([[Media:Type.1.A.pdf |pdf]]) * Structure.1.A ([[Media:Structure.1.A.pdf |pdf]]) go to [ [[C programming in plain view]] ] [[Category:C programming language]] </br> praspefl82lsbtmnb61w9j61hde6wsj 2835328 2835164 2026-10-01T10:36:50Z Young1lim 21186 /* Applications */ 2835328 wikitext text/x-wiki === Introduction === * Overview ([[Media:C01.Intro1.Overview.1.A.20170925.pdf |A.pdf]], [[Media:C01.Intro1.Overview.1.B.20170901.pdf |B.pdf]], [[Media:C01.Intro1.Overview.1.C.20170904.pdf |C.pdf]]) * Number System ([[Media:C01.Intro2.Number.1.A.20171023.pdf |A.pdf]], [[Media:C01.Intro2.Number.1.B.20170909.pdf |B.pdf]], [[Media:C01.Intro2.Number.1.C.20170914.pdf |C.pdf]]) * Memory System ([[Media:C01.Intro2.Memory.1.A.20170907.pdf |A.pdf]], [[Media:C01.Intro3.Memory.1.B.20170909.pdf |B.pdf]], [[Media:C01.Intro3.Memory.1.C.20170914.pdf |C.pdf]]) === Handling Repetition === * Control ([[Media:C02.Repeat1.Control.1.A.20170925.pdf |A.pdf]], [[Media:C02.Repeat1.Control.1.B.20170918.pdf |B.pdf]], [[Media:C02.Repeat1.Control.1.C.20170926.pdf |C.pdf]]) * Loop ([[Media:C02.Repeat2.Loop.1.A.20170925.pdf |A.pdf]], [[Media:C02.Repeat2.Loop.1.B.20170918.pdf |B.pdf]]) === Handling a Big Work === * Function Overview ([[Media:C03.Func1.Overview.1.A.20171030.pdf |A.pdf]], [[Media:C03.Func1.Oerview.1.B.20161022.pdf |B.pdf]]) * Functions & Variables ([[Media:C03.Func2.Variable.1.A.20161222.pdf |A.pdf]], [[Media:C03.Func2.Variable.1.B.20161222.pdf |B.pdf]]) * Functions & Pointers ([[Media:C03.Func3.Pointer.1.A.20161122.pdf |A.pdf]], [[Media:C03.Func3.Pointer.1.B.20161122.pdf |B.pdf]]) * Functions & Recursions ([[Media:C03.Func4.Recursion.1.A.20161214.pdf |A.pdf]], [[Media:C03.Func4.Recursion.1.B.20161214.pdf |B.pdf]]) === Handling Series of Data === ==== Background ==== * Background ([[Media:C04.Series0.Background.1.A.20180727.pdf |A.pdf]]) ==== Basics ==== * Pointers ([[Media:C04.S1.Pointer.1A.20240524.pdf |A.pdf]], [[Media:C04.Series2.Pointer.1.B.20161115.pdf |B.pdf]]) * Arrays ([[Media:C04.S2.Array.1A.20240514.pdf |A.pdf]], [[Media:C04.Series1.Array.1.B.20161115.pdf |B.pdf]]) * Array Pointers ([[Media:C04.S3.ArrayPointer.1A.20240208.pdf |A.pdf]], [[Media:C04.Series3.ArrayPointer.1.B.20181203.pdf |B.pdf]]) * Multi-dimensional Arrays ([[Media:C04.Series4.MultiDim.1.A.20221130.pdf |A.pdf]], [[Media:C04.Series4.MultiDim.1.B.1111.pdf |B.pdf]]) * Array Access Methods ([[Media:C04.Series4.ArrayAccess.1.A.20190511.pdf |A.pdf]], [[Media:C04.Series3.ArrayPointer.1.B.20181203.pdf |B.pdf]]) * Structures ([[Media:C04.Series3.Structure.1.A.20171204.pdf |A.pdf]], [[Media:C04.Series2.Structure.1.B.20161130.pdf |B.pdf]]) ==== Examples ==== * Spreadsheet Example Programs :: Example 1 ([[Media:C04.Series7.Example.1.A.20171213.pdf |A.pdf]], [[Media:C04.Series7.Example.1.C.20171213.pdf |C.pdf]]) :: Example 2 ([[Media:C04.Series7.Example.2.A.20171213.pdf |A.pdf]], [[Media:C04.Series7.Example.2.C.20171213.pdf |C.pdf]]) :: Example 3 ([[Media:C04.Series7.Example.3.A.20171213.pdf |A.pdf]], [[Media:C04.Series7.Example.3.C.20171213.pdf |C.pdf]]) :: Bubble Sort ([[Media:C04.Series7.BubbleSort.1.A.20171211.pdf |A.pdf]]) ==== Applications ==== * Address-of and de-reference operators ([[Media:C04.SA0.PtrOperator.1A.20261001.pdf |A.pdf]]) * Applications of Pointers ([[Media:C04.SA1.AppPointer.1A.20241121.pdf |A.pdf]]) * Applications of Arrays ([[Media:C04.SA2.AppArray.1A.20240715.pdf |A.pdf]]) * Applications of Array Pointers ([[Media:C04.SA3.AppArrayPointer.1A.20240210.pdf |A.pdf]]) * Applications of Multi-dimensional Arrays ([[Media:C04.Series4App.MultiDim.1.A.20210719.pdf |A.pdf]]) * Applications of Array Access Methods ([[Media:C04.Series9.AppArrAcess.1.A.20190511.pdf |A.pdf]]) * Applications of Structures ([[Media:C04.Series6.AppStruct.1.A.20190423.pdf |A.pdf]]) === Handling Various Kinds of Data === * Types ([[Media:C05.Data1.Type.1.A.20180217.pdf |A.pdf]], [[Media:C05.Data1.Type.1.B.20161212.pdf |B.pdf]]) * Typecasts ([[Media:C05.Data2.TypeCast.1.A.20180217.pdf |A.pdf]], [[Media:C05.Data2.TypeCast.1.B.20161216.pdf |A.pdf]]) * Operators ([[Media:C05.Data3.Operators.1.A.20161219.pdf |A.pdf]], [[Media:C05.Data3.Operators.1.B.20161216.pdf |B.pdf]]) * Files ([[Media:C05.Data4.File.1.A.20161124.pdf |A.pdf]], [[Media:C05.Data4.File.1.B.20161212.pdf |B.pdf]]) === Handling Low Level Operations === * Bitwise Operations ([[Media:BitOp.1.B.20161214.pdf |A.pdf]], [[Media:BitOp.1.B.20161203.pdf |B.pdf]]) * Bit Field ([[Media:BitField.1.A.20161214.pdf |A.pdf]], [[Media:BitField.1.B.20161202.pdf |B.pdf]]) * Union ([[Media:Union.1.A.20161221.pdf |A.pdf]], [[Media:Union.1.B.20161111.pdf |B.pdf]]) * Accessing IO Registers ([[Media:IO.1.A.20141215.pdf |A.pdf]], [[Media:IO.1.B.20161217.pdf |B.pdf]]) === Declarations === * Type Specifiers and Qualifiers ([[Media:C07.Spec1.Type.1.A.20171004.pdf |pdf]]) * Storage Class Specifiers ([[Media:C07.Spec2.Storage.1.A.20171009.pdf |pdf]]) * Scope === Class Notes === * TOC ([[Media:TOC.20171007.pdf |TOC.pdf]]) * Day01 ([[Media:Day01.A.20171007.pdf |A.pdf]], [[Media:Day01.B.20171209.pdf |B.pdf]], [[Media:Day01.C.20171211.pdf |C.pdf]]) ...... Introduction (1) Standard Library * Day02 ([[Media:Day02.A.20171007.pdf |A.pdf]], [[Media:Day02.B.20171209.pdf |B.pdf]], [[Media:Day02.C.20171209.pdf |C.pdf]]) ...... Introduction (2) Basic Elements * Day03 ([[Media:Day03.A.20171007.pdf |A.pdf]], [[Media:Day03.B.20170908.pdf |B.pdf]], [[Media:Day03.C.20171209.pdf |C.pdf]]) ...... Introduction (3) Numbers * Day04 ([[Media:Day04.A.20171007.pdf |A.pdf]], [[Media:Day04.B.20170915.pdf |B.pdf]], [[Media:Day04.C.20171209.pdf |C.pdf]]) ...... Structured Programming (1) Flowcharts * Day05 ([[Media:Day05.A.20171007.pdf |A.pdf]], [[Media:Day05.B.20170915.pdf |B.pdf]], [[Media:Day05.C.20171209.pdf |C.pdf]]) ...... Structured Programming (2) Conditions and Loops * Day06 ([[Media:Day06.A.20171007.pdf |A.pdf]], [[Media:Day06.B.20170923.pdf |B.pdf]], [[Media:Day06.C.20171209.pdf |C.pdf]]) ...... Program Control * Day07 ([[Media:Day07.A.20171007.pdf |A.pdf]], [[Media:Day07.B.20170926.pdf |B.pdf]], [[Media:Day07.C.20171209.pdf |C.pdf]]) ...... Function (1) Definitions * Day08 ([[Media:Day08.A.20171028.pdf |A.pdf]], [[Media:Day08.B.20171016.pdf |B.pdf]], [[Media:Day08.C.20171209.pdf |C.pdf]]) ...... Function (2) Storage Class and Scope * Day09 ([[Media:Day09.A.20171007.pdf |A.pdf]], [[Media:Day09.B.20171017.pdf |B.pdf]], [[Media:Day09.C.20171209.pdf |C.pdf]]) ...... Function (3) Recursion * Day10 ([[Media:Day10.A.20171209.pdf |A.pdf]], [[Media:Day10.B.20171017.pdf |B.pdf]], [[Media:Day10.C.20171209.pdf |C.pdf]]) ...... Arrays (1) Definitions * Day11 ([[Media:Day11.A.20171024.pdf |A.pdf]], [[Media:Day11.B.20171017.pdf |B.pdf]], [[Media:Day11.C.20171212.pdf |C.pdf]]) ...... Arrays (2) Applications * Day12 ([[Media:Day12.A.20171024.pdf |A.pdf]], [[Media:Day12.B.20171020.pdf |B.pdf]], [[Media:Day12.C.20171209.pdf |C.pdf]]) ...... Pointers (1) Definitions * Day13 ([[Media:Day13.A.20171025.pdf |A.pdf]], [[Media:Day13.B.20171024.pdf |B.pdf]], [[Media:Day13.C.20171209.pdf |C.pdf]]) ...... Pointers (2) Applications * Day14 ([[Media:Day14.A.20171226.pdf |A.pdf]], [[Media:Day14.B.20171101.pdf |B.pdf]], [[Media:Day14.C.20171209.pdf |C.pdf]]) ...... C String (1) * Day15 ([[Media:Day15.A.20171209.pdf |A.pdf]], [[Media:Day15.B.20171124.pdf |B.pdf]], [[Media:Day15.C.20171209.pdf |C.pdf]]) ...... C String (2) * Day16 ([[Media:Day16.A.20171208.pdf |A.pdf]], [[Media:Day16.B.20171114.pdf |B.pdf]], [[Media:Day16.C.20171209.pdf |C.pdf]]) ...... C Formatted IO * Day17 ([[Media:Day17.A.20171031.pdf |A.pdf]], [[Media:Day17.B.20171111.pdf |B.pdf]], [[Media:Day17.C.20171209.pdf |C.pdf]]) ...... Structure (1) Definitions * Day18 ([[Media:Day18.A.20171206.pdf |A.pdf]], [[Media:Day18.B.20171128.pdf |B.pdf]], [[Media:Day18.C.20171212.pdf |C.pdf]]) ...... Structure (2) Applications * Day19 ([[Media:Day19.A.20171205.pdf |A.pdf]], [[Media:Day19.B.20171121.pdf |B.pdf]], [[Media:Day19.C.20171209.pdf |C.pdf]]) ...... Union, Bitwise Operators, Enum * Day20 ([[Media:Day20.A.20171205.pdf |A.pdf]], [[Media:Day20.B.20171201.pdf |B.pdf]], [[Media:Day20.C.20171212.pdf |C.pdf]]) ...... Linked List * Day21 ([[Media:Day21.A.20171206.pdf |A.pdf]], [[Media:Day21.B.20171208.pdf |B.pdf]], [[Media:Day21.C.20171212.pdf |C.pdf]]) ...... File Processing * Day22 ([[Media:Day22.A.20171212.pdf |A.pdf]], [[Media:Day22.B.20171213.pdf |B.pdf]], [[Media:Day22.C.20171212.pdf |C.pdf]]) ...... Preprocessing <!----------------------------------------------------------------------> </br> See also https://cprogramex.wordpress.com/ == '''Old Materials '''== until 201201 * Intro.Overview.1.A ([[Media:C.Intro.Overview.1.A.20120107.pdf |pdf]]) * Intro.Memory.1.A ([[Media:C.Intro.Memory.1.A.20120107.pdf |pdf]]) * Intro.Number.1.A ([[Media:C.Intro.Number.1.A.20120107.pdf |pdf]]) * Repeat.Control.1.A ([[Media:C.Repeat.Control.1.A.20120109.pdf |pdf]]) * Repeat.Loop.1.A ([[Media:C.Repeat.Loop.1.A.20120113.pdf |pdf]]) * Work.Function.1.A ([[Media:C.Work.Function.1.A.20120117.pdf |pdf]]) * Work.Scope.1.A ([[Media:C.Work.Scope.1.A.20120117.pdf |pdf]]) * Series.Array.1.A ([[Media:Series.Array.1.A.20110718.pdf |pdf]]) * Series.Pointer.1.A ([[Media:Series.Pointer.1.A.20110719.pdf |pdf]]) * Series.Structure.1.A ([[Media:Series.Structure.1.A.20110805.pdf |pdf]]) * Data.Type.1.A ([[Media:C05.Data2.TypeCast.1.A.20130813.pdf |pdf]]) * Data.TypeCast.1.A ([[Media:Data.TypeCast.1.A.pdf |pdf]]) * Data.Operators.1.A ([[Media:Data.Operators.1.A.20110712.pdf |pdf]]) <br> until 201107 * Intro.1.A ([[Media:Intro.1.A.pdf |pdf]]) * Control.1.A ([[Media:Control.1.A.20110706.pdf |pdf]]) * Iteration.1.A ([[Media:Iteration.1.A.pdf |pdf]]) * Function.1.A ([[Media:Function.1.A.20110705.pdf |pdf]]) * Variable.1.A ([[Media:Variable.1.A.20110708.pdf |pdf]]) * Operators.1.A ([[Media:Operators.1.A.20110712.pdf |pdf]]) * Pointer.1.A ([[Media:Pointer.1.A.pdf |pdf]]) * Pointer.2.A ([[Media:Pointer.2.A.pdf |pdf]]) * Array.1.A ([[Media:Array.1.A.pdf |pdf]]) * Type.1.A ([[Media:Type.1.A.pdf |pdf]]) * Structure.1.A ([[Media:Structure.1.A.pdf |pdf]]) go to [ [[C programming in plain view]] ] [[Category:C programming language]] </br> qtx50pggm49icanx0dwm0xuyd6hktdy 2 289273 2835210 2834942 2026-09-30T16:14:08Z Dc.samizdat 2856930 /* An object's motion in space is the product of its discrete self-reflections */ 2835210 wikitext text/x-wiki {{align|center|David Brooks Christie}} {{align|center|dc@samizdat.org}} {{align|center|Draft in progress}} {{align|center|June 2023 - September 2026}} <blockquote>'''Abstract:''' The physical universe is properly visualized as Euclidean space <math>\mathbb{R}^4</math> of four orthogonal spatial dimensions. Space itself has a fourth perpendicular dimension, of which we are unaware in ordinary life. Atoms are 4-polytopes, small round 4-dimensional objects, and stars are 4-balls of atomic plasma, large round 4-dimensional objects. We ourselves and our planet are only 3-dimensional objects, but nonetheless we can see in four dimensions of space. We have been unaware that when we look up at night we see stars and galaxies, themselves large 4-dimensional objects, distributed all around us in 4-dimensional Euclidean space, and moving through it, like us, at the constant velocity <math>c</math>. Light from them reaches us directly, on straight lines through 4-space. This view of the observed universe is compatible with special and general relativity, and with quantum mechanics. It furnishes those theories with an explanatory geometric model.</blockquote> == Summary == We observe that: * Physical space has four perpendicular dimensions, not just three. * Atoms are [[W:4-polytope|4-polytopes]]. * The sun is a [[W:4-ball|4-ball]] that is round in four dimensions. * Everything of intermediate size between an atom and a star, including us and our planet, lies in a 3-dimensional manifold of ordinary space. * Our entire 3-space manifold is moving through Euclidean 4-space at the speed of light, in a direction perpendicular to its three interior dimensions. * Special relativity describes the linear motion of objects and light signals in four-dimensional Euclidean space. == A theory of the Euclidean cosmos == The physical universe is properly visualized as [[w:Four-dimensional_space|real Euclidean space of four orthogonal spatial dimensions]] <math>\mathbb{R}^4</math>. Space itself has a fourth perpendicular dimension, of which we are unaware in ordinary life. Atoms are [[w:4-polytope|4-polytopes]], small round 4-dimensional objects, and stars are [[W:4-ball|4-balls]] of atomic plasma, large round 4-dimensional objects. Objects intermediate in size between atoms and stars, including molecules, people, and planets, are so flat as to be essentially 3-dimensional, having only the thickness of an atom in the orthogonal fourth dimension. All objects with mass move inertially through Euclidean 4-space at constant velocity <math>c</math> as long as they exist, and acceleration only varies their direction. Objects moving in the same direction are in the same inertial reference frame. Their direction of motion through 4-space at velocity <math>c</math> is their proper time dimension, simply because their direction and velocity of motion through time is the same as their direction and velocity of motion through space. A typical galaxy such as ours occupies a 4-ball of mostly empty space, with stars and other objects distributed non-uniformly within it. The galaxy's orbital center may be nothing: a smaller 4-ball of empty space they surround. The stars in our spiral galaxy appear from our accustomed point of view to occupy a disk-like region of 3-dimensional space, with a denser ball-like center, but they are not so confined: they are distributed within a region of 4-dimensional space. The disk and ball have thickness not only in the third dimension, but in the fourth spatial dimension as well. Light from stars and galaxies reaches us on straight lines through Euclidean 4-space, so from our viewpoint, in what we have always imagined to be a 3-space universe, we look into the surrounding 4-space. Although we are physically confined within a 3-dimensional hyperplane by the inertia of our motion through 4-space at constant velocity <math>c</math>, light signals are not so confined, so we observe all the cosmological objects surrounding us, both in and above or below our hyperplane, without perceiving their separation in our fourth orthogonal dimension, the direction of our motion. We may perceive a galaxy as elliptical when it is actually spherical, because that is how its image projects from its 4-ball shape into a 3-ball region in our hyperplane, where we measure it with our 3-dimensional bodies. More generally, orbits are circular in 4-space, but elliptical in the 3-space of their elliptic hyperplane. The galaxy as a whole, or more properly its orbital barycenter, is translating through 4-space at velocity <math>c</math>, in a distinct direction orthogonal to all three dimensions of our ordinary proper 3-space. Stars within the galaxy are translating with it at the same velocity <math>c</math> in the same direction, but on spiral trajectories as they pursue their various orbits within the galaxy. The galaxy as a whole occupies a 4-ball within its proper inertial reference frame (that is, in the moving frame of reference in which the galaxy considers itself to be a stationary rotating 4-ball). Over time, the galaxy 4-ball occupies a 4-dimensional cylinder and progresses along the cylinder's axis at velocity <math>c</math>. In this more universal inertial reference frame, the stars in the galaxy follow helical geodesic paths through the 4-cylinder; their trajectories are screw-translations through 4-space, the compound of a simple rotation and a completely orthogonal linear translation. The gravitational force and the inertial tendency to follow a geodesic are the same phenomenon, by the equivalence principle. That said, they can be distinguished, and the galaxy is held together primarily by gravity as inertia, not by gravity as attraction to a central mass toward which objects fall in orbit. There is not enough mass in the galaxy to hold it together by attraction, there is just enough to bend the stars' trajectories toward each other, in helical orbits around a barycentric axis of motion. It is the tremendous inertial force of stars in translational motion at velocity <math>c</math> that holds the cylinder of motion together, not some invisible dark matter. The observed universe as a whole appears to be a [[W:3-sphere|3-sphere]] expanding radially from a central origin point at velocity <math>c</math>, the invariant velocity of mass-carrying objects through 4-space, also the propagation speed of light relative to any moving 3-space manifold, as measured by all observers. A 3-sphere is a hypersphere in Euclidean 4-space, but the enclosing surface of a 3-sphere is a curved, finite 3-space, dimensionally analogous to the surface of the earth which is a curved, finite 2-space. This 3-sphere could be the domain of our visible cosmos, but of course we do not know for certain that all the cosmological objects we observe lie near the surface of our expanding 3-sphere, since it is only our assumption that they must all have originated in the same big bang long ago. Possibly some of the more distant objects we observe did not, and lie elsewhere, outside our big-bang's 3-sphere of outflying matter or even inside its 3-sphere, below its surface. We cannot assume that all objects in the 4-space universe lie near the surface of the same expanding 3-sphere. For all observers, the conjectured big-bang of their origin corresponds not only to a now-distant point in their proper time past, it also corresponds to a distinct now-distant point in 4-dimensional space: the same point in the same Euclidean 4-space for all observers with the same origin. Our big bang had a distinct origin point in real space as well as in real time. More generally, time and Euclidean 4-space can be measured independently, just as time and Euclidean 3-space were measured classically, without the necessity to combine them as spacetime. The same inertial force which holds the galactic cylinder of motion together also confines us physically to an exceedingly thin three-dimensional surface manifold moving through 4-space at velocity <math>c</math>. All objects in our solar system except the sun itself lie within this thinest three-dimensional manifold, and have only the thickness of an atom in their direction-of-motion fourth dimension. That is why we are 3-dimensional objects ourselves, and why we cannot construct more than three perpendiculars through a single point in our local 3-dimensional space. A spherical region of 4-space is called a [[W:4-ball|4-ball]]. The enclosing surface of a 4-ball of any size is a finite, curved (non-Euclidean) 3-dimensional space called a [[w:3-sphere|3-sphere]]. Our entire big-bang-origin universe appears to be the largest 3-sphere we observe, but each of the cosmological objects within it (including our galaxy and our sun) is contained in a smaller 3-sphere shell of its own, lying (we assume) on the largest 3-sphere embedded in its surface, like a soap bubble on the surface of a larger soap bubble. All the 3-dimensional surfaces are expanding, as the largest 3-sphere inflates at radial velocity <math>c</math>. We ourselves live within such an expanding 3-dimensional surface, in an infinitesimally curved 3-manifold surface embedded in Euclidean 4-space. That surface is the ordinary 3-dimensional space we experience, and it contains the earth, all the planets and the 3-dimensional space between them. Our solar system is only a small patch on the surface of a dimensionally rounder space, although that surface is not infinite. It is curved, and finite, analogous to the way the 2-dimensional surface of the earth -- once thought to be flat -- is curved and finite. Our solar system occupies a small patch on a filmy 4-dimensional soap-bubble of galactic size rounded by gravity, that is thicker-skinned than the diameter of an atom only in the interior of stars and supermassive objects. Our 3-manifold of ordinary space, as a surface within our moving 4-ball galaxy, is translating through 4-space at velocity <math>c</math> with the galaxy, in a distinct direction orthogonal to the manifold's three orthogonal dimensions of interior space. At every material point in the manifold (at every atom), the translation through 4-space is following a geometric law of motion discovered by Coxeter, that governs the propagation of individual objects through Euclidean space by the actions of their symmetry groups. The solar system's atoms of mass are 4-polytopes that are simultaneously rotating and translating, and as they advance together they define a moving 3-dimensional manifold by their own collective inertia, also called gravity, the property of matter's ceaseless propagation through 4-space at the constant velocity <math>c</math>, the universal rate of causality at which quantum events occur, all objects move, and the universe evolves. Any moving 3-dimensional manifold such as ours is an evolving surface boundary that is empty in most places, occupied by single atoms in comparatively fewer places, and occupied by bound complexes of multiple atoms (molecules) in still fewer places. In all these places it is no thicker than one atom in the dimension corresponding to its direction of translation, because molecules are 3-dimensional complexes of atoms that add no thickness to the manifold. Every object which we find occurring naturally in the solar system other than the sun itself, even the largest of 3-dimensional objects a planet, is a 3-dimensional smear of atoms no thicker than one atom in its fourth dimension, the direction of its linear translation through 4-space at velocity <math>c</math>. The moving surface manifold cannot be thicker than one atom at any point unless and until there is enough mass near that point for the force of gravity as attraction to overcome the force of gravity as inertia, allowing atoms to be "heaped up" into larger 4-dimensional objects that form a lump in its moving surface. We have little understanding of such 4-dimensional lumps thicker than one atom, since they occur naturally in our vicinity only in the interior of the sun. In fact the sun is the only such lump occurring naturally in our solar system. We refer to such 4-dimensional lumps of matter as atomic plasma, and have little experimental knowledge of their internal geometry or processes. We know that such a lump as the sun burns at its surface 3-sphere and emits radiation, and we know a good deal about those surface processes which are nuclear atomic processes, but we know almost nothing about its interior 4-ball, a dimensionally rounder enclosed space whose existence we did not suspect. Every moving surface boundary of matter in the observed universe is evolving in four dimensions at velocity <math>c</math>. The current location in 4-space of any of its material objects corresponds to the present moment in the proper time of that object's inertial reference frame. The object's direction of movement at velocity <math>c</math> corresponds to its proper time dimension, which is a spiral over time, not a Euclidean (straight-line) dimension, since its direction is changing in its orbit. Objects with mass of all sizes, from subatomic particles to the largest objects observed in the cosmos, are perpetually in inertial rotational motion in some orbit, and simultaneously in inertial translational motion propagating themselves through 4-space, in two completely orthogonal inertial motions each at the constant universal rate of transformation <math>c</math>. Every object with mass moves relative to universal 4-coordinate Euclidean space on its own distinct geodesic spiral, a screw displacement trajectory that is the compound of its two completely orthogonal inertial motions, a rotation and a translation. Objects without mass such as photons lie off such moving surface boundaries of matter from which they were emitted, and their motion is of a different nature. They are in translational motion at velocity <math>c</math> through all four dimensions concurrently, without any rotational component of motion, so they move through 4-space on straight lines at a compound velocity. The propagation speed of light measured on a straight line through Euclidean 4-space is <math>c\prime = 2c</math>, so we can see in four dimensions, even though we are physically confined to a 3-dimensional manifold that is moving at velocity <math>c</math>. For example, we can look across the center of the mostly-empty 4-ball containing our galaxy and see stars in the opposite sides of its concentric 3-sphere orbital surfaces. We have been unaware that when we look up at night we see stars and galaxies, themselves large 4-dimensional objects, distributed all around us in 4-dimensional Euclidean space, and moving through it, like us, at the constant velocity <math>c</math>. They move in the 4-space direction corresponding to their proper time, perpendicular to all three dimensions of their proper 3-space, and generally the farther they are from us the greater the divergence of their direction of motion from our direction of motion: the greater the relative motion between us and their Hubble redshift. Light from them reaches us directly, propagating on straight lines through 4-space at twice the velocity at which they, and we ourselves, are propagating through 4-space. This physical model of the observed universe is compatible with the theories of special and general relativity, and with the atomic theory of quantum mechanics. It explains those theories geometrically, as expressions of intrinsic symmetries in Euclidean space. == Symmetries == It is common to speak of nature as a web, and so it is, the great web of our physical experiences. Every web must have its root systems somewhere, and nature in this sense must be rooted in the symmetries which underlie physics and geometry, the [[W:Group (mathematics)|mathematics of groups]].{{Sfn|Conway, Burgiel & Goodman-Strauss|2008}} As I understand [[W:Noether's theorem|Noether's theorem]] (which is not mathematically), hers is the deepest meta-theory of nature yet, deeper than [[W:Theory of relativity|Einstein's relativity]] or [[W:Evolution|Darwin's evolution]] or [[W:Euclidean geometry|Euclid's geometry]]. It finds that all fundamental findings in physics are based on conservation laws which can be laid at the doors of distinct [[W:symmetry group |symmetry group]]s. Thus all fundamental systems in physics, as examples [[W:quantum chromodynamics|quantum chromodynamics]] (QCD) the theory of the strong force binding the atomic nucleus and [[W:quantum electrodynamics|quantum electrodynamics]] (QED) the theory of the electromagnetic force, each have a corresponding symmetry [[W:group theory|group theory]] of which they are an expression. [[W:Coxeter group|Coxeter's theory of symmetry groups]] generated by reflections did for geometry what Noether's theorem and Einstein's relativity did for physics. [[W:Coxeter|Coxeter]] showed that Euclidean geometry is based on conservation laws that correspond to distinct symmetry groups, and that their group actions express the principle of relativity. Here is Coxeter's formulation of the motions of objects (their congruent transformations) in an ''n''-dimensional Euclidean space, excerpted:{{Sfn|Coxeter|1973|pp=217-218|loc=§12.2 Congruent transformations}} <blockquote>Let <math>\mathrm{Q}</math> denote a rotation, <math>\mathrm{R}</math> a reflection, <math>\mathrm{T}</math> a translation, and let <math>\mathrm{Q}^q \mathrm{R}^r\mathrm{T}</math> denote a product of several such transformations, all commutative with one another. Then <math>\mathrm{RT}</math> is a glide-reflection (in two or three dimensions), <math>\mathrm{QR}</math> is a rotary-reflection, <math>\mathrm{QT}</math> is a screw-displacement, and <math>\mathrm{Q^2}</math> is a double rotation (in four dimensions).<br> Every orthogonal transformation is expressible as:<br> :<math>\mathrm{Q}^q \mathrm{R}^r</math><br> where <math>(2^q + r \le n)</math>, the number of dimensions.<br> Transformations involving a translation are also expressible as:<br> :<math>\mathrm{Q}^q \mathrm{R}^r \mathrm{T}</math><br> where <math>(2^q + r + 1 \le n)</math>.<br> For <math>(n = 4)</math> in particular, every displacement is either a double rotation <math>\mathrm{Q}^2</math>, or a screw-displacement <math>\mathrm{QT}</math> [where the rotation component <math>\mathrm{Q}</math> is a simple rotation, but the <math>\mathrm{QT}</math> is chiral like a <math>\mathrm{Q^2}</math>]. Every enantiomorphous transformation in 4-space (reversing chirality) is a <math>\mathrm{QRT}</math>.</blockquote> If we begin with this most elemental [[w:Kinematics|kinematics]] of Coxeter's, and also assume the [[W:Galilean relativity|Galilean principle of relativity]], every displacement in 4-space can be viewed as either a <math>\mathrm{Q^2}</math> or a <math>\mathrm{QT}</math>, because we can view any <math>\mathrm{QT}</math> as a <math>\mathrm{Q^2}</math> in a linearly moving (translating) reference frame. Therefore any transformation from one inertial reference frame to another is expressable as a <math>\mathrm{Q^2}</math>. By the same principle, we can view any <math>\mathrm{QT}</math> or <math>\mathrm{Q^2}</math> as an isoclinic (equi-angled) <math>\mathrm{Q^2}</math> by proper choice of reference frame.{{Efn|[[W:Arthur Cayley|Cayley]] showed that any rotation in 4-space can be decomposed into two isoclinic rotations, which intuitively we might see follows from the fact that any transformation from one inertial reference frame to another is expressable as a [[W:SO(4)|rotation in 4-dimensional Euclidean space]].|name=Cayley's rotation factorization into two isoclinic reference frame transformations}} Coxeter's relation is thus a mathematical statement of the principle of relativity, on group-theoretic grounds. It correctly captures the limits to [[W:General relativity|general relativity]], in that we can only exchange the translation (<math>\mathrm{T}</math>) for ''one'' of the two rotations (<math>\mathrm{Q}</math>). An observer in any inertial reference frame can always measure the presence, direction and velocity of ''one'' rotation (<math>\mathrm{Q}</math>) up to uncertainty, and can always distinguish the direction of their own proper time translation (<math>\mathrm{T}</math>). As I understand Coxeter theory (which is not mathematically), the symmetry groups underlying physics seem to have an expression in a [[W:Euclidean space|Euclidean space]] of four [[W:dimension|dimension]]s, that is, they are [[W:Euclidean geometry#Higher dimensions|four-dimensional Euclidean geometry]]. Therefore as I understand that geometry (which is entirely by synthetic methods rather than by Clifford's algebraic methods), the [[W:Atom|atom]] seems to have a distinct Euclidean geometry, such that atoms and their constituent particles are four-dimensional geometric objects (4-polytopes), and nature can be understood in terms of their [[W:group action|group actions]], including centrally their group <math>SO(4)</math> [[W:rotations in 4-dimensional Euclidean space|rotations in 4-dimensional Euclidean space]]. The distinct Coxeter symmetry groups have characteristic <math>SO(4)</math> rotational expressions as the [[W:Regular_4-polytope|regular 4-polytopes]]. Their discrete isoclinic rotations are distinguishing properties of fundamental objects in geometry, relativity and quantum mechanics. For example, atoms exhibit <math>SO(4)</math> symmetries of the discrete isoclinic (equi-angled) double rotations (<math>\mathrm{Q^2}</math>) of a set of regular 4-polytopes that is characteristic of their [[w:Atomic_number|atomic number]]. == Special relativity describes Euclidean 4-space == <blockquote>Our entire model of the universe is built on symmetries. Some, like isotropy (the laws are the same in all directions), homogeneity (same in all places), and time invariance (same at all times) seem natural enough. Even relativity, the Lorentz Invariance that allows everyone to observe a constant speed of light, has an elegance to it that makes it seem natural.<ref>{{Cite book|first=Dave|last=Goldberg|title=The Universe in the Rearview Mirror: How Hidden Symmetries Shape Reality|chapter=§10. Hidden Symmetries: Why some symmetries but not others?|year=2013|publisher=Dutton Penguin Group|isbn=978-0-525-95366-1|ref={{SfnRef|Goldberg|2013}}}}</ref></blockquote> Although the Minkowski spacetime of relativity is a non-Euclidean 4-dimensional space,{{Efn|Spacetime is a non-Euclidean (curved) 4-dimensional space because it consists of three orthogonal space dimensions and a time dimension. The time dimension is not orthogonal to the three spatial dimensions; the time coordinate has the opposite sign to the three space coordinates so spacetime is hyperbolic, not a flat Euclidean 4-space at all.}} it has been noticed that its 3-dimensional space component could be modeled as a [[W:3-sphere|3-sphere]] embedded in 4-dimensional Euclidean (flat) space. That is, we could imagine that the ordinary 3-dimensional space we perceive is the curved 3-dimensional surface of a 4-dimensional ball (since the surface of a 4-ball is a curved 3-dimensional space called a 3-sphere, just as the surface of a 3-ball like the earth is a curved 2-dimensional space called a 2-sphere). This was [[#Origins of the theory|imagined by Einstein]] himself in 1921, as a thought experiment in which he carefully described his fourth orthogonal spatial dimension as merely a mathematical abstraction. Subsequently it was noticed by others (not mainstream physicists) that if physical space were really embedded in Euclidean 4-dimensional space (with our 3-dimensional space embedded in 4-space as some non-Euclidean 3-manifold, not necessarily a 3-sphere), then the Lorentz transformation effects of special relativity (spatial forshortenings and time dilations and so forth) could all be explained by ordinary perspective geometry in 4-dimensional Euclidean space. Special relativity reduces to classical vector space geometry (based on the 4-dimensional version of the Pythagorean theorem), but if and only if every observer is moving through 4-space at a universal constant velocity <math>c</math>, in some 4-space direction.{{Sfn|Yamashita|2023}} This counter-intuitive alternative geometric model of relativity, which has usually been called [[W:Formulations of special relativity#Euclidean relativity|Euclidean relativity]], is motivated by the fact that in every kind of relativity, but originally in Einstein's special relativity, each observer moves on a vector through a Euclidean four-dimensional space consisting of their three proper spatial dimensions and their proper time dimension, and the Pythagorean vector-sum of their motion through this kind of proper 4-space is always <math>c</math>, as measured by all observers from any inertial reference frame.{{Efn|Each observer is stationary in space in their own proper reference frame, while they move at maximum velocity {{Math|c}} through their own proper time. Observed from another reference frame in relative motion, they appear foreshortened in space in their direction of motion, and their clocks appear to be slowed to less than the maximum velocity {{Math|c}}.}} This is the Lorentz invariant, that allows everyone to observe a constant speed of light, regardless of their motion relative to the light source.{{Efn| ...cite Lewis Epstein's elegant explanation of the Lorentz Invariance as observers moving at constant velocity {{Math|c}} through space and proper time.}} But no physicists have taken the leap of claiming that therefore, our universe is physically [[W:Euclidean geometry#Higher dimensions|this kind of Euclidean 4-space]], and that observers are actually moving through it at velocity <math>c</math>. In physics as it has been universally understood, observers are not supposed to be able to move at velocity <math>c</math>. Their motion takes place in 3-space and in universal coordinate time (in Minkowski spacetime), and the cosmos is considered to be a non-Euclidean 3-space, generally a closed (finite) expanding 3-space, but with only three spatial dimensions, not four. In the Euclidean relativity alternative view, however, every observer is always moving at velocity <math>c</math> through the universe, which is real Euclidean 4-dimensional space <math>\mathbb{R}^4</math>. The direction in which they are moving is called their proper time axis.{{Efn|Time in spacetime is universal coordinate time, but there is another kind of time in relativity, the proper time in each inertial reference frame. Your proper time is the time you experience, and every observer has his own proper time; proper time runs at different rates in different inertial reference frames. It runs slower (compared to universal coordinate time) in a gravitational field (according to general relativity), and observers in motion with respect to each other view each other's clocks as running slower than their own clocks (according to special relativity).}} Their movement in time is not just modelled as movement in an abstract fourth dimension (as it is in Minkowski spacetime), their movement in time is isomorphic to their movement through physical space in a distinct direction at velocity <math>c</math>. Two observers' directions of movement through space may be different (or not, if they happen to be going in the same direction). Your proper time dimension is whichever direction you are moving. The other three directions perpendicular to your proper time axis are the three dimensions of your ordinary proper space, which again, will be different directions for you than for other observers moving in a different direction. There are four orthogonal spatial dimensions which we all share, but we share the same orthogonal proper time axis and ordinary proper 3-space axes only if we are at rest with respect to each other, actually moving in the same direction at velocity <math>c</math>, in the same inertial reference frame. Your proper 4-space coordinate system is rotated with respect to another observer's proper 4-space coordinate system, precisely as your vectors (directions of motion) are rotated in Euclidean 4-space with respect to each other, but there are no metric distortions (no Lorentz transformations) between your proper Euclidean 4-space coordinate systems; you are both embedded in the same Euclidean 4-dimensional space <math>\mathbb{R}^4</math>. Lorentz transformations are required only to convert between your respective proper Minkowski spacetime coordinate systems. So in this novel alternate view of relativity, every mass in the universe must be perpetually in motion at velocity <math>c</math> through Euclidean 4-space, along with all the masses in its vicinity that are going in (nearly) the same direction. The entire solar system, for example, must be translating in the fourth dimension at the "speed of light" <math>c</math>, although we do not notice it, since we are all moving in that same direction together. Acceleration of an object varies its direction of motion through 4-space, but never its velocity, which is invariant for all objects with mass. Two objects which are in motion relative to each other are both actually in motion at the same velocity <math>c</math>, but in at least slightly different directions.{{Efn|The angular divergence between two observer's motion vectors is proportional to their relative velocity: the more they diverge, the greater their relative velocity, up to the maximum divergence possible in the space. In Euclidean relativity all observers are in motion at velocity {{Math|c}} relative to universal Cartesian 4-coordinate space, so the maximum relative velocity between two observers is {{Math|2c}} when they are moving in exactly opposite directions in 4-space. This is not a contradiction of special relativity, which limits the maximum relative velocity between two observers to {{Math|c}}, it is the same measurement in different units. Special relativity measures all velocities in Minkowski spacetime (in a non-Euclidean 3-space). Euclidean relativity measures all velocities in Euclidean 4-space.}} In Einstein's relativity, the invariant <math>c</math> is the speed of light through 3-space. In Euclidean relativity, the invariant <math>c</math> is the speed of matter through 4-space! The speed of light through 3-space is also perceived as <math>c</math> by all observers, because they are each living in a moving 3-manifold that is translating through 4-space at velocity <math>c</math>. Despite their extreme differences in viewpoint, Einstein's relativity and Euclidean relativity are equivalent theories in complete agreement with each other, by definition. The two theories make exactly the same special relativity predictions of how observers in different inertial reference frames will perceive each other's motions in time and space. It is beyond the scope of this present paper to show how they also agree on the predictions of general relativity, but it is important to understand that our formulation of Euclidean relativity requires our acceptance of the experimentally verified findings of special relativity, general relativity and quantum mechanics. Our model and the standard model both describe the same geometric relations of space and time based on the same evidence, but as embedded in two very different universal host spaces: Euclidean 4-space versus Minkowski spacetime. In some instances our model provides a geometric explanation for physical phenomena where the standard model has none, as yet. An example is the two models' differing explanations for the gravitational coherence of galaxies: either their inertial motion at velocity <math>c</math>, or their possession of experimentally undetected dark matter. A more central example is our use of Coxeter's kinematics to explain the laws of relativistic motion geometrically. More generally, our model is related to deep geometric properties of number elucidated by Coxeter and other geometers.{{Efn| ...cite Kappraff & Adamson's 2003 paper on The Relationship of the Cotangent Function to Special Relativity Theory, geometry and properties of number,{{Sfn|Kappraff & Adamson|2003|loc=Special Relativity Theory, Geometry and properties of number}} which shows how the Lorentz coefficient is a function of a deep geometric property of number{{Sfn|Kappraff & Adamson|2000|loc=A Fresh Look at Number}} discovered by Steinbach,{{Sfn|Steinbach|1997|loc=Golden Fields: A Case for the Heptagon}} by means of which the root formula of geometry in any Euclidean dimension, the Pythagorean theorem, may be derived solely in terms of the addition of polygon side lengths, without recourse to their products or squares. More generally, Steinbach found that in the relations among regular polytope chords, to add is to multiply; every chord is both the product (quotient) of a pair of chords and the sum (difference) of another pair of chords.}} Euclidean relativity is not even a fringe theory; no physicists or astronomers have adopted it. There are many good reasons why the revolutionary leap to a four orthogonal spatial dimensions viewpoint has not been taken, beginning with the universally observed fact that we can only construct three perpendiculars through a point in our immediate space, which appears to be resolutely 3-dimensional, not 4-dimensional. Euclidean relativity offers a nice geometric explanation of the reasons for the Lorentz transformations, but only at the cost of raising other mysteries, which have been difficult for its aficionados to explain. Another mystery is how light signals between observers in relative motion could "catch up" with the receiver moving on a diverging path through 4-space from the emitter. If both observers are already moving at <math>c</math> (on diverging paths), the propagation speed of light through 4-space between them would have to be greater than <math>c</math>. Euclidean relativity is a revolutionary theory indeed, in which <math>c</math> cannot possibly be the speed of light! We conclude that, for a theory of Euclidean 4-space to be physically viable (that is, for <math>\mathbb{R}^4</math> to be our real space and not merely an abstract mathematical space), the speed of light through Euclidean 4-space must be <math>c\prime = 2c</math>, with massless photons translating through 4-space at twice the speed of mass-carrying objects. Photons must translate the diagonal distance through 4-space along the long diameter of a unit 4-hypercube, in the same time that massive particles translate inertially along the edge (or the radius) of a unit 4-hypercube. This is conceivable in Euclidean 4-space (and in no other Euclidean space of any dimensionality) because the long diagonal of the unit 4-hypercube is the natural number <math>\sqrt{4}</math>. == An object's motion in space is the product of its discrete self-reflections == Coxeter theory describes all the possible motions of an object in space as local functions of the object's discrete geometry (its shape). Coxeter observed that in a Euclidean space of any number of dimensions, any displacement of a geometric object from one place to another, and any rotation of the object from one orientation to another, can be broken down into the product of a number of discrete self-reflections. Any action of a polytope that transforms its position and orientation in space may be measured as a distinct sequence of self-reflections of the object in its own surfaces. Any motion of the object whatsoever may be precisely described as the object propagating itself through space by a discrete sequence of local self-reflections. This is a purely kinematic description of motion which does not give any account of forces acting on the object that cause it to move. Coxeter found that both changes in position (translations) and changes in orientation (rotations) can be broken down into the simplest of all displacements (self-reflections). A translation occurs when an object self-reflects twice, in two distinct surfaces which are parallel to each other. A rotation also occurs when an object self-reflects twice, but in two distinct surfaces which intersect each other. When a object self-reflects once, it turns itself inside out (it reverses its chirality), but in translations and rotations it self-reflects twice, preserving its chirality. Coxeter's laws of kinematics are a geometric counterpart to Newton's algebraic laws of motion in three dimensional Euclidean space. They are helpful because they can be understood as geometric pictures. But they are also a revolutionary advance beyond Newton's laws, because Coxeter formulated them in Euclidean spaces of any number of dimensions. In particular, they give us geometric pictures of all the possible motions of objects in 4-dimensional Euclidean space: <blockquote>Every orthogonal transformation in 4-space is expressible as:<br> :<math>\mathrm{Q}^q \mathrm{R}^r \mathrm{T}^t</math><br> where <math>(2^q + r + t \le 4)</math>. Every displacement is either a double rotation <math>\mathrm{Q}^2</math>, or a screw-displacement <math>\mathrm{QT}</math> [where the rotation component <math>\mathrm{Q}</math> is a simple rotation, but the <math>\mathrm{QT}</math> is chiral like a <math>\mathrm{Q^2}</math>]. Every enantiomorphous transformation in 4-space (reversing chirality) is a <math>\mathrm{QRT}</math>.</blockquote> While this description should be understood as geometric pictures, some of the pictures may not be easy for us to visualize, since we have no physical experience in 4-dimensional space. Rotation (<math>\mathrm{Q}</math>), reflection (<math>\mathrm{R}</math>) and translation (<math>\mathrm{T}</math>) are obvious analogues of what they are in three-dimensional space, but double rotation (<math>\mathrm{Q}^2</math>) is something new and unprecedented in our physical experience, because double rotations cannot occur until there are four or more dimensions of space in which to rotate. A point in 4-space may be in motion on two circles in two completely orthogonal rotation planes simultaneously. Nothing constrains the two circles to be of the same radius, or constrains either circle from being of infinite radius such that the point moves in a straight line within its rotation plane: a translation <math>\mathrm{T}</math> rather than a rotation <math>\mathrm{Q}</math>. The motion of a rigid object defined by multiple points is constrained by its rigidity, such that the radii of both circles may approach infinity, but only one of the two radii may actually reach infinity. Only one of the two rotations may actually be a translation. Four dimensional Euclidean space can contain no such thing as a <math>\mathrm{Q}^2\mathrm{T}</math>. A translating double rotation <math>\mathrm{Q}^2</math>, like a translating simple rotation <math>\mathrm{Q}</math>, is simply a screw translation <math>\mathrm{QT}</math>. That is the essence of the way the principle of relativity operates in Euclidean 4-space. An object which is double-rotating in its own proper inertial reference frame may be seen to be performing nothing more mysterious than a screw translation, when observed from an inertial reference frame from which the object is in relative translational motion. In a universe which is four-dimensional Euclidean space <math>\mathbb{R}^4</math>, wherein these motions occur only at the constant velocity <math>c</math>, there is a universal Cartesian 4-coordinate reference frame in which every rigid object is translating on a <math>\mathrm{QT}</math> at velocity <math>c</math>. That universal inertial reference frame is not the proper reference frame of any object or observer, wherein the object or observer is stationary, but it is the common reference frame of all observers. == Light propagates through 4-space at twice its apparent velocity <math>c</math>== Coxeter's laws of kinematics in 4-dimensional Euclidean space apply to all objects with mass, but we find there is an additional kind of displacement which applies only to massless particles such as photons. Light quanta (photons) translate through 4-space by 4-dimensional reflection <math>\mathrm{R}^4</math>, which may be termed a double translation <math>\mathrm{T}^2</math>, a pure translation via two pairs of parallel reflections without any rotation component <math>\mathrm{Q}</math>. Matter (atoms and all particles with mass) are perpetually rotating and translating through 4-space by <math>\mathrm{QT}</math>, a screw translation of a rotating object, which is relativistically equivalent to a stationary isoclinic <math>\mathrm{Q^2}</math>, an isoclinically rotating object such as an atom. A simple rotation <math>\mathrm{Q}</math> or simple translation <math>\mathrm{T}</math> is a double reflection <math>\mathrm{R^2}</math>, so a <math>\mathrm{QT}</math> or <math>\mathrm{Q^2}</math> is an <math>\mathrm{R^4}</math>, but not with the same group of reflection angles as a light signal <math>\mathrm{R^4}</math>. A translation <math>\mathrm{T = R^2}</math> is a double reflection in two parallel planes, and a rotation <math>\mathrm{Q = R^2}</math> is a double reflection in two intersecting planes, as in a <math>\mathrm{QT = R^4}</math> which is both at once. A double translation <math>\mathrm{T^2 = R^4}</math> is two double reflections in pairs of parallel planes at once, a reflection in four non-intersecting parallel planes; it is all translation and no rotation. In a <math>\mathrm{T^2}</math> all the motion goes to translation, so the translation goes twice as far as the simple translation <math>\mathrm{T}</math> in a <math>\mathrm{QT}</math>. A double translation <math>\mathrm{T^2 = R^4}</math> is the opposite of a double rotation <math>\mathrm{Q^2 = R^4}</math>, which is stationary but rotates twice as far as the simple rotation <math>\mathrm{Q}</math> in a <math>\mathrm{QT}</math>. The product of the two translations in a <math>\mathrm{T^2}</math> is a diagonal 4-space translation over the long diameter of the unit 4-hypercube, exactly twice the distance of a simple <math>\mathrm{T}</math> over the edge length (or radius) of the unit 4-hypercube. The [[w:Tesseract|4-hypercube (also known as the 8-cell or tesseract)]] is ''radially equilateral'', which means its edge length is equal to its radius, like the hexagon, so its long diameter (twice its radius) is exactly twice its edge length. The photon moves an equal distance in four orthogonal directions. By the four-dimensional Pythagorean theorem, each of those four distances is half the total distance the photon moves: one edge length (one radius) is half the total diagonal distance moved (the long diameter). That total movement is a double-the-distance translation, but without any rotation component, so it cannot carry any mass with it. A <math>\mathrm{T^2}</math> cannot reposition a 4-polytope the way a <math>\mathrm{QT}</math> does, it can only reposition a quantum of energy that has no distinguishing rotational symmetry, such as a photon. That is the price light pays to move exactly twice as fast as matter.{{Efn| ...lensing of double translations <math>\mathrm{T^2 = R^4}</math> in more than two pairs of parallel planes at once...relationship to the frequency of light emitted and the coherence length of the wave packet...}} == Special relativity is Galilean relativity in a Euclidean space of four orthogonal dimensions == {{Efn|...TAC suggests this section is needed sooner, i.e. in the preceding Special Relativity section, as it explains how Euclidean relativity reduces special relativity to 4D perspective geometry...it's misplaced (too late) here...}} Perspective effects known as the Lorentz transformations occur because each observer's proper 3-dimensional space is a moving curved manifold embedded in flat 4-dimensional Euclidean space. The curvature of their 3-space complicates sightline calculations for observers; they sometimes require Lorentz transformations to produce the actual 4-space Cartesian coordinates of objects in the scene being observed. But if all four spatial dimensions are considered, no Lorentz transformations are required (or permitted) in correct scene construction, except when an observer wants to calculate a projection, that is, the shadow of how things will appear to them from a three-dimensional viewpoint (not how they really are).{{Sfn|Yamashita|2023}} Space really has four orthogonal dimensions, and space and time behave there just as they do in a classical vector space, only bigger by one dimension. It is not necessary to combine 4-space with time in a unified spacetime to explain 4-dimensional perspective effects at high relative velocities, because Euclidean 4-space is already 4-dimensional, and those effects fall out naturally from the 4-dimensional Pythagorean theorem, exactly as ordinary visual perspective does in three dimensions from the 3-dimensional Pythagorean theorem. Because one of the four spatial dimensions corresponds to an observer's direction of motion (in both space and proper time), and all observers and all scenes being observed are in motion (at constant velocity) in their respective proper time directions, we observe perspective foreshortenings in time as well as in a spatial dimension. In special relativity these perspective effects are reciprocal, precisely because they are only apparent, not actual, changes in size and duration. (In general relativity the actual rate of physical processes varies from place to place, and reference frame differences are neither reciprocal nor illusory.) None of these Lorentz effects are beyond geometric explanation or paradoxical. The universe is unexpectedly strange to us in precisely the ways the Euclidean fourth dimension is strange to us; but that does hold many surprises. Euclidean 4-space is much more interesting than Euclidean 3-space, analogous to the way 3-space is much more interesting and deeply explanatory to us than it would be if we experienced it only as a 2-space with many folds and curves, as perhaps an ant does. The emergent properties of 4-space are hard for us to visualize because they lie so wholly beyond our physical experience, just as it was hard for our ancestors to imagine the earth as round like a ball. However, Euclidean spaces of successive dimensions are analogous, and so higher dimensional spaces can be anticipated and explored: that is Schläfli's great discovery. Moreover dimensional analogy itself, like everything else in nature, is an exact expression of intrinsic group-theoretic symmetries: that is Nother's great discovery. == Dimensional relativity == Coxeter's kinetic law of <math>n</math>-dimensional congruent Euclidean transformations may be called ''dimensional relativity'', since it captures the theories of special and general relativity, and has its roots in dimensional analogy. Dimensional analogy is the exploration of [[w:Hermann_Grassmann#Mathematician|Hermann Grassmann's vector space principle]], in which space cannot be limited to any finite number of dimensions. The geometry of higher-dimensional space is accessable by reason of direct analogy, as [[w:Ludwig Schläfli|Ludwig Schläfli]] subsequently demonstrated. By analogy to the surface of the earth, the bounding surface of a spherical region of <math>n</math>-dimensional Euclidean space is an <math>(n-1)</math>-sphere, a spherical space of one fewer dimensions than the <math>n</math>-ball of Euclidean space it surrounds. In dimensional relativity the sky is not a ceiling, but an infinite regress of alternating spherical and Euclidean <math>n</math>-spaces of increasing <math>n</math>, accessible from each observer's point of view. By dimensional analogy, each observer looks up into their own reference frame's regress of concentric alternating <math>n</math>-spaces. By the capacity for dimensional analogy which they possess, some observers see deeper into <math>n</math>-dimensional space than others. == Polycentric spherical relativity == An intelligent observer equipped with the principle of relativity may perceive the universe from any inertial reference frame, not only from their own proper stationary reference frame in the <math>n</math>-space universe in which they physically locate themself. We see that every observer may also properly view themself as stationary and the universe as an <math>(n+1)</math>-sphere with themself at the center observing it, perceptually equidistant from all points on its <math>n</math>-space surface, including their own physical location which is one of those surface points, distinguished to them but moving on the surface, and not the center of anything. This ''polycentric model'' of the universe is a further restatement of the principle of relativity. It is compatible with Galileo's relativity of uniformly moving objects in ordinary space, Einstein's special relativity of inertial reference frames in 4-dimensional spacetime, Einstein's general relativity of all reference frames in non-Euclidean spacetime, and Coxeter's dimensional relativity of orthogonal group actions in Euclidean and spherical spaces of any number of dimensions. It should be known as Thoreau's principle of ''spherical relativity'', since the first precise written statement of it appears in 1849: "The universe is a sphere whose center is wherever there is intelligence."{{Sfn|Thoreau|1849|p=349|ps=; "The universe is a sphere whose center is wherever there is intelligence." [Contemporaneous and independent of [[W:Ludwig Schlafli|Ludwig Schlafli]]'s pioneering work enumerating the complete set of regular polyschemes in any number of dimensions.]}} == Revolutions == The original Copernican revolution in 1543 displaced the center of the universe from the center of the earth to a point farther away, the center of the sun, with the earth performing a ''revolution'' around the sun, and the stars remaining on a fixed 2-sphere around the sun instead of around the earth. But this led inevitably to the recognition that the sun must be a star itself, not equidistant from all the stars, and the center of but one of many spheres, no monotheistic center at all. In such fashion the Euclidean four-dimensional revolution, emerging three to five centuries later, initially lends itself to the big bang theory of a single origin of the whole universe, but leads inevitably to the recognition that all the galaxies need not be equidistant from a single origin in time, any more than all the stars lie in the same galaxy, equidistant from a single center in space. The expanding sphere of matter on the surface of which we find ourselves living is likely to be one of many 3-spheres expanding at velocity <math>c</math>, with their big bang origins occurring at distinct times and places in the ''n''-dimensional universe. The most distant objects we see when we look up at night may not all have the same origin in space and time. As recently as Copernicus we believed all the stars lay on a single 2-sphere embedded in Euclidean 3-space, with our sun at its center. During the enlightenment we dispersed those stars into an infinite Euclidean 3-space, and relinquished our privileged position at the center. Then Einstein showed that our 3-space could not be Euclidean, that it must be a 3-manifold curved in every place in obedience to Newton's inverse-square law of gravity; and in a geometry related to time, at least, it must be 4-dimensional. In this work we suggest a theory of ''n''-dimensional real space and how light travels in it, a theory which says we can see into four orthogonal dimensions of Euclidean space, and so when we look up at night we see cosmological objects distributed in at least four dimensions of space around us, rather than all located in our own local 3-space. Looking still deeper and farther out, the universe viewed as a 4-sphere might, or might not, be expanding, and the most distant objects we see when we look up at night may, or may not, lie in our 4-dimensional hyperplane. Real space has ''n'' dimensions as [[w:Hermann_Grassmann|Grassmann]] and [[w:Schläfli|Schläfli]] showed, and we do not know how many dimensions the most distant objects we see may be distributed in. They need not all lie within the four spatial dimensions in which we have now learned to observe them, any more than they lie in the three dimensional hyperplane of local space in which we find everything residing in our solar system. When we look up at the objects that surround us, we have no way of discerning how many dimensions beyond three the space we are looking into has. We know their distance from us primarily by virtue of how long it takes their light to reach us. We can measure their distribution around us in 3-space or 4-space, but that is simply how we choose to measure their positions, not an actual finding of how they are distributed. Even if it is now evident that they do not all lie in the same 3-space, how many more dimensions than three are needed to contain them? We observe that our 4-ball galaxy is embedded in Euclidean ''n''-space as one of many 4-ball galaxies, each translating in a distinct direction through 4-space at velocity <math>c</math>, on more or less divergent paths from each other. But only much closer observation will reveal evidence of whether everything we see lies in the same Euclidean 4-space, or if it is distributed in five or more dimensions, and how it is moving there. To remain in agreement with the theory of relativity, the Euclidean four-dimensional viewpoint requires that all mass-carrying objects be in motion in some distinct direction through 4-space at the constant velocity <math>c</math>, although the relative velocity between nearby objects is much smaller since they move on similar vectors, aimed away from a common origin point in the past. It is natural to expect that objects moving at constant velocity away from a common origin will be distributed roughly on the surface of an expanding 3-sphere. Although their paths away from their origin are not straight lines but various helical isoclines (screw translations), nearby objects must be translating radially at the same velocity, since the objects in a system (such as our solar system or galaxy) do not separate rapidly over time but remain in orbital formation. Each system's screw translation has ''two'' [[w:Completely_orthogonal|completely orthogonal]] components of motion in 4-space, an orbital rotation (such as the earth's around our sun) and a linear translation of the entire system at velocity <math>c</math> in the direction of the original 3-sphere's radial expansion (along the system's proper time vector). Of course the view from our solar system does not suggest that each galaxy's own distinct 3-sphere is expanding at this great rate from its galactic center. The standard theory has been that the entire observable universe is expanding from a single big bang origin in time, with galaxies forming later. While the Euclidean four-dimensional viewpoint lends itself to that standard theory, it also supports theories which require no single origin point in space and time. These are the voyages of starship Earth, to boldly go where no one has gone before. We made the jump to lightspeed long ago, in whatever big bang our atoms emerged from, and have never slowed down since. == Origins of the theory == Einstein himself may have been the first to imagine the universe as the three-dimensional surface of a four-dimensional Euclidean 3-sphere, in what was narrowly the first written articulation of the geometry of Euclidean 4-space relativity, contemporaneous with the teen-aged Coxeter's (quoted below).{{Efn|[[W:William Rowan Hamilton|Hamilton]]'s algebra '''H''' of [[W:Quaternions|quaternions]] contains the notion of a [[W:Three-dimensional sphere|three-dimensional sphere]] embedded in a four-dimensional space, but Hamilton did not conceive of the quaternions as the Cartesian 4-coordinates of a Euclidean 4-space, and did not describe our ordinary 3-space as embedded in Euclidean 4-space.}} Einstein did this as a [[W:Gedankenexperiment|gedankenexperiment]] in the context of investigating whether his equations of general relativity predicted an infinite or a finite universe, in his 1921 Princeton lecture.<ref>{{Cite book|url=http://www.gutenberg.org/ebooks/36276|title=The Meaning of Relativity|last=Einstein|first=Albert|publisher=Princeton University Press|year=1923|isbn=|location=|pages=110-111}}</ref> He invited us to imagine "A spherical manifold of three dimensions, embedded in a Euclidean continuum of four dimensions", but he was careful to disclaim parenthetically that "The aid of a fourth space dimension has naturally no significance except that of a mathematical artifice." Informally, the Euclidean 4-dimensional theory of relativity may be given as a sort of reciprocal to that disclaimer of Einstein's: ''The Minkowski spacetime has naturally no significance except that of a mathematical artifice, as an aid to understanding how things will appear to an observer from their perspective; the foreshortenings, clock desynchronizations and other Lorentz transformations it predicts are proper calculations of actual perspective effects; but real space is a flat, Euclidean continuum of four orthogonal spatial dimensions, and in it the ordinary laws of a flat vector space hold (such as the Pythagorean theorem), and all sightline calculations work classically, so long as you consider all four spatial dimensions.'' The Euclidean theory of relativity differs from the special theory of relativity in ascribing to the physical universe a geometry of four or more orthogonal spatial dimensions, rather than the special theory's [[w:Minkowski spacetime|Minkowski spacetime]] geometry, in which three spatial dimensions and a time dimension comprise a unified spacetime of four dimensions. Anco and Maghadam found that <math>SO(4)</math> breaks to <math>\mathbb{S}^3</math> (the 3-sphere) if the energy in the Kepler orbit is negative (an elliptical orbit), and to <math>H^3</math> (Minkowski spacetime) if the energy is positive (a hyperbolic orbit). Therefore the fact that the planets orbit on ellipses in our 3-space suggests that they orbit on a 3-sphere embedded in Euclidean 4-space which is the actual geometry of our physical universe, and Minkowski spacetime is an abstraction; the reciprocal of Einstein's disclaimer is the direct model. Of course spacetime remains a true and useful abstraction, although it must relinquish its privileged position as our exclusive conception of our place in space.{{Efn| ...origins of the Euclidean 4-space insight in the observations of Fock, Atkinson, Moser and others.}} The invention of Euclidean geometry of more than three spatial dimensions preceded Einstein's theories by more than fifty years, when it was worked out originally by the Swiss mathematician [[w:Ludwig Schläfli|Ludwig Schläfli]] before 1853.{{Sfn|Coxeter|1973|loc=§7. Ordinary Polytopes in Higher Space; §7.x. Historical remarks|pp=141-144|ps=; "Practically all the ideas in this chapter ... are due to Schläfli, who discovered them before 1853 — a time when Cayley, Grassmann and Möbius were the only other people who had ever conceived the possibility of geometry in more than three dimensions."}} Schläfli extended Euclid's geometry of one, two, and three dimensions in a direct way to four or more dimensions, generalizing the rules and terms of [[w:Euclidean geometry|Euclidean geometry]] to spaces of any number of dimensions. He coined the general term ''[[polyscheme]]'' to mean geometric forms of any number of dimensions, including two-dimensional [[w:polygon|polygons]], three-dimensional [[w:polyhedron|polyhedra]], four dimensional [[w:polychoron|polychora]], and so on, and in the process he found all of the [[w:Regular polytope|regular polyschemes]] that are possible in every dimension, including in particular the [[User:Dc.samizdat/Rotations#Sequence of regular 4-polytopes|six convex regular polychora]] which can be constructed in a Euclidean space of four dimensions (the set analogous to the five [[w:Platonic solid|Platonic solids]] the ancients found in three dimensional space). Thus Schläfli was the first to explore the fourth dimension, reveal its emergent geometric properties, and discover its astonishing regular objects. Because his work was only published posthumously in 1901, and remained almost completely unknown until Coxeter published [[w:Regular_Polytopes_(book)|Regular Polytopes]] in 1947, other researchers had more than fifty years to rediscover the regular polychora, and competing terms were coined; today [[w:Reinhold_Hoppe|Reinhold Hoppe]]'s word ''[[w:Polytope|polytope]]'' is the commonly used term for ''polyscheme.''{{Efn|[[w:Reinhold_Hoppe|Reinhold Hoppe]]'s German word ''polytop'' was introduced into English by [[W:Alicia Boole Stott|Alicia Boole Stott]], who like Hoppe and [[W:Thorold Gosset|Thorold Gosset]] rediscovered Schlafli's six regular convex 4-polytopes, with no knowledge of their prior discovery. Today Schläfli's original ''polyschem'', with its echo of ''schema'' as in the configurations of information structures, seems even more fitting in its generality than ''polytope'' -- perhaps analogously as information software (programming) is even more general than information hardware (computers).}} Because of this century-long lag in the dissemination of a scientific discovery, the regular 4-polytopes appear to have played no role at all, by any name, in the twentieth century discovery and evolution of the theories of relativity and quantum mechanics.{{Efn|One could argue that the higher-dimensional polytopes have barely influenced science or culture at all thus far. The physicist John Edward Huth's comprehensive deep dive through the history of cultural and scientific concepts of physical space, from ancient flatland models of the world through general relativity and quantum mechancs, shows exactly how we got to our present standard model of the universe, although it includes no mention of higher-dimensional Euclidean space.<ref>{{Cite book|last=Huth|first=John Edward|title=A Sense of Space: A local's guide to a flat earth, the edge of the cosmos, and other curious places|year=2025|publisher=University of Chicago Press}}</ref>}} == Boundaries == <blockquote>Ever since we discovered that Earth is round and turns like a mad-spinning top, we have understood that reality is not as it appears to us: every time we glimpse a new aspect of it, it is a deeply emotional experience. Another veil has fallen.<ref>{{Cite book|author=Carlo Rovelli|author-link=W:Carlo Rovelli|title=Seven Brief Lessons on Physics|publisher=Riverhead|year=2016|isbn=978-0399184413}}</ref></blockquote> Of course it is strange to consciously contemplate this world we inhabit, our planet, our solar system, our 3-sphere surface in our vast galaxy, as the merest film, a boundary no thicker in the places we inhabit than the diameter of an electron (though much thicker in some places we cannot inhabit, such as the interior of stars). But is not our unconscious traditional concept of the boundary of our world even stranger? Since the enlightenment we are accustomed to thinking that there is nothing beyond three dimensional space: no boundary, because there is nothing else to separate us from. But anyone who knows the [[polyscheme]]s Schläfli discovered knows that space can have any number of dimensions, and that there are fundamental objects and motions to be discovered in four dimensions that are even more various and interesting than those we can discover in three. The strange thing, when we think about it that way, is that there ''is'' a boundary between three and four dimensional space. ''Why'' can't we move (or apparently, see) in more than three dimensions? Why is our physical world apparently only three dimensional? Why would it have just ''three'' dimensions, and not four, or five, or the ''n'' dimensions that Schläfli mapped? What is the nature of the boundary which confines us to just three dimensions? We know that in Euclidean geometry the boundary between three and four dimensions is itself a spherical three dimensional space, so we should suspect that we are materially confined within such a curved boundary surface. Light need not be confined with us within our three dimensional boundary space. We would look directly through four dimensional space in our natural way, by receiving light signals that travelled through it to us on straight lines. In that case the reason we do not observe a fourth spatial dimension in our vicinity is that there are no nearby objects in it, just off our hyperplane in the wild. The nearest four-dimensional object we can see with our eyes is our sun, which lies equatorially in our own hyperplane, though it bulges out of it above and below. But when we look up at the heavens, every pinprick of light we observe is itself a four-dimensional object off our hyperplane, and they are distributed all around us in four-dimensional space through which we gaze. We are four-dimensionally sighted creatures, even though our bodies are three-dimensional objects, thin as an atom in the fourth dimension. But that should not perplex us: we can see into three dimensional space even though our retinas are two dimensional objects, thin as a photoreceptor cell. Our unconscious provincial concept is that there is nothing else outside our three dimensional world: no boundary, because there is nothing else to separate us from. But Schläfli discovered something else: all the astonishing regular objects that exist in higher dimensions, which vastly extend our notions of the beauty and mystery of space itself, and the intrinsic spatial symmetries of our universe which geometry reveals. Space is more commodious than we thought it was, and permits previously unimagined objects and motions. So our provincial conception of our place in it now has the same kind of status as our idea that the sun rises in the east and passes overhead: it is mere appearance, not a true model and no longer a proper explanation. An inertial boundary is an explanation, be it ever so thin. And would a boundary of ''no'' thickness, a mere abstraction with no physical power to separate, be a more suitable explanation? We must look for a physically powerful explanation in the geometry of space itself, which general relativity properly associates with the gravitational or inertial force. <blockquote>The number of dimensions possessed by a figure is the number of straight lines each perpendicular to all the others which can be drawn on it. Thus a point has no dimensions, a straight line one, a plane surface two, and a solid three .... In space as we now know it only three lines can be imagined perpendicular to each other. A fourth line, perpendicular to all the other three would be quite invisible and unimaginable to us. We ourselves and all the material things around us probably possess a fourth dimension, of which we are quite unaware. If not, from a four-dimensional point of view we are mere geometrical abstractions, like geometrical surfaces, lines, and points are to us. But this thickness in the fourth dimension must be exceedingly minute, if it exists at all. That is, we could only draw an exceedingly small line perpendicular to our three perpendicular lines, length, breadth and thickness, so small that no microscope could ever perceive it. We can find out something about the conditions of the fourth and higher dimensions if they exist, without being certain that they do exist, by a process which I have termed "Dimensional Analogy."<ref>{{Citation|title=Dimensional Analogy|last=Coxeter|first=Donald|date=February 1923|publisher=Coxeter Fonds, University of Toronto Archives|authorlink=W:Harold Scott MacDonald Coxeter|series=|postscript=|work=}}</ref></blockquote> I believe, but I cannot prove, that we live in real space, which is Schläfli's Euclidean space of ''n'' analogous dimensions. As Grassmann showed first, space cannot be limited to any finite number of dimensions. There will always be higher dimensions to discover, first in imagination and then to explore physically, each an astonishing new enlightenment.<ref>{{Cite book|first=T.S.|last=Eliot|title=Little Gidding|volume=Four Quartets|year=1943}}<blockquote> :We shall not cease from exploration :And the end of all our exploring :Will be to arrive where we started :And know the place for the first time. :Through the unknown, remembered gate :When the last of earth left to discover :Is that which was the beginning; :At the source of the longest river :The voice of the hidden waterfall :And the children in the apple-tree :Not known, because not looked for :But heard, half-heard, in the stillness :Between two waves of the sea. </blockquote></ref> Schläfli discovered every regular convex polytope that exists in any dimension, but that was only the beginning of the story of dimensional analogy, not its end or even the end of its beginning. That project is forever beginning anew. Coxeter discovered that Schläfli's Euclidean space is an expression of intrinsic symmetries, as Noether discovered all of physics is. Kappraff and Adamson discovered that even the sequences of humble regular polygons have fractal complexity. Symmetry itself is chaotic, always reachable but forever beyond our complete grasp. We are on a Wilderness Project, and just at its beginning, but already we observe a Euclidean space of four or more orthogonal spatial dimensions in which all objects with mass move ceaselessly at the constant velocity <math>c</math>, the universal rate at which everything moves, quantum events occur, and each of our proper times evolves. I believe these facts explain the experimentally verified theories of relativity and quantum mechanics, by revealing their unified polycentric geometry, the same way the facts about Copernicus's heliocentric solar system explained the observed motions of the planets, by revealing the geometry of gravity. But others will have to do the math, work out the physics, and perform experiments to prove or disprove all of this, because I don't have the mathematics; entirely unlike Coxeter and Einstein, I am illiterate in those languages. <blockquote> ::::::BEECH :Where my imaginary line :Bends square in woods, an iron spine :And pile of real rocks have been founded. :And off this corner in the wild, :Where these are driven in and piled, :One tree, by being deeply wounded, :Has been impressed as Witness Tree :And made commit to memory :My proof of being not unbounded. :Thus truth's established and borne out, :Though circumstanced with dark and doubt— :Though by a world of doubt surrounded. :::::::—''The Moodie Forester''<ref>{{Cite book|title=A Witness Tree|last=Frost|first=Robert|year=1942|series=The Poetry of Robert Frost|publisher=Holt, Rinehart and Winston|edition=1969|}}</ref> </blockquote> == Appendix: Sequence of regular 4-polytopes == {{Regular convex 4-polytopes|wiki=W:|columns=7}} == ... == {{Efn|In a ''[[W:William Kingdon Clifford|Clifford]] displacement'', also known as an [[W:Rotations in 4-dimensional Euclidean space#Isoclinic rotations|isoclinic rotation]], all the Clifford parallel{{Efn|name=Clifford parallels}} invariant planes are displaced in four orthogonal directions (two completely orthogonal planes) at once: they are rotated by the same angle, and at the same time they are tilted ''sideways'' by that same angle. A [[W:Rotations in 4-dimensional Euclidean space#Isoclinic rotations|Clifford displacement]] is [[W:8-cell#Radial equilateral symmetry|4-dimensionally diagonal]].{{Efn|name=isoclinic 4-dimensional diagonal}} Every plane that is Clifford parallel to one of the completely orthogonal planes (including in this case an entire Clifford parallel bundle of 4 hexagons, but not all 16 hexagons) is invariant under the isoclinic rotation: all the points in the plane rotate in circles but remain in the plane, even as the whole plane tilts sideways. All 16 hexagons rotate by the same angle (though only 4 of them do so invariantly). All 16 hexagons are rotated by 60 degrees, and also displaced sideways by 60 degrees to a Clifford parallel hexagon. All of the other central polygons (e.g. squares) are also displaced to a Clifford parallel polygon 60 degrees away.|name=Clifford displacement}} {{Efn|It is not difficult to visualize four hexagonal planes intersecting at 60 degrees to each other, even in three dimensions. Four hexagonal central planes intersect at 60 degrees in the [[W:cuboctahedron|cuboctahedron]]. Four of the 24-cell's 16 hexagonal central planes (lying in the same 3-dimensional hyperplane) intersect at each of the 24-cell's vertices exactly the way they do at the center of a cuboctahedron. But the ''edges'' around the vertex do not meet as the radii do at the center of a cuboctahedron; the 24-cell has 8 edges around each vertex, not 12, so its vertex figure is the cube, not the cuboctahedron. The 8 edges meet exactly the way 8 edges do at the apex of a canonical [[W:cubic pyramid]|cubic pyramid]].{{Efn|name=24-cell vertex figure}}|name=cuboctahedral hexagons}} {{Efn|name=radially equilateral}} {{Efn|Eight {{sqrt|1}} edges converge in curved 3-dimensional space from the corners of the 24-cell's cubical vertex figure{{Efn|The [[W:vertex figure|vertex figure]] is the facet which is made by truncating a vertex; canonically, at the mid-edges incident to the vertex. But one can make similar vertex figures of different radii by truncating at any point along those edges, up to and including truncating at the adjacent vertices to make a ''full size'' vertex figure. Stillwell defines the vertex figure as "the convex hull of the neighbouring vertices of a given vertex".{{Sfn|Stillwell|2001|p=17}} That is what serves the illustrative purpose here.|name=full size vertex figure}} and meet at its center (the vertex), where they form 4 straight lines which cross there. The 8 vertices of the cube are the eight nearest other vertices of the 24-cell. The straight lines are geodesics: two {{sqrt|1}}-length segments of an apparently straight line (in the 3-space of the 24-cell's curved surface) that is bent in the 4th dimension into a great circle hexagon (in 4-space). Imagined from inside this curved 3-space, the bends in the hexagons are invisible. From outside (if we could view the 24-cell in 4-space), the straight lines would be seen to bend in the 4th dimension at the cube centers, because the center is displaced outward in the 4th dimension, out of the hyperplane defined by the cube's vertices. Thus the vertex cube is actually a [[W:cubic pyramid|cubic pyramid]]. Unlike a cube, it seems to be radially equilateral (like the tesseract and the 24-cell itself): its "radius" equals its edge length.{{Efn|The vertex cubic pyramid is not actually radially equilateral,{{Efn|name=radially equilateral}} because the edges radiating from its apex are not actually its radii: the apex of the [[W:cubic pyramid|cubic pyramid]] is not actually its center, just one of its vertices.}}|name=24-cell vertex figure}} {{Efn|The hexagons are inclined (tilted) at 60 degrees with respect to the unit radius coordinate system's orthogonal planes. Each hexagonal plane contains only ''one'' of the 4 coordinate system axes.{{Efn|Each great hexagon of the 24-cell contains one axis (one pair of antipodal vertices) belonging to each of the three inscribed 16-cells. The 24-cell contains three disjoint inscribed 16-cells, rotated 60° isoclinically{{Efn|name=isoclinic 4-dimensional diagonal}} with respect to each other (so their corresponding vertices are 120° {{=}} {{radic|3}} apart). A [[16-cell#Coordinates|16-cell is an orthonormal ''basis'']] for a 4-dimensional coordinate system, because its 8 vertices define the four orthogonal axes. In any choice of a vertex-up coordinate system (such as the unit radius coordinates used in this article), one of the three inscribed 16-cells is the basis for the coordinate system, and each hexagon has only ''one'' axis which is a coordinate system axis.|name=three basis 16-cells}} The hexagon consists of 3 pairs of opposite vertices (three 24-cell diameters): one opposite pair of ''integer'' coordinate vertices (one of the four coordinate axes), and two opposite pairs of ''half-integer'' coordinate vertices (not coordinate axes). For example: {{indent|17}}({{spaces|2}}0,{{spaces|2}}0,{{spaces|2}}1,{{spaces|2}}0) {{indent|5}}({{spaces|2}}{{sfrac|1|2}},–{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},–{{sfrac|1|2}}){{spaces|3}}({{spaces|2}}{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}}) {{indent|5}}(–{{sfrac|1|2}},–{{sfrac|1|2}},–{{sfrac|1|2}},–{{sfrac|1|2}}){{spaces|3}}(–{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},–{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}}) {{indent|17}}({{spaces|2}}0,{{spaces|2}}0,–1,{{spaces|2}}0)<br> is a hexagon on the ''y'' axis. Unlike the {{sqrt|2}} squares, the hexagons are actually made of 24-cell edges, so they are visible features of the 24-cell.|name=non-orthogonal hexagons|group=}} {{Efn|Visualize the three [[16-cell]]s inscribed in the 24-cell (left, right, and middle), and the rotation which takes them to each other. [[24-cell#Reciprocal constructions from 8-cell and 16-cell|The vertices of the middle 16-cell lie on the (w, x, y, z) coordinate axes]];{{Efn|name=six orthogonal planes of the Cartesian basis}} the other two are rotated 60° [[W:Rotations in 4-dimensional Euclidean space#Isoclinic rotations|isoclinically]] to its left and its right. The 24-vertex 24-cell is a compound of three 16-cells, whose three sets of 8 vertices are distributed around the 24-cell symmetrically; each vertex is surrounded by 8 others (in the 3-dimensional space of the 4-dimensional 24-cell's ''surface''), the way the vertices of a cube surround its center.{{Efn|name=24-cell vertex figure}} The 8 surrounding vertices (the cube corners) lie in other 16-cells: 4 in the other 16-cell to the left, and 4 in the other 16-cell to the right. They are the vertices of two tetrahedra inscribed in the cube, one belonging (as a cell) to each 16-cell. If the 16-cell edges are {{radic|2}}, each vertex of the compound of three 16-cells is {{radic|1}} away from its 8 surrounding vertices in other 16-cells. Now visualize those {{radic|1}} distances as the edges of the 24-cell (while continuing to visualize the disjoint 16-cells). The {{radic|1}} edges form great hexagons of 6 vertices which run around the 24-cell in a central plane. ''Four'' hexagons cross at each vertex (and its antipodal vertex), inclined at 60° to each other.{{Efn|name=cuboctahedral hexagons}} The [[24-cell#Hexagons|hexagons]] are not perpendicular to each other, or to the 16-cells' perpendicular [[24-cell#Squares|square central planes]].{{Efn|name=non-orthogonal hexagons}} The left and right 16-cells form a tesseract.{{Efn|Each pair of the three 16-cells inscribed in the 24-cell forms a 4-dimensional [[W:tesseract|hypercube (a tesseract or 8-cell)]], in [[24-cell#Relationships among interior polytopes|dimensional analogy]] to the way two tetrahedra form a cube: the two 8-vertex 16-cells are inscribed in the 16-vertex tesseract, occupying its alternate vertices. The third 16-cell does not lie within the tesseract; its 8 vertices protrude from the sides of the tesseract, forming a cubic pyramid on each of the tesseract's cubic cells. The three pairs of 16-cells form three tesseracts.{{Efn|name=three 8-cells}} The tesseracts share vertices, but the 16-cells are completely disjoint.{{Efn|name=completely disjoint}}|name=three 16-cells form three tesseracts}} Two 16-cells have vertex-pairs which are one {{radic|1}} edge (one hexagon edge) apart. But a [[24-cell#Simple rotations|''simple'' rotation]] of 60° will not take one whole 16-cell to another 16-cell, because their vertices are 60° apart in different directions, and a simple rotation has only one hexagonal plane of rotation. One 16-cell ''can'' be taken to another 16-cell by a 60° [[24-cell#Isoclinic rotations|''isoclinic'' rotation]], because an isoclinic rotation is [[3-sphere]] symmetric: four [[24-cell#Clifford parallel polytopes|Clifford parallel hexagonal planes]] rotate together, but in four different rotational directions,{{Efn|name=Clifford displacement}} taking each 16-cell to another 16-cell. But since an isoclinic 60° rotation is a ''diagonal'' rotation by 60° in ''two'' completely orthogonal directions at once,{{Efn|name=isoclinic geodesic}} the corresponding vertices of the 16-cell and the 16-cell it is taken to are 120° apart: ''two'' {{radic|1}} hexagon edges (or one {{radic|3}} hexagon chord) apart, not one {{radic|1}} edge (60°) apart as in a simple rotation.{{Efn|name=isoclinic 4-dimensional diagonal}} By the [[W:chiral|chiral]] diagonal nature of isoclinic rotations, the 16-cell ''cannot'' reach the adjacent 16-cell by rotating toward it; it can only reach the 16-cell ''beyond'' it. But of course, the 16-cell beyond the 16-cell to its right is the 16-cell to its left. So a 60° isoclinic rotation ''will'' take every 16-cell to another 16-cell: a 60° ''right'' isoclinic rotation will take the middle 16-cell to the 16-cell we may have originally visualized as the ''left'' 16-cell, and a 60° ''left'' isoclinic rotation will take the middle 16-cell to the 16-cell we visualized as the ''right'' 16-cell. (If so, that was our error in visualization; the 16-cell to the "left" is in fact the one reached by the left isoclinic rotation, as that is the only sense in which the two 16-cells are left or right of each other.)|name=three isoclinic 16-cells}} {{Efn|In a double rotation each vertex can be said to move along two completely orthogonal great circles at the same time, but it does not stay within the central plane of either of those original great circles; rather, it moves along a helical geodesic that traverses diagonally between great circles. The two completely orthogonal planes of rotation are said to be ''invariant'' because the points in each stay in the plane ''as the plane moves'', tilting sideways by the same angle that the other plane rotates.|name=helical geodesic}} {{Efn|A point under isoclinic rotation traverses the diagonal{{Efn|name=isoclinic 4-dimensional diagonal}} straight line of a single '''isoclinic geodesic''', reaching its destination directly, instead of the bent line of two successive '''simple geodesics'''. A '''[[W:geodesic|geodesic]]''' is the ''shortest path'' through a space (intuitively, a string pulled taught between two points). Simple geodesics are great circles lying in a central plane (the only kind of geodesics that occur in 3-space on the 2-sphere). Isoclinic geodesics are different: they do ''not'' lie in a single plane; they are 4-dimensional [[W:helix|spirals]] rather than simple 2-dimensional circles.{{Efn|name=helical geodesic}} But they are not like 3-dimensional [[W:screw threads|screw threads]] either, because they form a closed loop like any circle (after ''two'' revolutions). Isoclinic geodesics are ''4-dimensional great circles'', and they are just as circular as 2-dimensional circles: in fact, twice as circular, because they curve in a circle in two completely orthogonal directions at once.{{Efn|Isoclinic geodesics are ''4-dimensional great circles'' in the sense that they are 1-dimensional geodesic ''lines'' that curve in 4-space in two completely orthogonal planes at once. They should not be confused with ''great 2-spheres'',{{Sfn|Stillwell|2001|p=24}} which are the 4-dimensional analogues of 2-dimensional great circles (great 1-spheres).}} These '''isoclines''' are geodesic 1-dimensional lines embedded in a 4-dimensional space. On the 3-sphere{{Efn|All isoclines are geodesics, and isoclines on the 3-sphere are circles (curving equally in each dimension), but not all isoclines on 3-manifolds in 4-space are circles.}} they always occur in [[W:chiral|chiral]] pairs and form a pair of [[W:Villarceau circle|Villarceau circle]]s on the [[W:Clifford torus|Clifford torus]],{{Efn|Isoclines on the 3-sphere occur in non-intersecting chiral pairs. A left and a right isocline form a [[W:Hopf link|Hopf link]] called the {1,1} torus knot{{Sfn|Dorst|2019|loc=§1. Villarceau Circles|p=44|ps=; "In mathematics, the path that the (1, 1) knot on the torus traces is also known as a [[W:Villarceau circle|Villarceau circle]]. Villarceau circles are usually introduced as two intersecting circles that are the cross-section of a torus by a well-chosen plane cutting it. Picking one such circle and rotating it around the torus axis, the resulting family of circles can be used to rule the torus. By nesting tori smartly, the collection of all such circles then form a [[W:Hopf fibration|Hopf fibration]].... we prefer to consider the Villarceau circle as the (1, 1) torus knot [a [[W:Hopf link|Hopf link]]] rather than as a planar cut [two intersecting circles]."}} in which ''each'' of the two linked circles traverses all four dimensions.}} the paths of the left and the right [[W:Rotations in 4-dimensional Euclidean space#Double rotations|isoclinic rotation]]. They are [[W:Helix|helices]] bent into a [[W:Möbius strip|Möbius loop]] in the fourth dimension, taking a diagonal [[W:Winding number|winding route]] twice around the 3-sphere through the non-adjacent vertices of a 4-polytope's [[W:Skew polygon#Regular skew polygons in four dimensions|skew polygon]].|name=isoclinic geodesic}} {{Efn|[[File:Hopf band wikipedia.png|thumb|150px|Two [[W:Clifford parallel|Clifford parallel]] great circles spanned by a twisted [[W:Annulus (mathematics)|annulus]].]][[W:Clifford parallel|Clifford parallel]]s are non-intersecting curved lines that are parallel in the sense that the perpendicular (shortest) distance between them is the same at each point. A double helix is an example of Clifford parallelism in ordinary 3-dimensional Euclidean space. In 4-space Clifford parallels occur as geodesic great circles on the [[W:3-sphere|3-sphere]].{{Sfn|Kim|Rote|2016|pp=8-10|loc=Relations to Clifford Parallelism}} Whereas in 3-dimensional space, any two geodesic great circles on the [[W:2-sphere|2-sphere]] will always intersect at two antipodal points, in 4-dimensional space not all great circles intersect. In 4-polytopes various discrete sets of Clifford parallel non-intersecting geodesic great circles can be found on the 3-sphere. They spiral around each other in [[W:Hopf fibration|Hopf fiber bundles]] which visit all the vertices just once. The simplest example is that six mutually orthogonal great circles can be drawn on the 3-sphere, as three pairs of completely orthogonal great circles, intersecting at 8 points defining a [[16-cell]]. Each completely orthogonal pair of circles is Clifford parallel. They cannot intersect at all, because they lie in planes which intersect at only one point: the center of the 16-cell. Because they are perpendicular and share a common center, the two circles are obviously not parallel and separate in the usual way of parallel circles in 3 dimensions; rather they are connected like adjacent links in a chain, each passing through the other without intersecting at any points, forming a [[W:Hopf link|Hopf link]]|name=Clifford parallels}} {{Efn|In the 24-cell each great square plane is completely orthogonal{{Efn|name=completely orthogonal planes}} to another great square plane, and each great hexagon plane is completely orthogonal to a plane which intersects only two vertices: a great [[W:digon|digon]] plane.|name=pairs of completely orthogonal planes}} {{Efn|In an [[24-cell#Isoclinic rotations|isoclinic rotation]], each point anywhere in the 4-polytope moves an equal distance in four orthogonal directions at once, on a [[W:8-cell#Radial equilateral symmetry|4-dimensional diagonal]]. The point is displaced a total [[W:Pythagorean distance]] equal to the square root of four times the square of that distance. For example, when the unit-radius 24-cell rotates isoclinically 60° in a hexagon invariant plane and 60° in its completely orthogonal invariant plane,{{Efn|name=pairs of completely orthogonal planes}} all vertices are displaced to a vertex two edge lengths away. Each vertex is displaced to another vertex {{radic|3}} (120°) away, moving {{radic|3/4}} in four orthogonal coordinate directions.|name=isoclinic 4-dimensional diagonal}} {{Efn|Each square plane is isoclinic (Clifford parallel) to five other square planes but completely orthogonal{{Efn|name=completely orthogonal planes}} to only one of them.{{Efn|name=Clifford parallel squares in the 16-cell and 24-cell}} Every pair of completely orthogonal planes has Clifford parallel great circles, but not all Clifford parallel great circles are orthogonal (e.g., none of the hexagonal geodesics in the 24-cell are mutually orthogonal).|name=only some Clifford parallels are orthogonal}} {{Efn|In the [[16-cell#Rotations|16-cell]] the 6 orthogonal great squares form 3 pairs of completely orthogonal great circles; each pair is Clifford parallel. In the 24-cell, the 3 inscribed 16-cells lie rotated 60 degrees isoclinically{{Efn|name=isoclinic 4-dimensional diagonal}} with respect to each other; consequently their corresponding vertices are 120 degrees apart on a hexagonal great circle. Pairing their vertices which are 90 degrees apart reveals corresponding square great circles which are Clifford parallel. Each of the 18 square great circles is Clifford parallel not only to one other square great circle in the same 16-cell (the completely orthogonal one), but also to two square great circles (which are completely orthogonal to each other) in each of the other two 16-cells. (Completely orthogonal great circles are Clifford parallel, but not all Clifford parallels are orthogonal.{{Efn|name=only some Clifford parallels are orthogonal}}) A 60 degree isoclinic rotation of the 24-cell in hexagonal invariant planes takes each square great circle to a Clifford parallel (but non-orthogonal) square great circle in a different 16-cell.|name=Clifford parallel squares in the 16-cell and 24-cell}} {{Efn|In 4 dimensional space we can construct 4 perpendicular axes and 6 perpendicular planes through a point. Without loss of generality, we may take these to be the axes and orthogonal central planes of a (w, x, y, z) Cartesian coordinate system. In 4 dimensions we have the same 3 orthogonal planes (xy, xz, yz) that we have in 3 dimensions, and also 3 others (wx, wy, wz). Each of the 6 orthogonal planes shares an axis with 4 of the others, and is ''completely orthogonal'' to just one of the others: the only one with which it does not share an axis. Thus there are 3 pairs of completely orthogonal planes: xy and wz intersect only at the origin; xz and wy intersect only at the origin; yz and wx intersect only at the origin.|name=six orthogonal planes of the Cartesian basis}} {{Efn|Two planes in 4-dimensional space can have four possible reciprocal positions: (1) they can coincide (be exactly the same plane); (2) they can be parallel (the only way they can fail to intersect at all); (3) they can intersect in a single line, as two non-parallel planes do in 3-dimensional space; or (4) '''they can intersect in a single point'''{{Efn|To visualize how two planes can intersect in a single point in a four dimensional space, consider the Euclidean space (w, x, y, z) and imagine that the w dimension represents time rather than a spatial dimension. The xy central plane (where w{{=}}0, z{{=}}0) shares no axis with the wz central plane (where x{{=}}0, y{{=}}0). The xy plane exists at only a single instant in time (w{{=}}0); the wz plane (and in particular the w axis) exists all the time. Thus their only moment and place of intersection is at the origin point (0,0,0,0).|name=how planes intersect at a single point}} (and they ''must'', if they are completely orthogonal).{{Efn|Two flat planes A and B of a Euclidean space of four dimensions are called ''completely orthogonal'' if and only if every line in A is orthogonal to every line in B. In that case the planes A and B intersect at a single point O, so that if a line in A intersects with a line in B, they intersect at O.{{Efn|name=six orthogonal planes of the Cartesian basis}}|name=completely orthogonal planes}}|name=how planes intersect}} {{Efn|Polytopes are '''completely disjoint''' if all their ''element sets'' are disjoint: they do not share any vertices, edges, faces or cells. They may still overlap in space, sharing 4-content, volume, area, or lineage.|name=completely disjoint}} {{Efn|If the [[W:Euclidean distance|Pythagorean distance]] between any two vertices is {{sqrt|1}}, their geodesic distance is 1; they may be two adjacent vertices (in the curved 3-space of the surface), or a vertex and the center (in 4-space). If their Pythagorean distance is {{sqrt|2}}, their geodesic distance is 2 (whether via 3-space or 4-space, because the path along the edges is the same straight line with one 90^o bend in it as the path through the center). If their Pythagorean distance is {{sqrt|3}}, their geodesic distance is still 2 (whether on a hexagonal great circle past one 60^o bend, or as a straight line with one 60^o bend in it through the center). Finally, if their Pythagorean distance is {{sqrt|4}}, their geodesic distance is still 2 in 4-space (straight through the center), but it reaches 3 in 3-space (by going halfway around a hexagonal great circle).|name=Geodesic distance}} {{Efn|Two angles are required to fix the relative positions of two planes in 4-space.{{Sfn|Kim|Rote|2016|p=7|loc=§6 Angles between two Planes in 4-Space|ps=; "In four (and higher) dimensions, we need two angles to fix the relative position between two planes. (More generally, ''k'' angles are defined between ''k''-dimensional subspaces.)"}} Since all planes in the same [[W:hyperplane|hyperplane]] are 0 degrees apart in one of the two angles, only one angle is required in 3-space. Great hexagons in different hyperplanes are 60 degrees apart in ''both'' angles. Great squares in different hyperplanes are 90 degrees apart in ''both'' angles (completely orthogonal){{Efn|name=completely orthogonal planes}} or 60 degrees apart in ''both'' angles.{{Efn||name=Clifford parallel squares in the 16-cell and 24-cell}} Planes which are separated by two equal angles are called ''isoclinic''. Planes which are isoclinic have [[W:Clifford parallel|Clifford parallel]] great circles.{{Efn|name=Clifford parallels}} A great square and a great hexagon in different hyperplanes are neither isoclinic nor Clifford parallel; they are separated by a 90 degree angle ''and'' a 60 degree angle.|name=two angles between central planes}} {{Efn|The 24-cell contains 3 distinct 8-cells (tesseracts), rotated 60° isoclinically with respect to each other. The corresponding vertices of two 8-cells are {{radic|3}} (120°) apart. Each 8-cell contains 8 cubical cells, and each cube contains four {{radic|3}} chords (its long diagonals). The 8-cells are not completely disjoint{{Efn|name=completely disjoint}} (they share vertices), but each cube and each {{radic|3}} chord belongs to just one 8-cell. The {{radic|3}} chords joining the corresponding vertices of two 8-cells belong to the third 8-cell.|name=three 8-cells}} {{Efn|Departing from any vertex V₀ in the original great hexagon plane of isoclinic rotation P₀, the first vertex reached V₁ is 120 degrees away along a {{radic|3}} chord lying in a different hexagonal plane P₁. P₁ is inclined to P₀ at a 60° angle.{{Efn|P₀ and P₁ lie in the same hyperplane (the same central cuboctahedron) so their other angle of separation is 0.{{Efn|name=two angles between central planes}}}} The second vertex reached V₂ is 120 degrees beyond V₁ along a second {{radic|3}} chord lying in another hexagonal plane P₂ that is Clifford parallel to P₀.{{Efn|P₀ and P₂ are 60° apart in ''both'' angles of separation.{{Efn|name=two angles between central planes}} Clifford parallel planes are isoclinic (which means they are separated by two equal angles), and their corresponding vertices are all the same distance apart. Although V₀ and V₂ are ''two'' {{radic|3}} chords apart{{Efn|V₀ and V₂ are two {{radic|3}} chords apart on the geodesic path of this rotational isocline, but that is not the shortest geodesic path between them. In the 24-cell, it is impossible for two vertices to be more distant than ''one'' {{radic|3}} chord, unless they are antipodal vertices {{radic|4}} apart.{{Efn|name=Geodesic distance}} V₀ and V₂ are ''one'' {{radic|3}} chord apart on some other isocline. More generally, isoclines are geodesics because the distance between their ''adjacent'' vertices is the shortest distance between those two vertices, but a path between two vertices along a geodesic is not always the shortest distance between them (even on ordinary great circle geodesics).}}, P₀ and P₂ are just one {{radic|1}} edge apart (at every pair of ''nearest'' vertices).}} (Notice that V₁ lies in both intersecting planes P₁ and P₂, as V₀ lies in both P₀ and P₁. But P₀ and P₂ have ''no'' vertices in common; they do not intersect.) The third vertex reached V₃ is 120 degrees beyond V₂ along a third {{radic|3}} chord lying in another hexagonal plane P₃ that is Clifford parallel to P₁. The three {{radic|3}} chords lie in different 8-cells.{{Efn|name=three 8-cells}} V₀ to V₃ is a 360° isoclinic rotation.|name=360 degree geodesic path visiting 3 hexagonal planes}} {{Sfn|Mamone, Pileio & Levitt|2010|loc=§4.5 Regular Convex 4-Polytopes|pp=1438-1439|ps=; the 24-cell has 1152 symmetry operations (rotations and reflections) as enumerated in Table 2, symmetry group 𝐹₄.}} ==Notes== {{Regular convex 4-polytopes Notelist|wiki=W:}} ==Citations== {{Regular convex 4-polytopes Reflist|wiki=W:}} ==References== {{Refbegin}} * {{Cite book|title=A Week on the Concord and Merrimack Rivers|last=Thoreau|first=Henry David|author-link=W:Thoreau|publisher=James Munroe and Company|year=1849|isbn=|location=Boston|ref={{SfnRef|Thoreau|1849}}}} * {{Cite journal|title=Theoretical Evidence for Principles of Special Relativity Based on Isotropic and Uniform Four-Dimensional Space|first=Takuya|last=Yamashita|date=25 May 2023|doi= 10.20944/preprints202305.1785.v1|journal=Preprints|volume=2023|issue=2023051785|url=https://doi.org/10.20944/preprints202305.1785.v1}} * {{Cite_arXiv | arxiv=2512.02903v2 | date=2 January 2026 | title=Symmetry transformation group arising from the Laplace–Runge–Lenz vector | first1=Stephen C. | last1=Anco | first2=Mahdieh Gol Bashmani | last2=Moghadam | class=math-ph}} === [[Polyscheme|Polyschemes]] === {{Regular convex 4-polytopes Refs|wiki=W:}} {{Refend}} 9hr1kwaaoqrbw34akzfseoolracfj6m 2835211 2835210 2026-09-30T16:28:05Z Dc.samizdat 2856930 /* An object's motion in space is the product of its discrete self-reflections */ 2835211 wikitext text/x-wiki {{align|center|David Brooks Christie}} {{align|center|dc@samizdat.org}} {{align|center|Draft in progress}} {{align|center|June 2023 - September 2026}} <blockquote>'''Abstract:''' The physical universe is properly visualized as Euclidean space <math>\mathbb{R}^4</math> of four orthogonal spatial dimensions. Space itself has a fourth perpendicular dimension, of which we are unaware in ordinary life. Atoms are 4-polytopes, small round 4-dimensional objects, and stars are 4-balls of atomic plasma, large round 4-dimensional objects. We ourselves and our planet are only 3-dimensional objects, but nonetheless we can see in four dimensions of space. We have been unaware that when we look up at night we see stars and galaxies, themselves large 4-dimensional objects, distributed all around us in 4-dimensional Euclidean space, and moving through it, like us, at the constant velocity <math>c</math>. Light from them reaches us directly, on straight lines through 4-space. This view of the observed universe is compatible with special and general relativity, and with quantum mechanics. It furnishes those theories with an explanatory geometric model.</blockquote> == Summary == We observe that: * Physical space has four perpendicular dimensions, not just three. * Atoms are [[W:4-polytope|4-polytopes]]. * The sun is a [[W:4-ball|4-ball]] that is round in four dimensions. * Everything of intermediate size between an atom and a star, including us and our planet, lies in a 3-dimensional manifold of ordinary space. * Our entire 3-space manifold is moving through Euclidean 4-space at the speed of light, in a direction perpendicular to its three interior dimensions. * Special relativity describes the linear motion of objects and light signals in four-dimensional Euclidean space. == A theory of the Euclidean cosmos == The physical universe is properly visualized as [[w:Four-dimensional_space|real Euclidean space of four orthogonal spatial dimensions]] <math>\mathbb{R}^4</math>. Space itself has a fourth perpendicular dimension, of which we are unaware in ordinary life. Atoms are [[w:4-polytope|4-polytopes]], small round 4-dimensional objects, and stars are [[W:4-ball|4-balls]] of atomic plasma, large round 4-dimensional objects. Objects intermediate in size between atoms and stars, including molecules, people, and planets, are so flat as to be essentially 3-dimensional, having only the thickness of an atom in the orthogonal fourth dimension. All objects with mass move inertially through Euclidean 4-space at constant velocity <math>c</math> as long as they exist, and acceleration only varies their direction. Objects moving in the same direction are in the same inertial reference frame. Their direction of motion through 4-space at velocity <math>c</math> is their proper time dimension, simply because their direction and velocity of motion through time is the same as their direction and velocity of motion through space. A typical galaxy such as ours occupies a 4-ball of mostly empty space, with stars and other objects distributed non-uniformly within it. The galaxy's orbital center may be nothing: a smaller 4-ball of empty space they surround. The stars in our spiral galaxy appear from our accustomed point of view to occupy a disk-like region of 3-dimensional space, with a denser ball-like center, but they are not so confined: they are distributed within a region of 4-dimensional space. The disk and ball have thickness not only in the third dimension, but in the fourth spatial dimension as well. Light from stars and galaxies reaches us on straight lines through Euclidean 4-space, so from our viewpoint, in what we have always imagined to be a 3-space universe, we look into the surrounding 4-space. Although we are physically confined within a 3-dimensional hyperplane by the inertia of our motion through 4-space at constant velocity <math>c</math>, light signals are not so confined, so we observe all the cosmological objects surrounding us, both in and above or below our hyperplane, without perceiving their separation in our fourth orthogonal dimension, the direction of our motion. We may perceive a galaxy as elliptical when it is actually spherical, because that is how its image projects from its 4-ball shape into a 3-ball region in our hyperplane, where we measure it with our 3-dimensional bodies. More generally, orbits are circular in 4-space, but elliptical in the 3-space of their elliptic hyperplane. The galaxy as a whole, or more properly its orbital barycenter, is translating through 4-space at velocity <math>c</math>, in a distinct direction orthogonal to all three dimensions of our ordinary proper 3-space. Stars within the galaxy are translating with it at the same velocity <math>c</math> in the same direction, but on spiral trajectories as they pursue their various orbits within the galaxy. The galaxy as a whole occupies a 4-ball within its proper inertial reference frame (that is, in the moving frame of reference in which the galaxy considers itself to be a stationary rotating 4-ball). Over time, the galaxy 4-ball occupies a 4-dimensional cylinder and progresses along the cylinder's axis at velocity <math>c</math>. In this more universal inertial reference frame, the stars in the galaxy follow helical geodesic paths through the 4-cylinder; their trajectories are screw-translations through 4-space, the compound of a simple rotation and a completely orthogonal linear translation. The gravitational force and the inertial tendency to follow a geodesic are the same phenomenon, by the equivalence principle. That said, they can be distinguished, and the galaxy is held together primarily by gravity as inertia, not by gravity as attraction to a central mass toward which objects fall in orbit. There is not enough mass in the galaxy to hold it together by attraction, there is just enough to bend the stars' trajectories toward each other, in helical orbits around a barycentric axis of motion. It is the tremendous inertial force of stars in translational motion at velocity <math>c</math> that holds the cylinder of motion together, not some invisible dark matter. The observed universe as a whole appears to be a [[W:3-sphere|3-sphere]] expanding radially from a central origin point at velocity <math>c</math>, the invariant velocity of mass-carrying objects through 4-space, also the propagation speed of light relative to any moving 3-space manifold, as measured by all observers. A 3-sphere is a hypersphere in Euclidean 4-space, but the enclosing surface of a 3-sphere is a curved, finite 3-space, dimensionally analogous to the surface of the earth which is a curved, finite 2-space. This 3-sphere could be the domain of our visible cosmos, but of course we do not know for certain that all the cosmological objects we observe lie near the surface of our expanding 3-sphere, since it is only our assumption that they must all have originated in the same big bang long ago. Possibly some of the more distant objects we observe did not, and lie elsewhere, outside our big-bang's 3-sphere of outflying matter or even inside its 3-sphere, below its surface. We cannot assume that all objects in the 4-space universe lie near the surface of the same expanding 3-sphere. For all observers, the conjectured big-bang of their origin corresponds not only to a now-distant point in their proper time past, it also corresponds to a distinct now-distant point in 4-dimensional space: the same point in the same Euclidean 4-space for all observers with the same origin. Our big bang had a distinct origin point in real space as well as in real time. More generally, time and Euclidean 4-space can be measured independently, just as time and Euclidean 3-space were measured classically, without the necessity to combine them as spacetime. The same inertial force which holds the galactic cylinder of motion together also confines us physically to an exceedingly thin three-dimensional surface manifold moving through 4-space at velocity <math>c</math>. All objects in our solar system except the sun itself lie within this thinest three-dimensional manifold, and have only the thickness of an atom in their direction-of-motion fourth dimension. That is why we are 3-dimensional objects ourselves, and why we cannot construct more than three perpendiculars through a single point in our local 3-dimensional space. A spherical region of 4-space is called a [[W:4-ball|4-ball]]. The enclosing surface of a 4-ball of any size is a finite, curved (non-Euclidean) 3-dimensional space called a [[w:3-sphere|3-sphere]]. Our entire big-bang-origin universe appears to be the largest 3-sphere we observe, but each of the cosmological objects within it (including our galaxy and our sun) is contained in a smaller 3-sphere shell of its own, lying (we assume) on the largest 3-sphere embedded in its surface, like a soap bubble on the surface of a larger soap bubble. All the 3-dimensional surfaces are expanding, as the largest 3-sphere inflates at radial velocity <math>c</math>. We ourselves live within such an expanding 3-dimensional surface, in an infinitesimally curved 3-manifold surface embedded in Euclidean 4-space. That surface is the ordinary 3-dimensional space we experience, and it contains the earth, all the planets and the 3-dimensional space between them. Our solar system is only a small patch on the surface of a dimensionally rounder space, although that surface is not infinite. It is curved, and finite, analogous to the way the 2-dimensional surface of the earth -- once thought to be flat -- is curved and finite. Our solar system occupies a small patch on a filmy 4-dimensional soap-bubble of galactic size rounded by gravity, that is thicker-skinned than the diameter of an atom only in the interior of stars and supermassive objects. Our 3-manifold of ordinary space, as a surface within our moving 4-ball galaxy, is translating through 4-space at velocity <math>c</math> with the galaxy, in a distinct direction orthogonal to the manifold's three orthogonal dimensions of interior space. At every material point in the manifold (at every atom), the translation through 4-space is following a geometric law of motion discovered by Coxeter, that governs the propagation of individual objects through Euclidean space by the actions of their symmetry groups. The solar system's atoms of mass are 4-polytopes that are simultaneously rotating and translating, and as they advance together they define a moving 3-dimensional manifold by their own collective inertia, also called gravity, the property of matter's ceaseless propagation through 4-space at the constant velocity <math>c</math>, the universal rate of causality at which quantum events occur, all objects move, and the universe evolves. Any moving 3-dimensional manifold such as ours is an evolving surface boundary that is empty in most places, occupied by single atoms in comparatively fewer places, and occupied by bound complexes of multiple atoms (molecules) in still fewer places. In all these places it is no thicker than one atom in the dimension corresponding to its direction of translation, because molecules are 3-dimensional complexes of atoms that add no thickness to the manifold. Every object which we find occurring naturally in the solar system other than the sun itself, even the largest of 3-dimensional objects a planet, is a 3-dimensional smear of atoms no thicker than one atom in its fourth dimension, the direction of its linear translation through 4-space at velocity <math>c</math>. The moving surface manifold cannot be thicker than one atom at any point unless and until there is enough mass near that point for the force of gravity as attraction to overcome the force of gravity as inertia, allowing atoms to be "heaped up" into larger 4-dimensional objects that form a lump in its moving surface. We have little understanding of such 4-dimensional lumps thicker than one atom, since they occur naturally in our vicinity only in the interior of the sun. In fact the sun is the only such lump occurring naturally in our solar system. We refer to such 4-dimensional lumps of matter as atomic plasma, and have little experimental knowledge of their internal geometry or processes. We know that such a lump as the sun burns at its surface 3-sphere and emits radiation, and we know a good deal about those surface processes which are nuclear atomic processes, but we know almost nothing about its interior 4-ball, a dimensionally rounder enclosed space whose existence we did not suspect. Every moving surface boundary of matter in the observed universe is evolving in four dimensions at velocity <math>c</math>. The current location in 4-space of any of its material objects corresponds to the present moment in the proper time of that object's inertial reference frame. The object's direction of movement at velocity <math>c</math> corresponds to its proper time dimension, which is a spiral over time, not a Euclidean (straight-line) dimension, since its direction is changing in its orbit. Objects with mass of all sizes, from subatomic particles to the largest objects observed in the cosmos, are perpetually in inertial rotational motion in some orbit, and simultaneously in inertial translational motion propagating themselves through 4-space, in two completely orthogonal inertial motions each at the constant universal rate of transformation <math>c</math>. Every object with mass moves relative to universal 4-coordinate Euclidean space on its own distinct geodesic spiral, a screw displacement trajectory that is the compound of its two completely orthogonal inertial motions, a rotation and a translation. Objects without mass such as photons lie off such moving surface boundaries of matter from which they were emitted, and their motion is of a different nature. They are in translational motion at velocity <math>c</math> through all four dimensions concurrently, without any rotational component of motion, so they move through 4-space on straight lines at a compound velocity. The propagation speed of light measured on a straight line through Euclidean 4-space is <math>c\prime = 2c</math>, so we can see in four dimensions, even though we are physically confined to a 3-dimensional manifold that is moving at velocity <math>c</math>. For example, we can look across the center of the mostly-empty 4-ball containing our galaxy and see stars in the opposite sides of its concentric 3-sphere orbital surfaces. We have been unaware that when we look up at night we see stars and galaxies, themselves large 4-dimensional objects, distributed all around us in 4-dimensional Euclidean space, and moving through it, like us, at the constant velocity <math>c</math>. They move in the 4-space direction corresponding to their proper time, perpendicular to all three dimensions of their proper 3-space, and generally the farther they are from us the greater the divergence of their direction of motion from our direction of motion: the greater the relative motion between us and their Hubble redshift. Light from them reaches us directly, propagating on straight lines through 4-space at twice the velocity at which they, and we ourselves, are propagating through 4-space. This physical model of the observed universe is compatible with the theories of special and general relativity, and with the atomic theory of quantum mechanics. It explains those theories geometrically, as expressions of intrinsic symmetries in Euclidean space. == Symmetries == It is common to speak of nature as a web, and so it is, the great web of our physical experiences. Every web must have its root systems somewhere, and nature in this sense must be rooted in the symmetries which underlie physics and geometry, the [[W:Group (mathematics)|mathematics of groups]].{{Sfn|Conway, Burgiel & Goodman-Strauss|2008}} As I understand [[W:Noether's theorem|Noether's theorem]] (which is not mathematically), hers is the deepest meta-theory of nature yet, deeper than [[W:Theory of relativity|Einstein's relativity]] or [[W:Evolution|Darwin's evolution]] or [[W:Euclidean geometry|Euclid's geometry]]. It finds that all fundamental findings in physics are based on conservation laws which can be laid at the doors of distinct [[W:symmetry group |symmetry group]]s. Thus all fundamental systems in physics, as examples [[W:quantum chromodynamics|quantum chromodynamics]] (QCD) the theory of the strong force binding the atomic nucleus and [[W:quantum electrodynamics|quantum electrodynamics]] (QED) the theory of the electromagnetic force, each have a corresponding symmetry [[W:group theory|group theory]] of which they are an expression. [[W:Coxeter group|Coxeter's theory of symmetry groups]] generated by reflections did for geometry what Noether's theorem and Einstein's relativity did for physics. [[W:Coxeter|Coxeter]] showed that Euclidean geometry is based on conservation laws that correspond to distinct symmetry groups, and that their group actions express the principle of relativity. Here is Coxeter's formulation of the motions of objects (their congruent transformations) in an ''n''-dimensional Euclidean space, excerpted:{{Sfn|Coxeter|1973|pp=217-218|loc=§12.2 Congruent transformations}} <blockquote>Let <math>\mathrm{Q}</math> denote a rotation, <math>\mathrm{R}</math> a reflection, <math>\mathrm{T}</math> a translation, and let <math>\mathrm{Q}^q \mathrm{R}^r\mathrm{T}</math> denote a product of several such transformations, all commutative with one another. Then <math>\mathrm{RT}</math> is a glide-reflection (in two or three dimensions), <math>\mathrm{QR}</math> is a rotary-reflection, <math>\mathrm{QT}</math> is a screw-displacement, and <math>\mathrm{Q^2}</math> is a double rotation (in four dimensions).<br> Every orthogonal transformation is expressible as:<br> :<math>\mathrm{Q}^q \mathrm{R}^r</math><br> where <math>(2^q + r \le n)</math>, the number of dimensions.<br> Transformations involving a translation are also expressible as:<br> :<math>\mathrm{Q}^q \mathrm{R}^r \mathrm{T}</math><br> where <math>(2^q + r + 1 \le n)</math>.<br> For <math>(n = 4)</math> in particular, every displacement is either a double rotation <math>\mathrm{Q}^2</math>, or a screw-displacement <math>\mathrm{QT}</math> [where the rotation component <math>\mathrm{Q}</math> is a simple rotation, but the <math>\mathrm{QT}</math> is chiral like a <math>\mathrm{Q^2}</math>]. Every enantiomorphous transformation in 4-space (reversing chirality) is a <math>\mathrm{QRT}</math>.</blockquote> If we begin with this most elemental [[w:Kinematics|kinematics]] of Coxeter's, and also assume the [[W:Galilean relativity|Galilean principle of relativity]], every displacement in 4-space can be viewed as either a <math>\mathrm{Q^2}</math> or a <math>\mathrm{QT}</math>, because we can view any <math>\mathrm{QT}</math> as a <math>\mathrm{Q^2}</math> in a linearly moving (translating) reference frame. Therefore any transformation from one inertial reference frame to another is expressable as a <math>\mathrm{Q^2}</math>. By the same principle, we can view any <math>\mathrm{QT}</math> or <math>\mathrm{Q^2}</math> as an isoclinic (equi-angled) <math>\mathrm{Q^2}</math> by proper choice of reference frame.{{Efn|[[W:Arthur Cayley|Cayley]] showed that any rotation in 4-space can be decomposed into two isoclinic rotations, which intuitively we might see follows from the fact that any transformation from one inertial reference frame to another is expressable as a [[W:SO(4)|rotation in 4-dimensional Euclidean space]].|name=Cayley's rotation factorization into two isoclinic reference frame transformations}} Coxeter's relation is thus a mathematical statement of the principle of relativity, on group-theoretic grounds. It correctly captures the limits to [[W:General relativity|general relativity]], in that we can only exchange the translation (<math>\mathrm{T}</math>) for ''one'' of the two rotations (<math>\mathrm{Q}</math>). An observer in any inertial reference frame can always measure the presence, direction and velocity of ''one'' rotation (<math>\mathrm{Q}</math>) up to uncertainty, and can always distinguish the direction of their own proper time translation (<math>\mathrm{T}</math>). As I understand Coxeter theory (which is not mathematically), the symmetry groups underlying physics seem to have an expression in a [[W:Euclidean space|Euclidean space]] of four [[W:dimension|dimension]]s, that is, they are [[W:Euclidean geometry#Higher dimensions|four-dimensional Euclidean geometry]]. Therefore as I understand that geometry (which is entirely by synthetic methods rather than by Clifford's algebraic methods), the [[W:Atom|atom]] seems to have a distinct Euclidean geometry, such that atoms and their constituent particles are four-dimensional geometric objects (4-polytopes), and nature can be understood in terms of their [[W:group action|group actions]], including centrally their group <math>SO(4)</math> [[W:rotations in 4-dimensional Euclidean space|rotations in 4-dimensional Euclidean space]]. The distinct Coxeter symmetry groups have characteristic <math>SO(4)</math> rotational expressions as the [[W:Regular_4-polytope|regular 4-polytopes]]. Their discrete isoclinic rotations are distinguishing properties of fundamental objects in geometry, relativity and quantum mechanics. For example, atoms exhibit <math>SO(4)</math> symmetries of the discrete isoclinic (equi-angled) double rotations (<math>\mathrm{Q^2}</math>) of a set of regular 4-polytopes that is characteristic of their [[w:Atomic_number|atomic number]]. == Special relativity describes Euclidean 4-space == <blockquote>Our entire model of the universe is built on symmetries. Some, like isotropy (the laws are the same in all directions), homogeneity (same in all places), and time invariance (same at all times) seem natural enough. Even relativity, the Lorentz Invariance that allows everyone to observe a constant speed of light, has an elegance to it that makes it seem natural.<ref>{{Cite book|first=Dave|last=Goldberg|title=The Universe in the Rearview Mirror: How Hidden Symmetries Shape Reality|chapter=§10. Hidden Symmetries: Why some symmetries but not others?|year=2013|publisher=Dutton Penguin Group|isbn=978-0-525-95366-1|ref={{SfnRef|Goldberg|2013}}}}</ref></blockquote> Although the Minkowski spacetime of relativity is a non-Euclidean 4-dimensional space,{{Efn|Spacetime is a non-Euclidean (curved) 4-dimensional space because it consists of three orthogonal space dimensions and a time dimension. The time dimension is not orthogonal to the three spatial dimensions; the time coordinate has the opposite sign to the three space coordinates so spacetime is hyperbolic, not a flat Euclidean 4-space at all.}} it has been noticed that its 3-dimensional space component could be modeled as a [[W:3-sphere|3-sphere]] embedded in 4-dimensional Euclidean (flat) space. That is, we could imagine that the ordinary 3-dimensional space we perceive is the curved 3-dimensional surface of a 4-dimensional ball (since the surface of a 4-ball is a curved 3-dimensional space called a 3-sphere, just as the surface of a 3-ball like the earth is a curved 2-dimensional space called a 2-sphere). This was [[#Origins of the theory|imagined by Einstein]] himself in 1921, as a thought experiment in which he carefully described his fourth orthogonal spatial dimension as merely a mathematical abstraction. Subsequently it was noticed by others (not mainstream physicists) that if physical space were really embedded in Euclidean 4-dimensional space (with our 3-dimensional space embedded in 4-space as some non-Euclidean 3-manifold, not necessarily a 3-sphere), then the Lorentz transformation effects of special relativity (spatial forshortenings and time dilations and so forth) could all be explained by ordinary perspective geometry in 4-dimensional Euclidean space. Special relativity reduces to classical vector space geometry (based on the 4-dimensional version of the Pythagorean theorem), but if and only if every observer is moving through 4-space at a universal constant velocity <math>c</math>, in some 4-space direction.{{Sfn|Yamashita|2023}} This counter-intuitive alternative geometric model of relativity, which has usually been called [[W:Formulations of special relativity#Euclidean relativity|Euclidean relativity]], is motivated by the fact that in every kind of relativity, but originally in Einstein's special relativity, each observer moves on a vector through a Euclidean four-dimensional space consisting of their three proper spatial dimensions and their proper time dimension, and the Pythagorean vector-sum of their motion through this kind of proper 4-space is always <math>c</math>, as measured by all observers from any inertial reference frame.{{Efn|Each observer is stationary in space in their own proper reference frame, while they move at maximum velocity {{Math|c}} through their own proper time. Observed from another reference frame in relative motion, they appear foreshortened in space in their direction of motion, and their clocks appear to be slowed to less than the maximum velocity {{Math|c}}.}} This is the Lorentz invariant, that allows everyone to observe a constant speed of light, regardless of their motion relative to the light source.{{Efn| ...cite Lewis Epstein's elegant explanation of the Lorentz Invariance as observers moving at constant velocity {{Math|c}} through space and proper time.}} But no physicists have taken the leap of claiming that therefore, our universe is physically [[W:Euclidean geometry#Higher dimensions|this kind of Euclidean 4-space]], and that observers are actually moving through it at velocity <math>c</math>. In physics as it has been universally understood, observers are not supposed to be able to move at velocity <math>c</math>. Their motion takes place in 3-space and in universal coordinate time (in Minkowski spacetime), and the cosmos is considered to be a non-Euclidean 3-space, generally a closed (finite) expanding 3-space, but with only three spatial dimensions, not four. In the Euclidean relativity alternative view, however, every observer is always moving at velocity <math>c</math> through the universe, which is real Euclidean 4-dimensional space <math>\mathbb{R}^4</math>. The direction in which they are moving is called their proper time axis.{{Efn|Time in spacetime is universal coordinate time, but there is another kind of time in relativity, the proper time in each inertial reference frame. Your proper time is the time you experience, and every observer has his own proper time; proper time runs at different rates in different inertial reference frames. It runs slower (compared to universal coordinate time) in a gravitational field (according to general relativity), and observers in motion with respect to each other view each other's clocks as running slower than their own clocks (according to special relativity).}} Their movement in time is not just modelled as movement in an abstract fourth dimension (as it is in Minkowski spacetime), their movement in time is isomorphic to their movement through physical space in a distinct direction at velocity <math>c</math>. Two observers' directions of movement through space may be different (or not, if they happen to be going in the same direction). Your proper time dimension is whichever direction you are moving. The other three directions perpendicular to your proper time axis are the three dimensions of your ordinary proper space, which again, will be different directions for you than for other observers moving in a different direction. There are four orthogonal spatial dimensions which we all share, but we share the same orthogonal proper time axis and ordinary proper 3-space axes only if we are at rest with respect to each other, actually moving in the same direction at velocity <math>c</math>, in the same inertial reference frame. Your proper 4-space coordinate system is rotated with respect to another observer's proper 4-space coordinate system, precisely as your vectors (directions of motion) are rotated in Euclidean 4-space with respect to each other, but there are no metric distortions (no Lorentz transformations) between your proper Euclidean 4-space coordinate systems; you are both embedded in the same Euclidean 4-dimensional space <math>\mathbb{R}^4</math>. Lorentz transformations are required only to convert between your respective proper Minkowski spacetime coordinate systems. So in this novel alternate view of relativity, every mass in the universe must be perpetually in motion at velocity <math>c</math> through Euclidean 4-space, along with all the masses in its vicinity that are going in (nearly) the same direction. The entire solar system, for example, must be translating in the fourth dimension at the "speed of light" <math>c</math>, although we do not notice it, since we are all moving in that same direction together. Acceleration of an object varies its direction of motion through 4-space, but never its velocity, which is invariant for all objects with mass. Two objects which are in motion relative to each other are both actually in motion at the same velocity <math>c</math>, but in at least slightly different directions.{{Efn|The angular divergence between two observer's motion vectors is proportional to their relative velocity: the more they diverge, the greater their relative velocity, up to the maximum divergence possible in the space. In Euclidean relativity all observers are in motion at velocity {{Math|c}} relative to universal Cartesian 4-coordinate space, so the maximum relative velocity between two observers is {{Math|2c}} when they are moving in exactly opposite directions in 4-space. This is not a contradiction of special relativity, which limits the maximum relative velocity between two observers to {{Math|c}}, it is the same measurement in different units. Special relativity measures all velocities in Minkowski spacetime (in a non-Euclidean 3-space). Euclidean relativity measures all velocities in Euclidean 4-space.}} In Einstein's relativity, the invariant <math>c</math> is the speed of light through 3-space. In Euclidean relativity, the invariant <math>c</math> is the speed of matter through 4-space! The speed of light through 3-space is also perceived as <math>c</math> by all observers, because they are each living in a moving 3-manifold that is translating through 4-space at velocity <math>c</math>. Despite their extreme differences in viewpoint, Einstein's relativity and Euclidean relativity are equivalent theories in complete agreement with each other, by definition. The two theories make exactly the same special relativity predictions of how observers in different inertial reference frames will perceive each other's motions in time and space. It is beyond the scope of this present paper to show how they also agree on the predictions of general relativity, but it is important to understand that our formulation of Euclidean relativity requires our acceptance of the experimentally verified findings of special relativity, general relativity and quantum mechanics. Our model and the standard model both describe the same geometric relations of space and time based on the same evidence, but as embedded in two very different universal host spaces: Euclidean 4-space versus Minkowski spacetime. In some instances our model provides a geometric explanation for physical phenomena where the standard model has none, as yet. An example is the two models' differing explanations for the gravitational coherence of galaxies: either their inertial motion at velocity <math>c</math>, or their possession of experimentally undetected dark matter. A more central example is our use of Coxeter's kinematics to explain the laws of relativistic motion geometrically. More generally, our model is related to deep geometric properties of number elucidated by Coxeter and other geometers.{{Efn| ...cite Kappraff & Adamson's 2003 paper on The Relationship of the Cotangent Function to Special Relativity Theory, geometry and properties of number,{{Sfn|Kappraff & Adamson|2003|loc=Special Relativity Theory, Geometry and properties of number}} which shows how the Lorentz coefficient is a function of a deep geometric property of number{{Sfn|Kappraff & Adamson|2000|loc=A Fresh Look at Number}} discovered by Steinbach,{{Sfn|Steinbach|1997|loc=Golden Fields: A Case for the Heptagon}} by means of which the root formula of geometry in any Euclidean dimension, the Pythagorean theorem, may be derived solely in terms of the addition of polygon side lengths, without recourse to their products or squares. More generally, Steinbach found that in the relations among regular polytope chords, to add is to multiply; every chord is both the product (quotient) of a pair of chords and the sum (difference) of another pair of chords.}} Euclidean relativity is not even a fringe theory; no physicists or astronomers have adopted it. There are many good reasons why the revolutionary leap to a four orthogonal spatial dimensions viewpoint has not been taken, beginning with the universally observed fact that we can only construct three perpendiculars through a point in our immediate space, which appears to be resolutely 3-dimensional, not 4-dimensional. Euclidean relativity offers a nice geometric explanation of the reasons for the Lorentz transformations, but only at the cost of raising other mysteries, which have been difficult for its aficionados to explain. Another mystery is how light signals between observers in relative motion could "catch up" with the receiver moving on a diverging path through 4-space from the emitter. If both observers are already moving at <math>c</math> (on diverging paths), the propagation speed of light through 4-space between them would have to be greater than <math>c</math>. Euclidean relativity is a revolutionary theory indeed, in which <math>c</math> cannot possibly be the speed of light! We conclude that, for a theory of Euclidean 4-space to be physically viable (that is, for <math>\mathbb{R}^4</math> to be our real space and not merely an abstract mathematical space), the speed of light through Euclidean 4-space must be <math>c\prime = 2c</math>, with massless photons translating through 4-space at twice the speed of mass-carrying objects. Photons must translate the diagonal distance through 4-space along the long diameter of a unit 4-hypercube, in the same time that massive particles translate inertially along the edge (or the radius) of a unit 4-hypercube. This is conceivable in Euclidean 4-space (and in no other Euclidean space of any dimensionality) because the long diagonal of the unit 4-hypercube is the natural number <math>\sqrt{4}</math>. == An object's motion in space is the product of its discrete self-reflections == Coxeter theory describes all the possible motions of an object in space as local functions of the object's discrete geometry (its shape). Coxeter observed that in a Euclidean space of any number of dimensions, any displacement of a geometric object from one place to another, and any rotation of the object from one orientation to another, can be broken down into the product of a number of discrete self-reflections. Any action of a polytope that transforms its position and orientation in space may be measured as a distinct sequence of self-reflections of the object in its own surfaces. Any motion of the object whatsoever may be precisely described as the object propagating itself through space by a discrete sequence of local self-reflections. This is a purely kinematic description of motion which does not give any account of forces acting on the object that cause it to move. Coxeter found that both changes in position (translations) and changes in orientation (rotations) can be broken down into the simplest of all displacements (self-reflections). A translation occurs when an object self-reflects twice, in two distinct surfaces which are parallel to each other. A rotation also occurs when an object self-reflects twice, but in two distinct surfaces which intersect each other. When a object self-reflects once, it turns itself inside out (it reverses its chirality), but in translations and rotations it self-reflects twice, preserving its chirality. Coxeter's laws of kinematics are a geometric counterpart to Newton's algebraic laws of motion in three dimensional Euclidean space. They are helpful because they can be understood as geometric pictures, which help us to visualize the relationships between translation and rotation in classic Newtonian physics problems, such as the Kepler problem of the motion of the planets. But they are also a revolutionary advance beyond Newton's laws, because Coxeter formulated them in Euclidean spaces of any number of dimensions. In particular, they give us geometric pictures of all the possible motions of objects in 4-dimensional Euclidean space: <blockquote>Every orthogonal transformation in 4-space is expressible as:<br> :<math>\mathrm{Q}^q \mathrm{R}^r \mathrm{T}^t</math><br> where <math>(2^q + r + t \le 4)</math>. Every displacement is either a double rotation <math>\mathrm{Q}^2</math>, or a screw-displacement <math>\mathrm{QT}</math> [where the rotation component <math>\mathrm{Q}</math> is a simple rotation, but the <math>\mathrm{QT}</math> is chiral like a <math>\mathrm{Q^2}</math>]. Every enantiomorphous transformation in 4-space (reversing chirality) is a <math>\mathrm{QRT}</math>.</blockquote> While this description should be understood as geometric pictures, some of the pictures may not be easy for us to visualize, since we have no physical experience in 4-dimensional space. Rotation (<math>\mathrm{Q}</math>), reflection (<math>\mathrm{R}</math>) and translation (<math>\mathrm{T}</math>) are obvious analogues of what they are in three-dimensional space, but double rotation (<math>\mathrm{Q}^2</math>) is something new and unprecedented in our physical experience, because double rotations cannot occur until there are four or more dimensions of space in which to rotate. A point in 4-space may be in motion on two circles in two completely orthogonal rotation planes simultaneously. Nothing constrains the two circles to be of the same radius, or constrains either circle from being of infinite radius such that the point moves in a straight line within its rotation plane: a translation <math>\mathrm{T}</math> rather than a rotation <math>\mathrm{Q}</math>. The motion of a rigid object defined by multiple points is constrained by its rigidity, such that the radii of both circles may approach infinity, but only one of the two radii may actually reach infinity. Only one of the two rotations may actually be a translation. Four dimensional Euclidean space can contain no such thing as a <math>\mathrm{Q}^2\mathrm{T}</math>. A translating double rotation <math>\mathrm{Q}^2</math>, like a translating simple rotation <math>\mathrm{Q}</math>, is simply a screw translation <math>\mathrm{QT}</math>. That is the essence of the way the principle of relativity operates in Euclidean 4-space. An object which is double-rotating in its own proper inertial reference frame may be seen to be performing nothing more mysterious than a screw translation, when observed from an inertial reference frame from which the object is in relative translational motion. In a universe which is four-dimensional Euclidean space <math>\mathbb{R}^4</math>, wherein these motions occur only at the constant velocity <math>c</math>, there is a universal Cartesian 4-coordinate reference frame in which every rigid object is translating on a <math>\mathrm{QT}</math> at velocity <math>c</math>. That universal inertial reference frame is not the proper reference frame of any object or observer, wherein the object or observer is stationary, but it is the common reference frame of all observers. == Light propagates through 4-space at twice its apparent velocity <math>c</math>== Coxeter's laws of kinematics in 4-dimensional Euclidean space apply to all objects with mass, but we find there is an additional kind of displacement which applies only to massless particles such as photons. Light quanta (photons) translate through 4-space by 4-dimensional reflection <math>\mathrm{R}^4</math>, which may be termed a double translation <math>\mathrm{T}^2</math>, a pure translation via two pairs of parallel reflections without any rotation component <math>\mathrm{Q}</math>. Matter (atoms and all particles with mass) are perpetually rotating and translating through 4-space by <math>\mathrm{QT}</math>, a screw translation of a rotating object, which is relativistically equivalent to a stationary isoclinic <math>\mathrm{Q^2}</math>, an isoclinically rotating object such as an atom. A simple rotation <math>\mathrm{Q}</math> or simple translation <math>\mathrm{T}</math> is a double reflection <math>\mathrm{R^2}</math>, so a <math>\mathrm{QT}</math> or <math>\mathrm{Q^2}</math> is an <math>\mathrm{R^4}</math>, but not with the same group of reflection angles as a light signal <math>\mathrm{R^4}</math>. A translation <math>\mathrm{T = R^2}</math> is a double reflection in two parallel planes, and a rotation <math>\mathrm{Q = R^2}</math> is a double reflection in two intersecting planes, as in a <math>\mathrm{QT = R^4}</math> which is both at once. A double translation <math>\mathrm{T^2 = R^4}</math> is two double reflections in pairs of parallel planes at once, a reflection in four non-intersecting parallel planes; it is all translation and no rotation. In a <math>\mathrm{T^2}</math> all the motion goes to translation, so the translation goes twice as far as the simple translation <math>\mathrm{T}</math> in a <math>\mathrm{QT}</math>. A double translation <math>\mathrm{T^2 = R^4}</math> is the opposite of a double rotation <math>\mathrm{Q^2 = R^4}</math>, which is stationary but rotates twice as far as the simple rotation <math>\mathrm{Q}</math> in a <math>\mathrm{QT}</math>. The product of the two translations in a <math>\mathrm{T^2}</math> is a diagonal 4-space translation over the long diameter of the unit 4-hypercube, exactly twice the distance of a simple <math>\mathrm{T}</math> over the edge length (or radius) of the unit 4-hypercube. The [[w:Tesseract|4-hypercube (also known as the 8-cell or tesseract)]] is ''radially equilateral'', which means its edge length is equal to its radius, like the hexagon, so its long diameter (twice its radius) is exactly twice its edge length. The photon moves an equal distance in four orthogonal directions. By the four-dimensional Pythagorean theorem, each of those four distances is half the total distance the photon moves: one edge length (one radius) is half the total diagonal distance moved (the long diameter). That total movement is a double-the-distance translation, but without any rotation component, so it cannot carry any mass with it. A <math>\mathrm{T^2}</math> cannot reposition a 4-polytope the way a <math>\mathrm{QT}</math> does, it can only reposition a quantum of energy that has no distinguishing rotational symmetry, such as a photon. That is the price light pays to move exactly twice as fast as matter.{{Efn| ...lensing of double translations <math>\mathrm{T^2 = R^4}</math> in more than two pairs of parallel planes at once...relationship to the frequency of light emitted and the coherence length of the wave packet...}} == Special relativity is Galilean relativity in a Euclidean space of four orthogonal dimensions == {{Efn|...TAC suggests this section is needed sooner, i.e. in the preceding Special Relativity section, as it explains how Euclidean relativity reduces special relativity to 4D perspective geometry...it's misplaced (too late) here...}} Perspective effects known as the Lorentz transformations occur because each observer's proper 3-dimensional space is a moving curved manifold embedded in flat 4-dimensional Euclidean space. The curvature of their 3-space complicates sightline calculations for observers; they sometimes require Lorentz transformations to produce the actual 4-space Cartesian coordinates of objects in the scene being observed. But if all four spatial dimensions are considered, no Lorentz transformations are required (or permitted) in correct scene construction, except when an observer wants to calculate a projection, that is, the shadow of how things will appear to them from a three-dimensional viewpoint (not how they really are).{{Sfn|Yamashita|2023}} Space really has four orthogonal dimensions, and space and time behave there just as they do in a classical vector space, only bigger by one dimension. It is not necessary to combine 4-space with time in a unified spacetime to explain 4-dimensional perspective effects at high relative velocities, because Euclidean 4-space is already 4-dimensional, and those effects fall out naturally from the 4-dimensional Pythagorean theorem, exactly as ordinary visual perspective does in three dimensions from the 3-dimensional Pythagorean theorem. Because one of the four spatial dimensions corresponds to an observer's direction of motion (in both space and proper time), and all observers and all scenes being observed are in motion (at constant velocity) in their respective proper time directions, we observe perspective foreshortenings in time as well as in a spatial dimension. In special relativity these perspective effects are reciprocal, precisely because they are only apparent, not actual, changes in size and duration. (In general relativity the actual rate of physical processes varies from place to place, and reference frame differences are neither reciprocal nor illusory.) None of these Lorentz effects are beyond geometric explanation or paradoxical. The universe is unexpectedly strange to us in precisely the ways the Euclidean fourth dimension is strange to us; but that does hold many surprises. Euclidean 4-space is much more interesting than Euclidean 3-space, analogous to the way 3-space is much more interesting and deeply explanatory to us than it would be if we experienced it only as a 2-space with many folds and curves, as perhaps an ant does. The emergent properties of 4-space are hard for us to visualize because they lie so wholly beyond our physical experience, just as it was hard for our ancestors to imagine the earth as round like a ball. However, Euclidean spaces of successive dimensions are analogous, and so higher dimensional spaces can be anticipated and explored: that is Schläfli's great discovery. Moreover dimensional analogy itself, like everything else in nature, is an exact expression of intrinsic group-theoretic symmetries: that is Nother's great discovery. == Dimensional relativity == Coxeter's kinetic law of <math>n</math>-dimensional congruent Euclidean transformations may be called ''dimensional relativity'', since it captures the theories of special and general relativity, and has its roots in dimensional analogy. Dimensional analogy is the exploration of [[w:Hermann_Grassmann#Mathematician|Hermann Grassmann's vector space principle]], in which space cannot be limited to any finite number of dimensions. The geometry of higher-dimensional space is accessable by reason of direct analogy, as [[w:Ludwig Schläfli|Ludwig Schläfli]] subsequently demonstrated. By analogy to the surface of the earth, the bounding surface of a spherical region of <math>n</math>-dimensional Euclidean space is an <math>(n-1)</math>-sphere, a spherical space of one fewer dimensions than the <math>n</math>-ball of Euclidean space it surrounds. In dimensional relativity the sky is not a ceiling, but an infinite regress of alternating spherical and Euclidean <math>n</math>-spaces of increasing <math>n</math>, accessible from each observer's point of view. By dimensional analogy, each observer looks up into their own reference frame's regress of concentric alternating <math>n</math>-spaces. By the capacity for dimensional analogy which they possess, some observers see deeper into <math>n</math>-dimensional space than others. == Polycentric spherical relativity == An intelligent observer equipped with the principle of relativity may perceive the universe from any inertial reference frame, not only from their own proper stationary reference frame in the <math>n</math>-space universe in which they physically locate themself. We see that every observer may also properly view themself as stationary and the universe as an <math>(n+1)</math>-sphere with themself at the center observing it, perceptually equidistant from all points on its <math>n</math>-space surface, including their own physical location which is one of those surface points, distinguished to them but moving on the surface, and not the center of anything. This ''polycentric model'' of the universe is a further restatement of the principle of relativity. It is compatible with Galileo's relativity of uniformly moving objects in ordinary space, Einstein's special relativity of inertial reference frames in 4-dimensional spacetime, Einstein's general relativity of all reference frames in non-Euclidean spacetime, and Coxeter's dimensional relativity of orthogonal group actions in Euclidean and spherical spaces of any number of dimensions. It should be known as Thoreau's principle of ''spherical relativity'', since the first precise written statement of it appears in 1849: "The universe is a sphere whose center is wherever there is intelligence."{{Sfn|Thoreau|1849|p=349|ps=; "The universe is a sphere whose center is wherever there is intelligence." [Contemporaneous and independent of [[W:Ludwig Schlafli|Ludwig Schlafli]]'s pioneering work enumerating the complete set of regular polyschemes in any number of dimensions.]}} == Revolutions == The original Copernican revolution in 1543 displaced the center of the universe from the center of the earth to a point farther away, the center of the sun, with the earth performing a ''revolution'' around the sun, and the stars remaining on a fixed 2-sphere around the sun instead of around the earth. But this led inevitably to the recognition that the sun must be a star itself, not equidistant from all the stars, and the center of but one of many spheres, no monotheistic center at all. In such fashion the Euclidean four-dimensional revolution, emerging three to five centuries later, initially lends itself to the big bang theory of a single origin of the whole universe, but leads inevitably to the recognition that all the galaxies need not be equidistant from a single origin in time, any more than all the stars lie in the same galaxy, equidistant from a single center in space. The expanding sphere of matter on the surface of which we find ourselves living is likely to be one of many 3-spheres expanding at velocity <math>c</math>, with their big bang origins occurring at distinct times and places in the ''n''-dimensional universe. The most distant objects we see when we look up at night may not all have the same origin in space and time. As recently as Copernicus we believed all the stars lay on a single 2-sphere embedded in Euclidean 3-space, with our sun at its center. During the enlightenment we dispersed those stars into an infinite Euclidean 3-space, and relinquished our privileged position at the center. Then Einstein showed that our 3-space could not be Euclidean, that it must be a 3-manifold curved in every place in obedience to Newton's inverse-square law of gravity; and in a geometry related to time, at least, it must be 4-dimensional. In this work we suggest a theory of ''n''-dimensional real space and how light travels in it, a theory which says we can see into four orthogonal dimensions of Euclidean space, and so when we look up at night we see cosmological objects distributed in at least four dimensions of space around us, rather than all located in our own local 3-space. Looking still deeper and farther out, the universe viewed as a 4-sphere might, or might not, be expanding, and the most distant objects we see when we look up at night may, or may not, lie in our 4-dimensional hyperplane. Real space has ''n'' dimensions as [[w:Hermann_Grassmann|Grassmann]] and [[w:Schläfli|Schläfli]] showed, and we do not know how many dimensions the most distant objects we see may be distributed in. They need not all lie within the four spatial dimensions in which we have now learned to observe them, any more than they lie in the three dimensional hyperplane of local space in which we find everything residing in our solar system. When we look up at the objects that surround us, we have no way of discerning how many dimensions beyond three the space we are looking into has. We know their distance from us primarily by virtue of how long it takes their light to reach us. We can measure their distribution around us in 3-space or 4-space, but that is simply how we choose to measure their positions, not an actual finding of how they are distributed. Even if it is now evident that they do not all lie in the same 3-space, how many more dimensions than three are needed to contain them? We observe that our 4-ball galaxy is embedded in Euclidean ''n''-space as one of many 4-ball galaxies, each translating in a distinct direction through 4-space at velocity <math>c</math>, on more or less divergent paths from each other. But only much closer observation will reveal evidence of whether everything we see lies in the same Euclidean 4-space, or if it is distributed in five or more dimensions, and how it is moving there. To remain in agreement with the theory of relativity, the Euclidean four-dimensional viewpoint requires that all mass-carrying objects be in motion in some distinct direction through 4-space at the constant velocity <math>c</math>, although the relative velocity between nearby objects is much smaller since they move on similar vectors, aimed away from a common origin point in the past. It is natural to expect that objects moving at constant velocity away from a common origin will be distributed roughly on the surface of an expanding 3-sphere. Although their paths away from their origin are not straight lines but various helical isoclines (screw translations), nearby objects must be translating radially at the same velocity, since the objects in a system (such as our solar system or galaxy) do not separate rapidly over time but remain in orbital formation. Each system's screw translation has ''two'' [[w:Completely_orthogonal|completely orthogonal]] components of motion in 4-space, an orbital rotation (such as the earth's around our sun) and a linear translation of the entire system at velocity <math>c</math> in the direction of the original 3-sphere's radial expansion (along the system's proper time vector). Of course the view from our solar system does not suggest that each galaxy's own distinct 3-sphere is expanding at this great rate from its galactic center. The standard theory has been that the entire observable universe is expanding from a single big bang origin in time, with galaxies forming later. While the Euclidean four-dimensional viewpoint lends itself to that standard theory, it also supports theories which require no single origin point in space and time. These are the voyages of starship Earth, to boldly go where no one has gone before. We made the jump to lightspeed long ago, in whatever big bang our atoms emerged from, and have never slowed down since. == Origins of the theory == Einstein himself may have been the first to imagine the universe as the three-dimensional surface of a four-dimensional Euclidean 3-sphere, in what was narrowly the first written articulation of the geometry of Euclidean 4-space relativity, contemporaneous with the teen-aged Coxeter's (quoted below).{{Efn|[[W:William Rowan Hamilton|Hamilton]]'s algebra '''H''' of [[W:Quaternions|quaternions]] contains the notion of a [[W:Three-dimensional sphere|three-dimensional sphere]] embedded in a four-dimensional space, but Hamilton did not conceive of the quaternions as the Cartesian 4-coordinates of a Euclidean 4-space, and did not describe our ordinary 3-space as embedded in Euclidean 4-space.}} Einstein did this as a [[W:Gedankenexperiment|gedankenexperiment]] in the context of investigating whether his equations of general relativity predicted an infinite or a finite universe, in his 1921 Princeton lecture.<ref>{{Cite book|url=http://www.gutenberg.org/ebooks/36276|title=The Meaning of Relativity|last=Einstein|first=Albert|publisher=Princeton University Press|year=1923|isbn=|location=|pages=110-111}}</ref> He invited us to imagine "A spherical manifold of three dimensions, embedded in a Euclidean continuum of four dimensions", but he was careful to disclaim parenthetically that "The aid of a fourth space dimension has naturally no significance except that of a mathematical artifice." Informally, the Euclidean 4-dimensional theory of relativity may be given as a sort of reciprocal to that disclaimer of Einstein's: ''The Minkowski spacetime has naturally no significance except that of a mathematical artifice, as an aid to understanding how things will appear to an observer from their perspective; the foreshortenings, clock desynchronizations and other Lorentz transformations it predicts are proper calculations of actual perspective effects; but real space is a flat, Euclidean continuum of four orthogonal spatial dimensions, and in it the ordinary laws of a flat vector space hold (such as the Pythagorean theorem), and all sightline calculations work classically, so long as you consider all four spatial dimensions.'' The Euclidean theory of relativity differs from the special theory of relativity in ascribing to the physical universe a geometry of four or more orthogonal spatial dimensions, rather than the special theory's [[w:Minkowski spacetime|Minkowski spacetime]] geometry, in which three spatial dimensions and a time dimension comprise a unified spacetime of four dimensions. Anco and Maghadam found that <math>SO(4)</math> breaks to <math>\mathbb{S}^3</math> (the 3-sphere) if the energy in the Kepler orbit is negative (an elliptical orbit), and to <math>H^3</math> (Minkowski spacetime) if the energy is positive (a hyperbolic orbit). Therefore the fact that the planets orbit on ellipses in our 3-space suggests that they orbit on a 3-sphere embedded in Euclidean 4-space which is the actual geometry of our physical universe, and Minkowski spacetime is an abstraction; the reciprocal of Einstein's disclaimer is the direct model. Of course spacetime remains a true and useful abstraction, although it must relinquish its privileged position as our exclusive conception of our place in space.{{Efn| ...origins of the Euclidean 4-space insight in the observations of Fock, Atkinson, Moser and others.}} The invention of Euclidean geometry of more than three spatial dimensions preceded Einstein's theories by more than fifty years, when it was worked out originally by the Swiss mathematician [[w:Ludwig Schläfli|Ludwig Schläfli]] before 1853.{{Sfn|Coxeter|1973|loc=§7. Ordinary Polytopes in Higher Space; §7.x. Historical remarks|pp=141-144|ps=; "Practically all the ideas in this chapter ... are due to Schläfli, who discovered them before 1853 — a time when Cayley, Grassmann and Möbius were the only other people who had ever conceived the possibility of geometry in more than three dimensions."}} Schläfli extended Euclid's geometry of one, two, and three dimensions in a direct way to four or more dimensions, generalizing the rules and terms of [[w:Euclidean geometry|Euclidean geometry]] to spaces of any number of dimensions. He coined the general term ''[[polyscheme]]'' to mean geometric forms of any number of dimensions, including two-dimensional [[w:polygon|polygons]], three-dimensional [[w:polyhedron|polyhedra]], four dimensional [[w:polychoron|polychora]], and so on, and in the process he found all of the [[w:Regular polytope|regular polyschemes]] that are possible in every dimension, including in particular the [[User:Dc.samizdat/Rotations#Sequence of regular 4-polytopes|six convex regular polychora]] which can be constructed in a Euclidean space of four dimensions (the set analogous to the five [[w:Platonic solid|Platonic solids]] the ancients found in three dimensional space). Thus Schläfli was the first to explore the fourth dimension, reveal its emergent geometric properties, and discover its astonishing regular objects. Because his work was only published posthumously in 1901, and remained almost completely unknown until Coxeter published [[w:Regular_Polytopes_(book)|Regular Polytopes]] in 1947, other researchers had more than fifty years to rediscover the regular polychora, and competing terms were coined; today [[w:Reinhold_Hoppe|Reinhold Hoppe]]'s word ''[[w:Polytope|polytope]]'' is the commonly used term for ''polyscheme.''{{Efn|[[w:Reinhold_Hoppe|Reinhold Hoppe]]'s German word ''polytop'' was introduced into English by [[W:Alicia Boole Stott|Alicia Boole Stott]], who like Hoppe and [[W:Thorold Gosset|Thorold Gosset]] rediscovered Schlafli's six regular convex 4-polytopes, with no knowledge of their prior discovery. Today Schläfli's original ''polyschem'', with its echo of ''schema'' as in the configurations of information structures, seems even more fitting in its generality than ''polytope'' -- perhaps analogously as information software (programming) is even more general than information hardware (computers).}} Because of this century-long lag in the dissemination of a scientific discovery, the regular 4-polytopes appear to have played no role at all, by any name, in the twentieth century discovery and evolution of the theories of relativity and quantum mechanics.{{Efn|One could argue that the higher-dimensional polytopes have barely influenced science or culture at all thus far. The physicist John Edward Huth's comprehensive deep dive through the history of cultural and scientific concepts of physical space, from ancient flatland models of the world through general relativity and quantum mechancs, shows exactly how we got to our present standard model of the universe, although it includes no mention of higher-dimensional Euclidean space.<ref>{{Cite book|last=Huth|first=John Edward|title=A Sense of Space: A local's guide to a flat earth, the edge of the cosmos, and other curious places|year=2025|publisher=University of Chicago Press}}</ref>}} == Boundaries == <blockquote>Ever since we discovered that Earth is round and turns like a mad-spinning top, we have understood that reality is not as it appears to us: every time we glimpse a new aspect of it, it is a deeply emotional experience. Another veil has fallen.<ref>{{Cite book|author=Carlo Rovelli|author-link=W:Carlo Rovelli|title=Seven Brief Lessons on Physics|publisher=Riverhead|year=2016|isbn=978-0399184413}}</ref></blockquote> Of course it is strange to consciously contemplate this world we inhabit, our planet, our solar system, our 3-sphere surface in our vast galaxy, as the merest film, a boundary no thicker in the places we inhabit than the diameter of an electron (though much thicker in some places we cannot inhabit, such as the interior of stars). But is not our unconscious traditional concept of the boundary of our world even stranger? Since the enlightenment we are accustomed to thinking that there is nothing beyond three dimensional space: no boundary, because there is nothing else to separate us from. But anyone who knows the [[polyscheme]]s Schläfli discovered knows that space can have any number of dimensions, and that there are fundamental objects and motions to be discovered in four dimensions that are even more various and interesting than those we can discover in three. The strange thing, when we think about it that way, is that there ''is'' a boundary between three and four dimensional space. ''Why'' can't we move (or apparently, see) in more than three dimensions? Why is our physical world apparently only three dimensional? Why would it have just ''three'' dimensions, and not four, or five, or the ''n'' dimensions that Schläfli mapped? What is the nature of the boundary which confines us to just three dimensions? We know that in Euclidean geometry the boundary between three and four dimensions is itself a spherical three dimensional space, so we should suspect that we are materially confined within such a curved boundary surface. Light need not be confined with us within our three dimensional boundary space. We would look directly through four dimensional space in our natural way, by receiving light signals that travelled through it to us on straight lines. In that case the reason we do not observe a fourth spatial dimension in our vicinity is that there are no nearby objects in it, just off our hyperplane in the wild. The nearest four-dimensional object we can see with our eyes is our sun, which lies equatorially in our own hyperplane, though it bulges out of it above and below. But when we look up at the heavens, every pinprick of light we observe is itself a four-dimensional object off our hyperplane, and they are distributed all around us in four-dimensional space through which we gaze. We are four-dimensionally sighted creatures, even though our bodies are three-dimensional objects, thin as an atom in the fourth dimension. But that should not perplex us: we can see into three dimensional space even though our retinas are two dimensional objects, thin as a photoreceptor cell. Our unconscious provincial concept is that there is nothing else outside our three dimensional world: no boundary, because there is nothing else to separate us from. But Schläfli discovered something else: all the astonishing regular objects that exist in higher dimensions, which vastly extend our notions of the beauty and mystery of space itself, and the intrinsic spatial symmetries of our universe which geometry reveals. Space is more commodious than we thought it was, and permits previously unimagined objects and motions. So our provincial conception of our place in it now has the same kind of status as our idea that the sun rises in the east and passes overhead: it is mere appearance, not a true model and no longer a proper explanation. An inertial boundary is an explanation, be it ever so thin. And would a boundary of ''no'' thickness, a mere abstraction with no physical power to separate, be a more suitable explanation? We must look for a physically powerful explanation in the geometry of space itself, which general relativity properly associates with the gravitational or inertial force. <blockquote>The number of dimensions possessed by a figure is the number of straight lines each perpendicular to all the others which can be drawn on it. Thus a point has no dimensions, a straight line one, a plane surface two, and a solid three .... In space as we now know it only three lines can be imagined perpendicular to each other. A fourth line, perpendicular to all the other three would be quite invisible and unimaginable to us. We ourselves and all the material things around us probably possess a fourth dimension, of which we are quite unaware. If not, from a four-dimensional point of view we are mere geometrical abstractions, like geometrical surfaces, lines, and points are to us. But this thickness in the fourth dimension must be exceedingly minute, if it exists at all. That is, we could only draw an exceedingly small line perpendicular to our three perpendicular lines, length, breadth and thickness, so small that no microscope could ever perceive it. We can find out something about the conditions of the fourth and higher dimensions if they exist, without being certain that they do exist, by a process which I have termed "Dimensional Analogy."<ref>{{Citation|title=Dimensional Analogy|last=Coxeter|first=Donald|date=February 1923|publisher=Coxeter Fonds, University of Toronto Archives|authorlink=W:Harold Scott MacDonald Coxeter|series=|postscript=|work=}}</ref></blockquote> I believe, but I cannot prove, that we live in real space, which is Schläfli's Euclidean space of ''n'' analogous dimensions. As Grassmann showed first, space cannot be limited to any finite number of dimensions. There will always be higher dimensions to discover, first in imagination and then to explore physically, each an astonishing new enlightenment.<ref>{{Cite book|first=T.S.|last=Eliot|title=Little Gidding|volume=Four Quartets|year=1943}}<blockquote> :We shall not cease from exploration :And the end of all our exploring :Will be to arrive where we started :And know the place for the first time. :Through the unknown, remembered gate :When the last of earth left to discover :Is that which was the beginning; :At the source of the longest river :The voice of the hidden waterfall :And the children in the apple-tree :Not known, because not looked for :But heard, half-heard, in the stillness :Between two waves of the sea. </blockquote></ref> Schläfli discovered every regular convex polytope that exists in any dimension, but that was only the beginning of the story of dimensional analogy, not its end or even the end of its beginning. That project is forever beginning anew. Coxeter discovered that Schläfli's Euclidean space is an expression of intrinsic symmetries, as Noether discovered all of physics is. Kappraff and Adamson discovered that even the sequences of humble regular polygons have fractal complexity. Symmetry itself is chaotic, always reachable but forever beyond our complete grasp. We are on a Wilderness Project, and just at its beginning, but already we observe a Euclidean space of four or more orthogonal spatial dimensions in which all objects with mass move ceaselessly at the constant velocity <math>c</math>, the universal rate at which everything moves, quantum events occur, and each of our proper times evolves. I believe these facts explain the experimentally verified theories of relativity and quantum mechanics, by revealing their unified polycentric geometry, the same way the facts about Copernicus's heliocentric solar system explained the observed motions of the planets, by revealing the geometry of gravity. But others will have to do the math, work out the physics, and perform experiments to prove or disprove all of this, because I don't have the mathematics; entirely unlike Coxeter and Einstein, I am illiterate in those languages. <blockquote> ::::::BEECH :Where my imaginary line :Bends square in woods, an iron spine :And pile of real rocks have been founded. :And off this corner in the wild, :Where these are driven in and piled, :One tree, by being deeply wounded, :Has been impressed as Witness Tree :And made commit to memory :My proof of being not unbounded. :Thus truth's established and borne out, :Though circumstanced with dark and doubt— :Though by a world of doubt surrounded. :::::::—''The Moodie Forester''<ref>{{Cite book|title=A Witness Tree|last=Frost|first=Robert|year=1942|series=The Poetry of Robert Frost|publisher=Holt, Rinehart and Winston|edition=1969|}}</ref> </blockquote> == Appendix: Sequence of regular 4-polytopes == {{Regular convex 4-polytopes|wiki=W:|columns=7}} == ... == {{Efn|In a ''[[W:William Kingdon Clifford|Clifford]] displacement'', also known as an [[W:Rotations in 4-dimensional Euclidean space#Isoclinic rotations|isoclinic rotation]], all the Clifford parallel{{Efn|name=Clifford parallels}} invariant planes are displaced in four orthogonal directions (two completely orthogonal planes) at once: they are rotated by the same angle, and at the same time they are tilted ''sideways'' by that same angle. A [[W:Rotations in 4-dimensional Euclidean space#Isoclinic rotations|Clifford displacement]] is [[W:8-cell#Radial equilateral symmetry|4-dimensionally diagonal]].{{Efn|name=isoclinic 4-dimensional diagonal}} Every plane that is Clifford parallel to one of the completely orthogonal planes (including in this case an entire Clifford parallel bundle of 4 hexagons, but not all 16 hexagons) is invariant under the isoclinic rotation: all the points in the plane rotate in circles but remain in the plane, even as the whole plane tilts sideways. All 16 hexagons rotate by the same angle (though only 4 of them do so invariantly). All 16 hexagons are rotated by 60 degrees, and also displaced sideways by 60 degrees to a Clifford parallel hexagon. All of the other central polygons (e.g. squares) are also displaced to a Clifford parallel polygon 60 degrees away.|name=Clifford displacement}} {{Efn|It is not difficult to visualize four hexagonal planes intersecting at 60 degrees to each other, even in three dimensions. Four hexagonal central planes intersect at 60 degrees in the [[W:cuboctahedron|cuboctahedron]]. Four of the 24-cell's 16 hexagonal central planes (lying in the same 3-dimensional hyperplane) intersect at each of the 24-cell's vertices exactly the way they do at the center of a cuboctahedron. But the ''edges'' around the vertex do not meet as the radii do at the center of a cuboctahedron; the 24-cell has 8 edges around each vertex, not 12, so its vertex figure is the cube, not the cuboctahedron. The 8 edges meet exactly the way 8 edges do at the apex of a canonical [[W:cubic pyramid]|cubic pyramid]].{{Efn|name=24-cell vertex figure}}|name=cuboctahedral hexagons}} {{Efn|name=radially equilateral}} {{Efn|Eight {{sqrt|1}} edges converge in curved 3-dimensional space from the corners of the 24-cell's cubical vertex figure{{Efn|The [[W:vertex figure|vertex figure]] is the facet which is made by truncating a vertex; canonically, at the mid-edges incident to the vertex. But one can make similar vertex figures of different radii by truncating at any point along those edges, up to and including truncating at the adjacent vertices to make a ''full size'' vertex figure. Stillwell defines the vertex figure as "the convex hull of the neighbouring vertices of a given vertex".{{Sfn|Stillwell|2001|p=17}} That is what serves the illustrative purpose here.|name=full size vertex figure}} and meet at its center (the vertex), where they form 4 straight lines which cross there. The 8 vertices of the cube are the eight nearest other vertices of the 24-cell. The straight lines are geodesics: two {{sqrt|1}}-length segments of an apparently straight line (in the 3-space of the 24-cell's curved surface) that is bent in the 4th dimension into a great circle hexagon (in 4-space). Imagined from inside this curved 3-space, the bends in the hexagons are invisible. From outside (if we could view the 24-cell in 4-space), the straight lines would be seen to bend in the 4th dimension at the cube centers, because the center is displaced outward in the 4th dimension, out of the hyperplane defined by the cube's vertices. Thus the vertex cube is actually a [[W:cubic pyramid|cubic pyramid]]. Unlike a cube, it seems to be radially equilateral (like the tesseract and the 24-cell itself): its "radius" equals its edge length.{{Efn|The vertex cubic pyramid is not actually radially equilateral,{{Efn|name=radially equilateral}} because the edges radiating from its apex are not actually its radii: the apex of the [[W:cubic pyramid|cubic pyramid]] is not actually its center, just one of its vertices.}}|name=24-cell vertex figure}} {{Efn|The hexagons are inclined (tilted) at 60 degrees with respect to the unit radius coordinate system's orthogonal planes. Each hexagonal plane contains only ''one'' of the 4 coordinate system axes.{{Efn|Each great hexagon of the 24-cell contains one axis (one pair of antipodal vertices) belonging to each of the three inscribed 16-cells. The 24-cell contains three disjoint inscribed 16-cells, rotated 60° isoclinically{{Efn|name=isoclinic 4-dimensional diagonal}} with respect to each other (so their corresponding vertices are 120° {{=}} {{radic|3}} apart). A [[16-cell#Coordinates|16-cell is an orthonormal ''basis'']] for a 4-dimensional coordinate system, because its 8 vertices define the four orthogonal axes. In any choice of a vertex-up coordinate system (such as the unit radius coordinates used in this article), one of the three inscribed 16-cells is the basis for the coordinate system, and each hexagon has only ''one'' axis which is a coordinate system axis.|name=three basis 16-cells}} The hexagon consists of 3 pairs of opposite vertices (three 24-cell diameters): one opposite pair of ''integer'' coordinate vertices (one of the four coordinate axes), and two opposite pairs of ''half-integer'' coordinate vertices (not coordinate axes). For example: {{indent|17}}({{spaces|2}}0,{{spaces|2}}0,{{spaces|2}}1,{{spaces|2}}0) {{indent|5}}({{spaces|2}}{{sfrac|1|2}},–{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},–{{sfrac|1|2}}){{spaces|3}}({{spaces|2}}{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}}) {{indent|5}}(–{{sfrac|1|2}},–{{sfrac|1|2}},–{{sfrac|1|2}},–{{sfrac|1|2}}){{spaces|3}}(–{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},–{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}}) {{indent|17}}({{spaces|2}}0,{{spaces|2}}0,–1,{{spaces|2}}0)<br> is a hexagon on the ''y'' axis. Unlike the {{sqrt|2}} squares, the hexagons are actually made of 24-cell edges, so they are visible features of the 24-cell.|name=non-orthogonal hexagons|group=}} {{Efn|Visualize the three [[16-cell]]s inscribed in the 24-cell (left, right, and middle), and the rotation which takes them to each other. [[24-cell#Reciprocal constructions from 8-cell and 16-cell|The vertices of the middle 16-cell lie on the (w, x, y, z) coordinate axes]];{{Efn|name=six orthogonal planes of the Cartesian basis}} the other two are rotated 60° [[W:Rotations in 4-dimensional Euclidean space#Isoclinic rotations|isoclinically]] to its left and its right. The 24-vertex 24-cell is a compound of three 16-cells, whose three sets of 8 vertices are distributed around the 24-cell symmetrically; each vertex is surrounded by 8 others (in the 3-dimensional space of the 4-dimensional 24-cell's ''surface''), the way the vertices of a cube surround its center.{{Efn|name=24-cell vertex figure}} The 8 surrounding vertices (the cube corners) lie in other 16-cells: 4 in the other 16-cell to the left, and 4 in the other 16-cell to the right. They are the vertices of two tetrahedra inscribed in the cube, one belonging (as a cell) to each 16-cell. If the 16-cell edges are {{radic|2}}, each vertex of the compound of three 16-cells is {{radic|1}} away from its 8 surrounding vertices in other 16-cells. Now visualize those {{radic|1}} distances as the edges of the 24-cell (while continuing to visualize the disjoint 16-cells). The {{radic|1}} edges form great hexagons of 6 vertices which run around the 24-cell in a central plane. ''Four'' hexagons cross at each vertex (and its antipodal vertex), inclined at 60° to each other.{{Efn|name=cuboctahedral hexagons}} The [[24-cell#Hexagons|hexagons]] are not perpendicular to each other, or to the 16-cells' perpendicular [[24-cell#Squares|square central planes]].{{Efn|name=non-orthogonal hexagons}} The left and right 16-cells form a tesseract.{{Efn|Each pair of the three 16-cells inscribed in the 24-cell forms a 4-dimensional [[W:tesseract|hypercube (a tesseract or 8-cell)]], in [[24-cell#Relationships among interior polytopes|dimensional analogy]] to the way two tetrahedra form a cube: the two 8-vertex 16-cells are inscribed in the 16-vertex tesseract, occupying its alternate vertices. The third 16-cell does not lie within the tesseract; its 8 vertices protrude from the sides of the tesseract, forming a cubic pyramid on each of the tesseract's cubic cells. The three pairs of 16-cells form three tesseracts.{{Efn|name=three 8-cells}} The tesseracts share vertices, but the 16-cells are completely disjoint.{{Efn|name=completely disjoint}}|name=three 16-cells form three tesseracts}} Two 16-cells have vertex-pairs which are one {{radic|1}} edge (one hexagon edge) apart. But a [[24-cell#Simple rotations|''simple'' rotation]] of 60° will not take one whole 16-cell to another 16-cell, because their vertices are 60° apart in different directions, and a simple rotation has only one hexagonal plane of rotation. One 16-cell ''can'' be taken to another 16-cell by a 60° [[24-cell#Isoclinic rotations|''isoclinic'' rotation]], because an isoclinic rotation is [[3-sphere]] symmetric: four [[24-cell#Clifford parallel polytopes|Clifford parallel hexagonal planes]] rotate together, but in four different rotational directions,{{Efn|name=Clifford displacement}} taking each 16-cell to another 16-cell. But since an isoclinic 60° rotation is a ''diagonal'' rotation by 60° in ''two'' completely orthogonal directions at once,{{Efn|name=isoclinic geodesic}} the corresponding vertices of the 16-cell and the 16-cell it is taken to are 120° apart: ''two'' {{radic|1}} hexagon edges (or one {{radic|3}} hexagon chord) apart, not one {{radic|1}} edge (60°) apart as in a simple rotation.{{Efn|name=isoclinic 4-dimensional diagonal}} By the [[W:chiral|chiral]] diagonal nature of isoclinic rotations, the 16-cell ''cannot'' reach the adjacent 16-cell by rotating toward it; it can only reach the 16-cell ''beyond'' it. But of course, the 16-cell beyond the 16-cell to its right is the 16-cell to its left. So a 60° isoclinic rotation ''will'' take every 16-cell to another 16-cell: a 60° ''right'' isoclinic rotation will take the middle 16-cell to the 16-cell we may have originally visualized as the ''left'' 16-cell, and a 60° ''left'' isoclinic rotation will take the middle 16-cell to the 16-cell we visualized as the ''right'' 16-cell. (If so, that was our error in visualization; the 16-cell to the "left" is in fact the one reached by the left isoclinic rotation, as that is the only sense in which the two 16-cells are left or right of each other.)|name=three isoclinic 16-cells}} {{Efn|In a double rotation each vertex can be said to move along two completely orthogonal great circles at the same time, but it does not stay within the central plane of either of those original great circles; rather, it moves along a helical geodesic that traverses diagonally between great circles. The two completely orthogonal planes of rotation are said to be ''invariant'' because the points in each stay in the plane ''as the plane moves'', tilting sideways by the same angle that the other plane rotates.|name=helical geodesic}} {{Efn|A point under isoclinic rotation traverses the diagonal{{Efn|name=isoclinic 4-dimensional diagonal}} straight line of a single '''isoclinic geodesic''', reaching its destination directly, instead of the bent line of two successive '''simple geodesics'''. A '''[[W:geodesic|geodesic]]''' is the ''shortest path'' through a space (intuitively, a string pulled taught between two points). Simple geodesics are great circles lying in a central plane (the only kind of geodesics that occur in 3-space on the 2-sphere). Isoclinic geodesics are different: they do ''not'' lie in a single plane; they are 4-dimensional [[W:helix|spirals]] rather than simple 2-dimensional circles.{{Efn|name=helical geodesic}} But they are not like 3-dimensional [[W:screw threads|screw threads]] either, because they form a closed loop like any circle (after ''two'' revolutions). Isoclinic geodesics are ''4-dimensional great circles'', and they are just as circular as 2-dimensional circles: in fact, twice as circular, because they curve in a circle in two completely orthogonal directions at once.{{Efn|Isoclinic geodesics are ''4-dimensional great circles'' in the sense that they are 1-dimensional geodesic ''lines'' that curve in 4-space in two completely orthogonal planes at once. They should not be confused with ''great 2-spheres'',{{Sfn|Stillwell|2001|p=24}} which are the 4-dimensional analogues of 2-dimensional great circles (great 1-spheres).}} These '''isoclines''' are geodesic 1-dimensional lines embedded in a 4-dimensional space. On the 3-sphere{{Efn|All isoclines are geodesics, and isoclines on the 3-sphere are circles (curving equally in each dimension), but not all isoclines on 3-manifolds in 4-space are circles.}} they always occur in [[W:chiral|chiral]] pairs and form a pair of [[W:Villarceau circle|Villarceau circle]]s on the [[W:Clifford torus|Clifford torus]],{{Efn|Isoclines on the 3-sphere occur in non-intersecting chiral pairs. A left and a right isocline form a [[W:Hopf link|Hopf link]] called the {1,1} torus knot{{Sfn|Dorst|2019|loc=§1. Villarceau Circles|p=44|ps=; "In mathematics, the path that the (1, 1) knot on the torus traces is also known as a [[W:Villarceau circle|Villarceau circle]]. Villarceau circles are usually introduced as two intersecting circles that are the cross-section of a torus by a well-chosen plane cutting it. Picking one such circle and rotating it around the torus axis, the resulting family of circles can be used to rule the torus. By nesting tori smartly, the collection of all such circles then form a [[W:Hopf fibration|Hopf fibration]].... we prefer to consider the Villarceau circle as the (1, 1) torus knot [a [[W:Hopf link|Hopf link]]] rather than as a planar cut [two intersecting circles]."}} in which ''each'' of the two linked circles traverses all four dimensions.}} the paths of the left and the right [[W:Rotations in 4-dimensional Euclidean space#Double rotations|isoclinic rotation]]. They are [[W:Helix|helices]] bent into a [[W:Möbius strip|Möbius loop]] in the fourth dimension, taking a diagonal [[W:Winding number|winding route]] twice around the 3-sphere through the non-adjacent vertices of a 4-polytope's [[W:Skew polygon#Regular skew polygons in four dimensions|skew polygon]].|name=isoclinic geodesic}} {{Efn|[[File:Hopf band wikipedia.png|thumb|150px|Two [[W:Clifford parallel|Clifford parallel]] great circles spanned by a twisted [[W:Annulus (mathematics)|annulus]].]][[W:Clifford parallel|Clifford parallel]]s are non-intersecting curved lines that are parallel in the sense that the perpendicular (shortest) distance between them is the same at each point. A double helix is an example of Clifford parallelism in ordinary 3-dimensional Euclidean space. In 4-space Clifford parallels occur as geodesic great circles on the [[W:3-sphere|3-sphere]].{{Sfn|Kim|Rote|2016|pp=8-10|loc=Relations to Clifford Parallelism}} Whereas in 3-dimensional space, any two geodesic great circles on the [[W:2-sphere|2-sphere]] will always intersect at two antipodal points, in 4-dimensional space not all great circles intersect. In 4-polytopes various discrete sets of Clifford parallel non-intersecting geodesic great circles can be found on the 3-sphere. They spiral around each other in [[W:Hopf fibration|Hopf fiber bundles]] which visit all the vertices just once. The simplest example is that six mutually orthogonal great circles can be drawn on the 3-sphere, as three pairs of completely orthogonal great circles, intersecting at 8 points defining a [[16-cell]]. Each completely orthogonal pair of circles is Clifford parallel. They cannot intersect at all, because they lie in planes which intersect at only one point: the center of the 16-cell. Because they are perpendicular and share a common center, the two circles are obviously not parallel and separate in the usual way of parallel circles in 3 dimensions; rather they are connected like adjacent links in a chain, each passing through the other without intersecting at any points, forming a [[W:Hopf link|Hopf link]]|name=Clifford parallels}} {{Efn|In the 24-cell each great square plane is completely orthogonal{{Efn|name=completely orthogonal planes}} to another great square plane, and each great hexagon plane is completely orthogonal to a plane which intersects only two vertices: a great [[W:digon|digon]] plane.|name=pairs of completely orthogonal planes}} {{Efn|In an [[24-cell#Isoclinic rotations|isoclinic rotation]], each point anywhere in the 4-polytope moves an equal distance in four orthogonal directions at once, on a [[W:8-cell#Radial equilateral symmetry|4-dimensional diagonal]]. The point is displaced a total [[W:Pythagorean distance]] equal to the square root of four times the square of that distance. For example, when the unit-radius 24-cell rotates isoclinically 60° in a hexagon invariant plane and 60° in its completely orthogonal invariant plane,{{Efn|name=pairs of completely orthogonal planes}} all vertices are displaced to a vertex two edge lengths away. Each vertex is displaced to another vertex {{radic|3}} (120°) away, moving {{radic|3/4}} in four orthogonal coordinate directions.|name=isoclinic 4-dimensional diagonal}} {{Efn|Each square plane is isoclinic (Clifford parallel) to five other square planes but completely orthogonal{{Efn|name=completely orthogonal planes}} to only one of them.{{Efn|name=Clifford parallel squares in the 16-cell and 24-cell}} Every pair of completely orthogonal planes has Clifford parallel great circles, but not all Clifford parallel great circles are orthogonal (e.g., none of the hexagonal geodesics in the 24-cell are mutually orthogonal).|name=only some Clifford parallels are orthogonal}} {{Efn|In the [[16-cell#Rotations|16-cell]] the 6 orthogonal great squares form 3 pairs of completely orthogonal great circles; each pair is Clifford parallel. In the 24-cell, the 3 inscribed 16-cells lie rotated 60 degrees isoclinically{{Efn|name=isoclinic 4-dimensional diagonal}} with respect to each other; consequently their corresponding vertices are 120 degrees apart on a hexagonal great circle. Pairing their vertices which are 90 degrees apart reveals corresponding square great circles which are Clifford parallel. Each of the 18 square great circles is Clifford parallel not only to one other square great circle in the same 16-cell (the completely orthogonal one), but also to two square great circles (which are completely orthogonal to each other) in each of the other two 16-cells. (Completely orthogonal great circles are Clifford parallel, but not all Clifford parallels are orthogonal.{{Efn|name=only some Clifford parallels are orthogonal}}) A 60 degree isoclinic rotation of the 24-cell in hexagonal invariant planes takes each square great circle to a Clifford parallel (but non-orthogonal) square great circle in a different 16-cell.|name=Clifford parallel squares in the 16-cell and 24-cell}} {{Efn|In 4 dimensional space we can construct 4 perpendicular axes and 6 perpendicular planes through a point. Without loss of generality, we may take these to be the axes and orthogonal central planes of a (w, x, y, z) Cartesian coordinate system. In 4 dimensions we have the same 3 orthogonal planes (xy, xz, yz) that we have in 3 dimensions, and also 3 others (wx, wy, wz). Each of the 6 orthogonal planes shares an axis with 4 of the others, and is ''completely orthogonal'' to just one of the others: the only one with which it does not share an axis. Thus there are 3 pairs of completely orthogonal planes: xy and wz intersect only at the origin; xz and wy intersect only at the origin; yz and wx intersect only at the origin.|name=six orthogonal planes of the Cartesian basis}} {{Efn|Two planes in 4-dimensional space can have four possible reciprocal positions: (1) they can coincide (be exactly the same plane); (2) they can be parallel (the only way they can fail to intersect at all); (3) they can intersect in a single line, as two non-parallel planes do in 3-dimensional space; or (4) '''they can intersect in a single point'''{{Efn|To visualize how two planes can intersect in a single point in a four dimensional space, consider the Euclidean space (w, x, y, z) and imagine that the w dimension represents time rather than a spatial dimension. The xy central plane (where w{{=}}0, z{{=}}0) shares no axis with the wz central plane (where x{{=}}0, y{{=}}0). The xy plane exists at only a single instant in time (w{{=}}0); the wz plane (and in particular the w axis) exists all the time. Thus their only moment and place of intersection is at the origin point (0,0,0,0).|name=how planes intersect at a single point}} (and they ''must'', if they are completely orthogonal).{{Efn|Two flat planes A and B of a Euclidean space of four dimensions are called ''completely orthogonal'' if and only if every line in A is orthogonal to every line in B. In that case the planes A and B intersect at a single point O, so that if a line in A intersects with a line in B, they intersect at O.{{Efn|name=six orthogonal planes of the Cartesian basis}}|name=completely orthogonal planes}}|name=how planes intersect}} {{Efn|Polytopes are '''completely disjoint''' if all their ''element sets'' are disjoint: they do not share any vertices, edges, faces or cells. They may still overlap in space, sharing 4-content, volume, area, or lineage.|name=completely disjoint}} {{Efn|If the [[W:Euclidean distance|Pythagorean distance]] between any two vertices is {{sqrt|1}}, their geodesic distance is 1; they may be two adjacent vertices (in the curved 3-space of the surface), or a vertex and the center (in 4-space). If their Pythagorean distance is {{sqrt|2}}, their geodesic distance is 2 (whether via 3-space or 4-space, because the path along the edges is the same straight line with one 90^o bend in it as the path through the center). If their Pythagorean distance is {{sqrt|3}}, their geodesic distance is still 2 (whether on a hexagonal great circle past one 60^o bend, or as a straight line with one 60^o bend in it through the center). Finally, if their Pythagorean distance is {{sqrt|4}}, their geodesic distance is still 2 in 4-space (straight through the center), but it reaches 3 in 3-space (by going halfway around a hexagonal great circle).|name=Geodesic distance}} {{Efn|Two angles are required to fix the relative positions of two planes in 4-space.{{Sfn|Kim|Rote|2016|p=7|loc=§6 Angles between two Planes in 4-Space|ps=; "In four (and higher) dimensions, we need two angles to fix the relative position between two planes. (More generally, ''k'' angles are defined between ''k''-dimensional subspaces.)"}} Since all planes in the same [[W:hyperplane|hyperplane]] are 0 degrees apart in one of the two angles, only one angle is required in 3-space. Great hexagons in different hyperplanes are 60 degrees apart in ''both'' angles. Great squares in different hyperplanes are 90 degrees apart in ''both'' angles (completely orthogonal){{Efn|name=completely orthogonal planes}} or 60 degrees apart in ''both'' angles.{{Efn||name=Clifford parallel squares in the 16-cell and 24-cell}} Planes which are separated by two equal angles are called ''isoclinic''. Planes which are isoclinic have [[W:Clifford parallel|Clifford parallel]] great circles.{{Efn|name=Clifford parallels}} A great square and a great hexagon in different hyperplanes are neither isoclinic nor Clifford parallel; they are separated by a 90 degree angle ''and'' a 60 degree angle.|name=two angles between central planes}} {{Efn|The 24-cell contains 3 distinct 8-cells (tesseracts), rotated 60° isoclinically with respect to each other. The corresponding vertices of two 8-cells are {{radic|3}} (120°) apart. Each 8-cell contains 8 cubical cells, and each cube contains four {{radic|3}} chords (its long diagonals). The 8-cells are not completely disjoint{{Efn|name=completely disjoint}} (they share vertices), but each cube and each {{radic|3}} chord belongs to just one 8-cell. The {{radic|3}} chords joining the corresponding vertices of two 8-cells belong to the third 8-cell.|name=three 8-cells}} {{Efn|Departing from any vertex V₀ in the original great hexagon plane of isoclinic rotation P₀, the first vertex reached V₁ is 120 degrees away along a {{radic|3}} chord lying in a different hexagonal plane P₁. P₁ is inclined to P₀ at a 60° angle.{{Efn|P₀ and P₁ lie in the same hyperplane (the same central cuboctahedron) so their other angle of separation is 0.{{Efn|name=two angles between central planes}}}} The second vertex reached V₂ is 120 degrees beyond V₁ along a second {{radic|3}} chord lying in another hexagonal plane P₂ that is Clifford parallel to P₀.{{Efn|P₀ and P₂ are 60° apart in ''both'' angles of separation.{{Efn|name=two angles between central planes}} Clifford parallel planes are isoclinic (which means they are separated by two equal angles), and their corresponding vertices are all the same distance apart. Although V₀ and V₂ are ''two'' {{radic|3}} chords apart{{Efn|V₀ and V₂ are two {{radic|3}} chords apart on the geodesic path of this rotational isocline, but that is not the shortest geodesic path between them. In the 24-cell, it is impossible for two vertices to be more distant than ''one'' {{radic|3}} chord, unless they are antipodal vertices {{radic|4}} apart.{{Efn|name=Geodesic distance}} V₀ and V₂ are ''one'' {{radic|3}} chord apart on some other isocline. More generally, isoclines are geodesics because the distance between their ''adjacent'' vertices is the shortest distance between those two vertices, but a path between two vertices along a geodesic is not always the shortest distance between them (even on ordinary great circle geodesics).}}, P₀ and P₂ are just one {{radic|1}} edge apart (at every pair of ''nearest'' vertices).}} (Notice that V₁ lies in both intersecting planes P₁ and P₂, as V₀ lies in both P₀ and P₁. But P₀ and P₂ have ''no'' vertices in common; they do not intersect.) The third vertex reached V₃ is 120 degrees beyond V₂ along a third {{radic|3}} chord lying in another hexagonal plane P₃ that is Clifford parallel to P₁. The three {{radic|3}} chords lie in different 8-cells.{{Efn|name=three 8-cells}} V₀ to V₃ is a 360° isoclinic rotation.|name=360 degree geodesic path visiting 3 hexagonal planes}} {{Sfn|Mamone, Pileio & Levitt|2010|loc=§4.5 Regular Convex 4-Polytopes|pp=1438-1439|ps=; the 24-cell has 1152 symmetry operations (rotations and reflections) as enumerated in Table 2, symmetry group 𝐹₄.}} ==Notes== {{Regular convex 4-polytopes Notelist|wiki=W:}} ==Citations== {{Regular convex 4-polytopes Reflist|wiki=W:}} ==References== {{Refbegin}} * {{Cite book|title=A Week on the Concord and Merrimack Rivers|last=Thoreau|first=Henry David|author-link=W:Thoreau|publisher=James Munroe and Company|year=1849|isbn=|location=Boston|ref={{SfnRef|Thoreau|1849}}}} * {{Cite journal|title=Theoretical Evidence for Principles of Special Relativity Based on Isotropic and Uniform Four-Dimensional Space|first=Takuya|last=Yamashita|date=25 May 2023|doi= 10.20944/preprints202305.1785.v1|journal=Preprints|volume=2023|issue=2023051785|url=https://doi.org/10.20944/preprints202305.1785.v1}} * {{Cite_arXiv | arxiv=2512.02903v2 | date=2 January 2026 | title=Symmetry transformation group arising from the Laplace–Runge–Lenz vector | first1=Stephen C. | last1=Anco | first2=Mahdieh Gol Bashmani | last2=Moghadam | class=math-ph}} === [[Polyscheme|Polyschemes]] === {{Regular convex 4-polytopes Refs|wiki=W:}} {{Refend}} 2kdpw1y3rfmrzfofw09o97w96z3liw0 2835212 2835211 2026-09-30T17:07:34Z Dc.samizdat 2856930 /* An object's motion in space is the product of its discrete self-reflections */ 2835212 wikitext text/x-wiki {{align|center|David Brooks Christie}} {{align|center|dc@samizdat.org}} {{align|center|Draft in progress}} {{align|center|June 2023 - September 2026}} <blockquote>'''Abstract:''' The physical universe is properly visualized as Euclidean space <math>\mathbb{R}^4</math> of four orthogonal spatial dimensions. Space itself has a fourth perpendicular dimension, of which we are unaware in ordinary life. Atoms are 4-polytopes, small round 4-dimensional objects, and stars are 4-balls of atomic plasma, large round 4-dimensional objects. We ourselves and our planet are only 3-dimensional objects, but nonetheless we can see in four dimensions of space. We have been unaware that when we look up at night we see stars and galaxies, themselves large 4-dimensional objects, distributed all around us in 4-dimensional Euclidean space, and moving through it, like us, at the constant velocity <math>c</math>. Light from them reaches us directly, on straight lines through 4-space. This view of the observed universe is compatible with special and general relativity, and with quantum mechanics. It furnishes those theories with an explanatory geometric model.</blockquote> == Summary == We observe that: * Physical space has four perpendicular dimensions, not just three. * Atoms are [[W:4-polytope|4-polytopes]]. * The sun is a [[W:4-ball|4-ball]] that is round in four dimensions. * Everything of intermediate size between an atom and a star, including us and our planet, lies in a 3-dimensional manifold of ordinary space. * Our entire 3-space manifold is moving through Euclidean 4-space at the speed of light, in a direction perpendicular to its three interior dimensions. * Special relativity describes the linear motion of objects and light signals in four-dimensional Euclidean space. == A theory of the Euclidean cosmos == The physical universe is properly visualized as [[w:Four-dimensional_space|real Euclidean space of four orthogonal spatial dimensions]] <math>\mathbb{R}^4</math>. Space itself has a fourth perpendicular dimension, of which we are unaware in ordinary life. Atoms are [[w:4-polytope|4-polytopes]], small round 4-dimensional objects, and stars are [[W:4-ball|4-balls]] of atomic plasma, large round 4-dimensional objects. Objects intermediate in size between atoms and stars, including molecules, people, and planets, are so flat as to be essentially 3-dimensional, having only the thickness of an atom in the orthogonal fourth dimension. All objects with mass move inertially through Euclidean 4-space at constant velocity <math>c</math> as long as they exist, and acceleration only varies their direction. Objects moving in the same direction are in the same inertial reference frame. Their direction of motion through 4-space at velocity <math>c</math> is their proper time dimension, simply because their direction and velocity of motion through time is the same as their direction and velocity of motion through space. A typical galaxy such as ours occupies a 4-ball of mostly empty space, with stars and other objects distributed non-uniformly within it. The galaxy's orbital center may be nothing: a smaller 4-ball of empty space they surround. The stars in our spiral galaxy appear from our accustomed point of view to occupy a disk-like region of 3-dimensional space, with a denser ball-like center, but they are not so confined: they are distributed within a region of 4-dimensional space. The disk and ball have thickness not only in the third dimension, but in the fourth spatial dimension as well. Light from stars and galaxies reaches us on straight lines through Euclidean 4-space, so from our viewpoint, in what we have always imagined to be a 3-space universe, we look into the surrounding 4-space. Although we are physically confined within a 3-dimensional hyperplane by the inertia of our motion through 4-space at constant velocity <math>c</math>, light signals are not so confined, so we observe all the cosmological objects surrounding us, both in and above or below our hyperplane, without perceiving their separation in our fourth orthogonal dimension, the direction of our motion. We may perceive a galaxy as elliptical when it is actually spherical, because that is how its image projects from its 4-ball shape into a 3-ball region in our hyperplane, where we measure it with our 3-dimensional bodies. More generally, orbits are circular in 4-space, but elliptical in the 3-space of their elliptic hyperplane. The galaxy as a whole, or more properly its orbital barycenter, is translating through 4-space at velocity <math>c</math>, in a distinct direction orthogonal to all three dimensions of our ordinary proper 3-space. Stars within the galaxy are translating with it at the same velocity <math>c</math> in the same direction, but on spiral trajectories as they pursue their various orbits within the galaxy. The galaxy as a whole occupies a 4-ball within its proper inertial reference frame (that is, in the moving frame of reference in which the galaxy considers itself to be a stationary rotating 4-ball). Over time, the galaxy 4-ball occupies a 4-dimensional cylinder and progresses along the cylinder's axis at velocity <math>c</math>. In this more universal inertial reference frame, the stars in the galaxy follow helical geodesic paths through the 4-cylinder; their trajectories are screw-translations through 4-space, the compound of a simple rotation and a completely orthogonal linear translation. The gravitational force and the inertial tendency to follow a geodesic are the same phenomenon, by the equivalence principle. That said, they can be distinguished, and the galaxy is held together primarily by gravity as inertia, not by gravity as attraction to a central mass toward which objects fall in orbit. There is not enough mass in the galaxy to hold it together by attraction, there is just enough to bend the stars' trajectories toward each other, in helical orbits around a barycentric axis of motion. It is the tremendous inertial force of stars in translational motion at velocity <math>c</math> that holds the cylinder of motion together, not some invisible dark matter. The observed universe as a whole appears to be a [[W:3-sphere|3-sphere]] expanding radially from a central origin point at velocity <math>c</math>, the invariant velocity of mass-carrying objects through 4-space, also the propagation speed of light relative to any moving 3-space manifold, as measured by all observers. A 3-sphere is a hypersphere in Euclidean 4-space, but the enclosing surface of a 3-sphere is a curved, finite 3-space, dimensionally analogous to the surface of the earth which is a curved, finite 2-space. This 3-sphere could be the domain of our visible cosmos, but of course we do not know for certain that all the cosmological objects we observe lie near the surface of our expanding 3-sphere, since it is only our assumption that they must all have originated in the same big bang long ago. Possibly some of the more distant objects we observe did not, and lie elsewhere, outside our big-bang's 3-sphere of outflying matter or even inside its 3-sphere, below its surface. We cannot assume that all objects in the 4-space universe lie near the surface of the same expanding 3-sphere. For all observers, the conjectured big-bang of their origin corresponds not only to a now-distant point in their proper time past, it also corresponds to a distinct now-distant point in 4-dimensional space: the same point in the same Euclidean 4-space for all observers with the same origin. Our big bang had a distinct origin point in real space as well as in real time. More generally, time and Euclidean 4-space can be measured independently, just as time and Euclidean 3-space were measured classically, without the necessity to combine them as spacetime. The same inertial force which holds the galactic cylinder of motion together also confines us physically to an exceedingly thin three-dimensional surface manifold moving through 4-space at velocity <math>c</math>. All objects in our solar system except the sun itself lie within this thinest three-dimensional manifold, and have only the thickness of an atom in their direction-of-motion fourth dimension. That is why we are 3-dimensional objects ourselves, and why we cannot construct more than three perpendiculars through a single point in our local 3-dimensional space. A spherical region of 4-space is called a [[W:4-ball|4-ball]]. The enclosing surface of a 4-ball of any size is a finite, curved (non-Euclidean) 3-dimensional space called a [[w:3-sphere|3-sphere]]. Our entire big-bang-origin universe appears to be the largest 3-sphere we observe, but each of the cosmological objects within it (including our galaxy and our sun) is contained in a smaller 3-sphere shell of its own, lying (we assume) on the largest 3-sphere embedded in its surface, like a soap bubble on the surface of a larger soap bubble. All the 3-dimensional surfaces are expanding, as the largest 3-sphere inflates at radial velocity <math>c</math>. We ourselves live within such an expanding 3-dimensional surface, in an infinitesimally curved 3-manifold surface embedded in Euclidean 4-space. That surface is the ordinary 3-dimensional space we experience, and it contains the earth, all the planets and the 3-dimensional space between them. Our solar system is only a small patch on the surface of a dimensionally rounder space, although that surface is not infinite. It is curved, and finite, analogous to the way the 2-dimensional surface of the earth -- once thought to be flat -- is curved and finite. Our solar system occupies a small patch on a filmy 4-dimensional soap-bubble of galactic size rounded by gravity, that is thicker-skinned than the diameter of an atom only in the interior of stars and supermassive objects. Our 3-manifold of ordinary space, as a surface within our moving 4-ball galaxy, is translating through 4-space at velocity <math>c</math> with the galaxy, in a distinct direction orthogonal to the manifold's three orthogonal dimensions of interior space. At every material point in the manifold (at every atom), the translation through 4-space is following a geometric law of motion discovered by Coxeter, that governs the propagation of individual objects through Euclidean space by the actions of their symmetry groups. The solar system's atoms of mass are 4-polytopes that are simultaneously rotating and translating, and as they advance together they define a moving 3-dimensional manifold by their own collective inertia, also called gravity, the property of matter's ceaseless propagation through 4-space at the constant velocity <math>c</math>, the universal rate of causality at which quantum events occur, all objects move, and the universe evolves. Any moving 3-dimensional manifold such as ours is an evolving surface boundary that is empty in most places, occupied by single atoms in comparatively fewer places, and occupied by bound complexes of multiple atoms (molecules) in still fewer places. In all these places it is no thicker than one atom in the dimension corresponding to its direction of translation, because molecules are 3-dimensional complexes of atoms that add no thickness to the manifold. Every object which we find occurring naturally in the solar system other than the sun itself, even the largest of 3-dimensional objects a planet, is a 3-dimensional smear of atoms no thicker than one atom in its fourth dimension, the direction of its linear translation through 4-space at velocity <math>c</math>. The moving surface manifold cannot be thicker than one atom at any point unless and until there is enough mass near that point for the force of gravity as attraction to overcome the force of gravity as inertia, allowing atoms to be "heaped up" into larger 4-dimensional objects that form a lump in its moving surface. We have little understanding of such 4-dimensional lumps thicker than one atom, since they occur naturally in our vicinity only in the interior of the sun. In fact the sun is the only such lump occurring naturally in our solar system. We refer to such 4-dimensional lumps of matter as atomic plasma, and have little experimental knowledge of their internal geometry or processes. We know that such a lump as the sun burns at its surface 3-sphere and emits radiation, and we know a good deal about those surface processes which are nuclear atomic processes, but we know almost nothing about its interior 4-ball, a dimensionally rounder enclosed space whose existence we did not suspect. Every moving surface boundary of matter in the observed universe is evolving in four dimensions at velocity <math>c</math>. The current location in 4-space of any of its material objects corresponds to the present moment in the proper time of that object's inertial reference frame. The object's direction of movement at velocity <math>c</math> corresponds to its proper time dimension, which is a spiral over time, not a Euclidean (straight-line) dimension, since its direction is changing in its orbit. Objects with mass of all sizes, from subatomic particles to the largest objects observed in the cosmos, are perpetually in inertial rotational motion in some orbit, and simultaneously in inertial translational motion propagating themselves through 4-space, in two completely orthogonal inertial motions each at the constant universal rate of transformation <math>c</math>. Every object with mass moves relative to universal 4-coordinate Euclidean space on its own distinct geodesic spiral, a screw displacement trajectory that is the compound of its two completely orthogonal inertial motions, a rotation and a translation. Objects without mass such as photons lie off such moving surface boundaries of matter from which they were emitted, and their motion is of a different nature. They are in translational motion at velocity <math>c</math> through all four dimensions concurrently, without any rotational component of motion, so they move through 4-space on straight lines at a compound velocity. The propagation speed of light measured on a straight line through Euclidean 4-space is <math>c\prime = 2c</math>, so we can see in four dimensions, even though we are physically confined to a 3-dimensional manifold that is moving at velocity <math>c</math>. For example, we can look across the center of the mostly-empty 4-ball containing our galaxy and see stars in the opposite sides of its concentric 3-sphere orbital surfaces. We have been unaware that when we look up at night we see stars and galaxies, themselves large 4-dimensional objects, distributed all around us in 4-dimensional Euclidean space, and moving through it, like us, at the constant velocity <math>c</math>. They move in the 4-space direction corresponding to their proper time, perpendicular to all three dimensions of their proper 3-space, and generally the farther they are from us the greater the divergence of their direction of motion from our direction of motion: the greater the relative motion between us and their Hubble redshift. Light from them reaches us directly, propagating on straight lines through 4-space at twice the velocity at which they, and we ourselves, are propagating through 4-space. This physical model of the observed universe is compatible with the theories of special and general relativity, and with the atomic theory of quantum mechanics. It explains those theories geometrically, as expressions of intrinsic symmetries in Euclidean space. == Symmetries == It is common to speak of nature as a web, and so it is, the great web of our physical experiences. Every web must have its root systems somewhere, and nature in this sense must be rooted in the symmetries which underlie physics and geometry, the [[W:Group (mathematics)|mathematics of groups]].{{Sfn|Conway, Burgiel & Goodman-Strauss|2008}} As I understand [[W:Noether's theorem|Noether's theorem]] (which is not mathematically), hers is the deepest meta-theory of nature yet, deeper than [[W:Theory of relativity|Einstein's relativity]] or [[W:Evolution|Darwin's evolution]] or [[W:Euclidean geometry|Euclid's geometry]]. It finds that all fundamental findings in physics are based on conservation laws which can be laid at the doors of distinct [[W:symmetry group |symmetry group]]s. Thus all fundamental systems in physics, as examples [[W:quantum chromodynamics|quantum chromodynamics]] (QCD) the theory of the strong force binding the atomic nucleus and [[W:quantum electrodynamics|quantum electrodynamics]] (QED) the theory of the electromagnetic force, each have a corresponding symmetry [[W:group theory|group theory]] of which they are an expression. [[W:Coxeter group|Coxeter's theory of symmetry groups]] generated by reflections did for geometry what Noether's theorem and Einstein's relativity did for physics. [[W:Coxeter|Coxeter]] showed that Euclidean geometry is based on conservation laws that correspond to distinct symmetry groups, and that their group actions express the principle of relativity. Here is Coxeter's formulation of the motions of objects (their congruent transformations) in an ''n''-dimensional Euclidean space, excerpted:{{Sfn|Coxeter|1973|pp=217-218|loc=§12.2 Congruent transformations}} <blockquote>Let <math>\mathrm{Q}</math> denote a rotation, <math>\mathrm{R}</math> a reflection, <math>\mathrm{T}</math> a translation, and let <math>\mathrm{Q}^q \mathrm{R}^r\mathrm{T}</math> denote a product of several such transformations, all commutative with one another. Then <math>\mathrm{RT}</math> is a glide-reflection (in two or three dimensions), <math>\mathrm{QR}</math> is a rotary-reflection, <math>\mathrm{QT}</math> is a screw-displacement, and <math>\mathrm{Q^2}</math> is a double rotation (in four dimensions).<br> Every orthogonal transformation is expressible as:<br> :<math>\mathrm{Q}^q \mathrm{R}^r</math><br> where <math>(2^q + r \le n)</math>, the number of dimensions.<br> Transformations involving a translation are also expressible as:<br> :<math>\mathrm{Q}^q \mathrm{R}^r \mathrm{T}</math><br> where <math>(2^q + r + 1 \le n)</math>.<br> For <math>(n = 4)</math> in particular, every displacement is either a double rotation <math>\mathrm{Q}^2</math>, or a screw-displacement <math>\mathrm{QT}</math> [where the rotation component <math>\mathrm{Q}</math> is a simple rotation, but the <math>\mathrm{QT}</math> is chiral like a <math>\mathrm{Q^2}</math>]. Every enantiomorphous transformation in 4-space (reversing chirality) is a <math>\mathrm{QRT}</math>.</blockquote> If we begin with this most elemental [[w:Kinematics|kinematics]] of Coxeter's, and also assume the [[W:Galilean relativity|Galilean principle of relativity]], every displacement in 4-space can be viewed as either a <math>\mathrm{Q^2}</math> or a <math>\mathrm{QT}</math>, because we can view any <math>\mathrm{QT}</math> as a <math>\mathrm{Q^2}</math> in a linearly moving (translating) reference frame. Therefore any transformation from one inertial reference frame to another is expressable as a <math>\mathrm{Q^2}</math>. By the same principle, we can view any <math>\mathrm{QT}</math> or <math>\mathrm{Q^2}</math> as an isoclinic (equi-angled) <math>\mathrm{Q^2}</math> by proper choice of reference frame.{{Efn|[[W:Arthur Cayley|Cayley]] showed that any rotation in 4-space can be decomposed into two isoclinic rotations, which intuitively we might see follows from the fact that any transformation from one inertial reference frame to another is expressable as a [[W:SO(4)|rotation in 4-dimensional Euclidean space]].|name=Cayley's rotation factorization into two isoclinic reference frame transformations}} Coxeter's relation is thus a mathematical statement of the principle of relativity, on group-theoretic grounds. It correctly captures the limits to [[W:General relativity|general relativity]], in that we can only exchange the translation (<math>\mathrm{T}</math>) for ''one'' of the two rotations (<math>\mathrm{Q}</math>). An observer in any inertial reference frame can always measure the presence, direction and velocity of ''one'' rotation (<math>\mathrm{Q}</math>) up to uncertainty, and can always distinguish the direction of their own proper time translation (<math>\mathrm{T}</math>). As I understand Coxeter theory (which is not mathematically), the symmetry groups underlying physics seem to have an expression in a [[W:Euclidean space|Euclidean space]] of four [[W:dimension|dimension]]s, that is, they are [[W:Euclidean geometry#Higher dimensions|four-dimensional Euclidean geometry]]. Therefore as I understand that geometry (which is entirely by synthetic methods rather than by Clifford's algebraic methods), the [[W:Atom|atom]] seems to have a distinct Euclidean geometry, such that atoms and their constituent particles are four-dimensional geometric objects (4-polytopes), and nature can be understood in terms of their [[W:group action|group actions]], including centrally their group <math>SO(4)</math> [[W:rotations in 4-dimensional Euclidean space|rotations in 4-dimensional Euclidean space]]. The distinct Coxeter symmetry groups have characteristic <math>SO(4)</math> rotational expressions as the [[W:Regular_4-polytope|regular 4-polytopes]]. Their discrete isoclinic rotations are distinguishing properties of fundamental objects in geometry, relativity and quantum mechanics. For example, atoms exhibit <math>SO(4)</math> symmetries of the discrete isoclinic (equi-angled) double rotations (<math>\mathrm{Q^2}</math>) of a set of regular 4-polytopes that is characteristic of their [[w:Atomic_number|atomic number]]. == Special relativity describes Euclidean 4-space == <blockquote>Our entire model of the universe is built on symmetries. Some, like isotropy (the laws are the same in all directions), homogeneity (same in all places), and time invariance (same at all times) seem natural enough. Even relativity, the Lorentz Invariance that allows everyone to observe a constant speed of light, has an elegance to it that makes it seem natural.<ref>{{Cite book|first=Dave|last=Goldberg|title=The Universe in the Rearview Mirror: How Hidden Symmetries Shape Reality|chapter=§10. Hidden Symmetries: Why some symmetries but not others?|year=2013|publisher=Dutton Penguin Group|isbn=978-0-525-95366-1|ref={{SfnRef|Goldberg|2013}}}}</ref></blockquote> Although the Minkowski spacetime of relativity is a non-Euclidean 4-dimensional space,{{Efn|Spacetime is a non-Euclidean (curved) 4-dimensional space because it consists of three orthogonal space dimensions and a time dimension. The time dimension is not orthogonal to the three spatial dimensions; the time coordinate has the opposite sign to the three space coordinates so spacetime is hyperbolic, not a flat Euclidean 4-space at all.}} it has been noticed that its 3-dimensional space component could be modeled as a [[W:3-sphere|3-sphere]] embedded in 4-dimensional Euclidean (flat) space. That is, we could imagine that the ordinary 3-dimensional space we perceive is the curved 3-dimensional surface of a 4-dimensional ball (since the surface of a 4-ball is a curved 3-dimensional space called a 3-sphere, just as the surface of a 3-ball like the earth is a curved 2-dimensional space called a 2-sphere). This was [[#Origins of the theory|imagined by Einstein]] himself in 1921, as a thought experiment in which he carefully described his fourth orthogonal spatial dimension as merely a mathematical abstraction. Subsequently it was noticed by others (not mainstream physicists) that if physical space were really embedded in Euclidean 4-dimensional space (with our 3-dimensional space embedded in 4-space as some non-Euclidean 3-manifold, not necessarily a 3-sphere), then the Lorentz transformation effects of special relativity (spatial forshortenings and time dilations and so forth) could all be explained by ordinary perspective geometry in 4-dimensional Euclidean space. Special relativity reduces to classical vector space geometry (based on the 4-dimensional version of the Pythagorean theorem), but if and only if every observer is moving through 4-space at a universal constant velocity <math>c</math>, in some 4-space direction.{{Sfn|Yamashita|2023}} This counter-intuitive alternative geometric model of relativity, which has usually been called [[W:Formulations of special relativity#Euclidean relativity|Euclidean relativity]], is motivated by the fact that in every kind of relativity, but originally in Einstein's special relativity, each observer moves on a vector through a Euclidean four-dimensional space consisting of their three proper spatial dimensions and their proper time dimension, and the Pythagorean vector-sum of their motion through this kind of proper 4-space is always <math>c</math>, as measured by all observers from any inertial reference frame.{{Efn|Each observer is stationary in space in their own proper reference frame, while they move at maximum velocity {{Math|c}} through their own proper time. Observed from another reference frame in relative motion, they appear foreshortened in space in their direction of motion, and their clocks appear to be slowed to less than the maximum velocity {{Math|c}}.}} This is the Lorentz invariant, that allows everyone to observe a constant speed of light, regardless of their motion relative to the light source.{{Efn| ...cite Lewis Epstein's elegant explanation of the Lorentz Invariance as observers moving at constant velocity {{Math|c}} through space and proper time.}} But no physicists have taken the leap of claiming that therefore, our universe is physically [[W:Euclidean geometry#Higher dimensions|this kind of Euclidean 4-space]], and that observers are actually moving through it at velocity <math>c</math>. In physics as it has been universally understood, observers are not supposed to be able to move at velocity <math>c</math>. Their motion takes place in 3-space and in universal coordinate time (in Minkowski spacetime), and the cosmos is considered to be a non-Euclidean 3-space, generally a closed (finite) expanding 3-space, but with only three spatial dimensions, not four. In the Euclidean relativity alternative view, however, every observer is always moving at velocity <math>c</math> through the universe, which is real Euclidean 4-dimensional space <math>\mathbb{R}^4</math>. The direction in which they are moving is called their proper time axis.{{Efn|Time in spacetime is universal coordinate time, but there is another kind of time in relativity, the proper time in each inertial reference frame. Your proper time is the time you experience, and every observer has his own proper time; proper time runs at different rates in different inertial reference frames. It runs slower (compared to universal coordinate time) in a gravitational field (according to general relativity), and observers in motion with respect to each other view each other's clocks as running slower than their own clocks (according to special relativity).}} Their movement in time is not just modelled as movement in an abstract fourth dimension (as it is in Minkowski spacetime), their movement in time is isomorphic to their movement through physical space in a distinct direction at velocity <math>c</math>. Two observers' directions of movement through space may be different (or not, if they happen to be going in the same direction). Your proper time dimension is whichever direction you are moving. The other three directions perpendicular to your proper time axis are the three dimensions of your ordinary proper space, which again, will be different directions for you than for other observers moving in a different direction. There are four orthogonal spatial dimensions which we all share, but we share the same orthogonal proper time axis and ordinary proper 3-space axes only if we are at rest with respect to each other, actually moving in the same direction at velocity <math>c</math>, in the same inertial reference frame. Your proper 4-space coordinate system is rotated with respect to another observer's proper 4-space coordinate system, precisely as your vectors (directions of motion) are rotated in Euclidean 4-space with respect to each other, but there are no metric distortions (no Lorentz transformations) between your proper Euclidean 4-space coordinate systems; you are both embedded in the same Euclidean 4-dimensional space <math>\mathbb{R}^4</math>. Lorentz transformations are required only to convert between your respective proper Minkowski spacetime coordinate systems. So in this novel alternate view of relativity, every mass in the universe must be perpetually in motion at velocity <math>c</math> through Euclidean 4-space, along with all the masses in its vicinity that are going in (nearly) the same direction. The entire solar system, for example, must be translating in the fourth dimension at the "speed of light" <math>c</math>, although we do not notice it, since we are all moving in that same direction together. Acceleration of an object varies its direction of motion through 4-space, but never its velocity, which is invariant for all objects with mass. Two objects which are in motion relative to each other are both actually in motion at the same velocity <math>c</math>, but in at least slightly different directions.{{Efn|The angular divergence between two observer's motion vectors is proportional to their relative velocity: the more they diverge, the greater their relative velocity, up to the maximum divergence possible in the space. In Euclidean relativity all observers are in motion at velocity {{Math|c}} relative to universal Cartesian 4-coordinate space, so the maximum relative velocity between two observers is {{Math|2c}} when they are moving in exactly opposite directions in 4-space. This is not a contradiction of special relativity, which limits the maximum relative velocity between two observers to {{Math|c}}, it is the same measurement in different units. Special relativity measures all velocities in Minkowski spacetime (in a non-Euclidean 3-space). Euclidean relativity measures all velocities in Euclidean 4-space.}} In Einstein's relativity, the invariant <math>c</math> is the speed of light through 3-space. In Euclidean relativity, the invariant <math>c</math> is the speed of matter through 4-space! The speed of light through 3-space is also perceived as <math>c</math> by all observers, because they are each living in a moving 3-manifold that is translating through 4-space at velocity <math>c</math>. Despite their extreme differences in viewpoint, Einstein's relativity and Euclidean relativity are equivalent theories in complete agreement with each other, by definition. The two theories make exactly the same special relativity predictions of how observers in different inertial reference frames will perceive each other's motions in time and space. It is beyond the scope of this present paper to show how they also agree on the predictions of general relativity, but it is important to understand that our formulation of Euclidean relativity requires our acceptance of the experimentally verified findings of special relativity, general relativity and quantum mechanics. Our model and the standard model both describe the same geometric relations of space and time based on the same evidence, but as embedded in two very different universal host spaces: Euclidean 4-space versus Minkowski spacetime. In some instances our model provides a geometric explanation for physical phenomena where the standard model has none, as yet. An example is the two models' differing explanations for the gravitational coherence of galaxies: either their inertial motion at velocity <math>c</math>, or their possession of experimentally undetected dark matter. A more central example is our use of Coxeter's kinematics to explain the laws of relativistic motion geometrically. More generally, our model is related to deep geometric properties of number elucidated by Coxeter and other geometers.{{Efn| ...cite Kappraff & Adamson's 2003 paper on The Relationship of the Cotangent Function to Special Relativity Theory, geometry and properties of number,{{Sfn|Kappraff & Adamson|2003|loc=Special Relativity Theory, Geometry and properties of number}} which shows how the Lorentz coefficient is a function of a deep geometric property of number{{Sfn|Kappraff & Adamson|2000|loc=A Fresh Look at Number}} discovered by Steinbach,{{Sfn|Steinbach|1997|loc=Golden Fields: A Case for the Heptagon}} by means of which the root formula of geometry in any Euclidean dimension, the Pythagorean theorem, may be derived solely in terms of the addition of polygon side lengths, without recourse to their products or squares. More generally, Steinbach found that in the relations among regular polytope chords, to add is to multiply; every chord is both the product (quotient) of a pair of chords and the sum (difference) of another pair of chords.}} Euclidean relativity is not even a fringe theory; no physicists or astronomers have adopted it. There are many good reasons why the revolutionary leap to a four orthogonal spatial dimensions viewpoint has not been taken, beginning with the universally observed fact that we can only construct three perpendiculars through a point in our immediate space, which appears to be resolutely 3-dimensional, not 4-dimensional. Euclidean relativity offers a nice geometric explanation of the reasons for the Lorentz transformations, but only at the cost of raising other mysteries, which have been difficult for its aficionados to explain. Another mystery is how light signals between observers in relative motion could "catch up" with the receiver moving on a diverging path through 4-space from the emitter. If both observers are already moving at <math>c</math> (on diverging paths), the propagation speed of light through 4-space between them would have to be greater than <math>c</math>. Euclidean relativity is a revolutionary theory indeed, in which <math>c</math> cannot possibly be the speed of light! We conclude that, for a theory of Euclidean 4-space to be physically viable (that is, for <math>\mathbb{R}^4</math> to be our real space and not merely an abstract mathematical space), the speed of light through Euclidean 4-space must be <math>c\prime = 2c</math>, with massless photons translating through 4-space at twice the speed of mass-carrying objects. Photons must translate the diagonal distance through 4-space along the long diameter of a unit 4-hypercube, in the same time that massive particles translate inertially along the edge (or the radius) of a unit 4-hypercube. This is conceivable in Euclidean 4-space (and in no other Euclidean space of any dimensionality) because the long diagonal of the unit 4-hypercube is the natural number <math>\sqrt{4}</math>. == An object's motion in space is the product of its discrete self-reflections == Coxeter theory describes all the possible motions of an object in space as local functions of the object's discrete geometry (its shape). Coxeter observed that in a Euclidean space of any number of dimensions, any displacement of a geometric object from one place to another, and any rotation of the object from one orientation to another, can be broken down into the product of a number of discrete self-reflections. Any action of a polytope that transforms its position and orientation in space may be measured as a distinct sequence of self-reflections of the object in its own surfaces. Any motion of the object whatsoever may be precisely described as the object propagating itself through space by a discrete sequence of local self-reflections. This is a purely kinematic description of motion which does not give any account of forces acting on the object that cause it to move. Coxeter found that both changes in position (translations) and changes in orientation (rotations) can be broken down into the simplest of all displacements (self-reflections). A translation occurs when an object self-reflects twice, in two distinct surfaces which are parallel to each other. A rotation also occurs when an object self-reflects twice, but in two distinct surfaces which intersect each other. When a object self-reflects once, it turns itself inside out (it reverses its chirality), but in translations and rotations it self-reflects twice, preserving its chirality. Coxeter's laws of kinematics are a geometric counterpart to Newton's algebraic laws of motion in three dimensional Euclidean space. They are helpful because they can be understood as geometric pictures, which may help us to visualize the relationships between translation and rotation in classic Newtonian physics problems, such as the Kepler problem of the motion of the planets. But they are also a revolutionary advance beyond Newton's laws, because Coxeter formulated them in Euclidean spaces of any number of dimensions. In particular, they give us geometric pictures of all the possible motions of objects in 4-dimensional Euclidean space: <blockquote>Every orthogonal transformation in 4-space is expressible as:<br> :<math>\mathrm{Q}^q \mathrm{R}^r \mathrm{T}^t</math><br> where <math>(2^q + r + t \le 4)</math>. Every displacement is either a double rotation <math>\mathrm{Q}^2</math>, or a screw-displacement <math>\mathrm{QT}</math> [where the rotation component <math>\mathrm{Q}</math> is a simple rotation, but the <math>\mathrm{QT}</math> is chiral like a <math>\mathrm{Q^2}</math>]. Every enantiomorphous transformation in 4-space (reversing chirality) is a <math>\mathrm{QRT}</math>.</blockquote> While this description should be understood as geometric pictures, some of the pictures may not be easy for us to visualize, since we have no physical experience in 4-dimensional space. Rotation (<math>\mathrm{Q}</math>), reflection (<math>\mathrm{R}</math>) and translation (<math>\mathrm{T}</math>) are obvious analogues of what they are in three-dimensional space, but double rotation (<math>\mathrm{Q}^2</math>) is something new and unprecedented in our physical experience, because double rotations cannot occur until there are four or more dimensions of space in which to rotate. A point in 4-space may be in motion on two circles in two completely orthogonal rotation planes simultaneously. Nothing constrains the two circles to be of the same radius, or constrains either circle from being of infinite radius such that the point moves in a straight line within its rotation plane: a translation <math>\mathrm{T}</math> rather than a rotation <math>\mathrm{Q}</math>. The motion of a rigid object defined by multiple points is constrained by its rigidity, such that the radii of both circles may approach infinity, but only one of the two radii may actually reach infinity. Only one of the two rotations may actually be a translation. Four dimensional Euclidean space can contain no such thing as a <math>\mathrm{Q}^2\mathrm{T}</math>. A translating double rotation <math>\mathrm{Q}^2</math>, like a translating simple rotation <math>\mathrm{Q}</math>, is simply a screw translation <math>\mathrm{QT}</math>. That is the essence of the way the principle of relativity operates in Euclidean 4-space. An object which is double-rotating in its own proper inertial reference frame may be seen to be performing nothing more mysterious than a screw translation, when observed from an inertial reference frame from which the object is in relative translational motion. In a universe which is four-dimensional Euclidean space <math>\mathbb{R}^4</math>, wherein these motions occur only at the constant velocity <math>c</math>, there is a universal Cartesian 4-coordinate reference frame in which every rigid object is translating on a <math>\mathrm{QT}</math> at velocity <math>c</math>. That universal inertial reference frame is not the proper reference frame of any object or observer, wherein the object or observer is stationary, but it is the common reference frame of all observers. == Light propagates through 4-space at twice its apparent velocity <math>c</math>== Coxeter's laws of kinematics in 4-dimensional Euclidean space apply to all objects with mass, but we find there is an additional kind of displacement which applies only to massless particles such as photons. Light quanta (photons) translate through 4-space by 4-dimensional reflection <math>\mathrm{R}^4</math>, which may be termed a double translation <math>\mathrm{T}^2</math>, a pure translation via two pairs of parallel reflections without any rotation component <math>\mathrm{Q}</math>. Matter (atoms and all particles with mass) are perpetually rotating and translating through 4-space by <math>\mathrm{QT}</math>, a screw translation of a rotating object, which is relativistically equivalent to a stationary isoclinic <math>\mathrm{Q^2}</math>, an isoclinically rotating object such as an atom. A simple rotation <math>\mathrm{Q}</math> or simple translation <math>\mathrm{T}</math> is a double reflection <math>\mathrm{R^2}</math>, so a <math>\mathrm{QT}</math> or <math>\mathrm{Q^2}</math> is an <math>\mathrm{R^4}</math>, but not with the same group of reflection angles as a light signal <math>\mathrm{R^4}</math>. A translation <math>\mathrm{T = R^2}</math> is a double reflection in two parallel planes, and a rotation <math>\mathrm{Q = R^2}</math> is a double reflection in two intersecting planes, as in a <math>\mathrm{QT = R^4}</math> which is both at once. A double translation <math>\mathrm{T^2 = R^4}</math> is two double reflections in pairs of parallel planes at once, a reflection in four non-intersecting parallel planes; it is all translation and no rotation. In a <math>\mathrm{T^2}</math> all the motion goes to translation, so the translation goes twice as far as the simple translation <math>\mathrm{T}</math> in a <math>\mathrm{QT}</math>. A double translation <math>\mathrm{T^2 = R^4}</math> is the opposite of a double rotation <math>\mathrm{Q^2 = R^4}</math>, which is stationary but rotates twice as far as the simple rotation <math>\mathrm{Q}</math> in a <math>\mathrm{QT}</math>. The product of the two translations in a <math>\mathrm{T^2}</math> is a diagonal 4-space translation over the long diameter of the unit 4-hypercube, exactly twice the distance of a simple <math>\mathrm{T}</math> over the edge length (or radius) of the unit 4-hypercube. The [[w:Tesseract|4-hypercube (also known as the 8-cell or tesseract)]] is ''radially equilateral'', which means its edge length is equal to its radius, like the hexagon, so its long diameter (twice its radius) is exactly twice its edge length. The photon moves an equal distance in four orthogonal directions. By the four-dimensional Pythagorean theorem, each of those four distances is half the total distance the photon moves: one edge length (one radius) is half the total diagonal distance moved (the long diameter). That total movement is a double-the-distance translation, but without any rotation component, so it cannot carry any mass with it. A <math>\mathrm{T^2}</math> cannot reposition a 4-polytope the way a <math>\mathrm{QT}</math> does, it can only reposition a quantum of energy that has no distinguishing rotational symmetry, such as a photon. That is the price light pays to move exactly twice as fast as matter.{{Efn| ...lensing of double translations <math>\mathrm{T^2 = R^4}</math> in more than two pairs of parallel planes at once...relationship to the frequency of light emitted and the coherence length of the wave packet...}} == Special relativity is Galilean relativity in a Euclidean space of four orthogonal dimensions == {{Efn|...TAC suggests this section is needed sooner, i.e. in the preceding Special Relativity section, as it explains how Euclidean relativity reduces special relativity to 4D perspective geometry...it's misplaced (too late) here...}} Perspective effects known as the Lorentz transformations occur because each observer's proper 3-dimensional space is a moving curved manifold embedded in flat 4-dimensional Euclidean space. The curvature of their 3-space complicates sightline calculations for observers; they sometimes require Lorentz transformations to produce the actual 4-space Cartesian coordinates of objects in the scene being observed. But if all four spatial dimensions are considered, no Lorentz transformations are required (or permitted) in correct scene construction, except when an observer wants to calculate a projection, that is, the shadow of how things will appear to them from a three-dimensional viewpoint (not how they really are).{{Sfn|Yamashita|2023}} Space really has four orthogonal dimensions, and space and time behave there just as they do in a classical vector space, only bigger by one dimension. It is not necessary to combine 4-space with time in a unified spacetime to explain 4-dimensional perspective effects at high relative velocities, because Euclidean 4-space is already 4-dimensional, and those effects fall out naturally from the 4-dimensional Pythagorean theorem, exactly as ordinary visual perspective does in three dimensions from the 3-dimensional Pythagorean theorem. Because one of the four spatial dimensions corresponds to an observer's direction of motion (in both space and proper time), and all observers and all scenes being observed are in motion (at constant velocity) in their respective proper time directions, we observe perspective foreshortenings in time as well as in a spatial dimension. In special relativity these perspective effects are reciprocal, precisely because they are only apparent, not actual, changes in size and duration. (In general relativity the actual rate of physical processes varies from place to place, and reference frame differences are neither reciprocal nor illusory.) None of these Lorentz effects are beyond geometric explanation or paradoxical. The universe is unexpectedly strange to us in precisely the ways the Euclidean fourth dimension is strange to us; but that does hold many surprises. Euclidean 4-space is much more interesting than Euclidean 3-space, analogous to the way 3-space is much more interesting and deeply explanatory to us than it would be if we experienced it only as a 2-space with many folds and curves, as perhaps an ant does. The emergent properties of 4-space are hard for us to visualize because they lie so wholly beyond our physical experience, just as it was hard for our ancestors to imagine the earth as round like a ball. However, Euclidean spaces of successive dimensions are analogous, and so higher dimensional spaces can be anticipated and explored: that is Schläfli's great discovery. Moreover dimensional analogy itself, like everything else in nature, is an exact expression of intrinsic group-theoretic symmetries: that is Nother's great discovery. == Dimensional relativity == Coxeter's kinetic law of <math>n</math>-dimensional congruent Euclidean transformations may be called ''dimensional relativity'', since it captures the theories of special and general relativity, and has its roots in dimensional analogy. Dimensional analogy is the exploration of [[w:Hermann_Grassmann#Mathematician|Hermann Grassmann's vector space principle]], in which space cannot be limited to any finite number of dimensions. The geometry of higher-dimensional space is accessable by reason of direct analogy, as [[w:Ludwig Schläfli|Ludwig Schläfli]] subsequently demonstrated. By analogy to the surface of the earth, the bounding surface of a spherical region of <math>n</math>-dimensional Euclidean space is an <math>(n-1)</math>-sphere, a spherical space of one fewer dimensions than the <math>n</math>-ball of Euclidean space it surrounds. In dimensional relativity the sky is not a ceiling, but an infinite regress of alternating spherical and Euclidean <math>n</math>-spaces of increasing <math>n</math>, accessible from each observer's point of view. By dimensional analogy, each observer looks up into their own reference frame's regress of concentric alternating <math>n</math>-spaces. By the capacity for dimensional analogy which they possess, some observers see deeper into <math>n</math>-dimensional space than others. == Polycentric spherical relativity == An intelligent observer equipped with the principle of relativity may perceive the universe from any inertial reference frame, not only from their own proper stationary reference frame in the <math>n</math>-space universe in which they physically locate themself. We see that every observer may also properly view themself as stationary and the universe as an <math>(n+1)</math>-sphere with themself at the center observing it, perceptually equidistant from all points on its <math>n</math>-space surface, including their own physical location which is one of those surface points, distinguished to them but moving on the surface, and not the center of anything. This ''polycentric model'' of the universe is a further restatement of the principle of relativity. It is compatible with Galileo's relativity of uniformly moving objects in ordinary space, Einstein's special relativity of inertial reference frames in 4-dimensional spacetime, Einstein's general relativity of all reference frames in non-Euclidean spacetime, and Coxeter's dimensional relativity of orthogonal group actions in Euclidean and spherical spaces of any number of dimensions. It should be known as Thoreau's principle of ''spherical relativity'', since the first precise written statement of it appears in 1849: "The universe is a sphere whose center is wherever there is intelligence."{{Sfn|Thoreau|1849|p=349|ps=; "The universe is a sphere whose center is wherever there is intelligence." [Contemporaneous and independent of [[W:Ludwig Schlafli|Ludwig Schlafli]]'s pioneering work enumerating the complete set of regular polyschemes in any number of dimensions.]}} == Revolutions == The original Copernican revolution in 1543 displaced the center of the universe from the center of the earth to a point farther away, the center of the sun, with the earth performing a ''revolution'' around the sun, and the stars remaining on a fixed 2-sphere around the sun instead of around the earth. But this led inevitably to the recognition that the sun must be a star itself, not equidistant from all the stars, and the center of but one of many spheres, no monotheistic center at all. In such fashion the Euclidean four-dimensional revolution, emerging three to five centuries later, initially lends itself to the big bang theory of a single origin of the whole universe, but leads inevitably to the recognition that all the galaxies need not be equidistant from a single origin in time, any more than all the stars lie in the same galaxy, equidistant from a single center in space. The expanding sphere of matter on the surface of which we find ourselves living is likely to be one of many 3-spheres expanding at velocity <math>c</math>, with their big bang origins occurring at distinct times and places in the ''n''-dimensional universe. The most distant objects we see when we look up at night may not all have the same origin in space and time. As recently as Copernicus we believed all the stars lay on a single 2-sphere embedded in Euclidean 3-space, with our sun at its center. During the enlightenment we dispersed those stars into an infinite Euclidean 3-space, and relinquished our privileged position at the center. Then Einstein showed that our 3-space could not be Euclidean, that it must be a 3-manifold curved in every place in obedience to Newton's inverse-square law of gravity; and in a geometry related to time, at least, it must be 4-dimensional. In this work we suggest a theory of ''n''-dimensional real space and how light travels in it, a theory which says we can see into four orthogonal dimensions of Euclidean space, and so when we look up at night we see cosmological objects distributed in at least four dimensions of space around us, rather than all located in our own local 3-space. Looking still deeper and farther out, the universe viewed as a 4-sphere might, or might not, be expanding, and the most distant objects we see when we look up at night may, or may not, lie in our 4-dimensional hyperplane. Real space has ''n'' dimensions as [[w:Hermann_Grassmann|Grassmann]] and [[w:Schläfli|Schläfli]] showed, and we do not know how many dimensions the most distant objects we see may be distributed in. They need not all lie within the four spatial dimensions in which we have now learned to observe them, any more than they lie in the three dimensional hyperplane of local space in which we find everything residing in our solar system. When we look up at the objects that surround us, we have no way of discerning how many dimensions beyond three the space we are looking into has. We know their distance from us primarily by virtue of how long it takes their light to reach us. We can measure their distribution around us in 3-space or 4-space, but that is simply how we choose to measure their positions, not an actual finding of how they are distributed. Even if it is now evident that they do not all lie in the same 3-space, how many more dimensions than three are needed to contain them? We observe that our 4-ball galaxy is embedded in Euclidean ''n''-space as one of many 4-ball galaxies, each translating in a distinct direction through 4-space at velocity <math>c</math>, on more or less divergent paths from each other. But only much closer observation will reveal evidence of whether everything we see lies in the same Euclidean 4-space, or if it is distributed in five or more dimensions, and how it is moving there. To remain in agreement with the theory of relativity, the Euclidean four-dimensional viewpoint requires that all mass-carrying objects be in motion in some distinct direction through 4-space at the constant velocity <math>c</math>, although the relative velocity between nearby objects is much smaller since they move on similar vectors, aimed away from a common origin point in the past. It is natural to expect that objects moving at constant velocity away from a common origin will be distributed roughly on the surface of an expanding 3-sphere. Although their paths away from their origin are not straight lines but various helical isoclines (screw translations), nearby objects must be translating radially at the same velocity, since the objects in a system (such as our solar system or galaxy) do not separate rapidly over time but remain in orbital formation. Each system's screw translation has ''two'' [[w:Completely_orthogonal|completely orthogonal]] components of motion in 4-space, an orbital rotation (such as the earth's around our sun) and a linear translation of the entire system at velocity <math>c</math> in the direction of the original 3-sphere's radial expansion (along the system's proper time vector). Of course the view from our solar system does not suggest that each galaxy's own distinct 3-sphere is expanding at this great rate from its galactic center. The standard theory has been that the entire observable universe is expanding from a single big bang origin in time, with galaxies forming later. While the Euclidean four-dimensional viewpoint lends itself to that standard theory, it also supports theories which require no single origin point in space and time. These are the voyages of starship Earth, to boldly go where no one has gone before. We made the jump to lightspeed long ago, in whatever big bang our atoms emerged from, and have never slowed down since. == Origins of the theory == Einstein himself may have been the first to imagine the universe as the three-dimensional surface of a four-dimensional Euclidean 3-sphere, in what was narrowly the first written articulation of the geometry of Euclidean 4-space relativity, contemporaneous with the teen-aged Coxeter's (quoted below).{{Efn|[[W:William Rowan Hamilton|Hamilton]]'s algebra '''H''' of [[W:Quaternions|quaternions]] contains the notion of a [[W:Three-dimensional sphere|three-dimensional sphere]] embedded in a four-dimensional space, but Hamilton did not conceive of the quaternions as the Cartesian 4-coordinates of a Euclidean 4-space, and did not describe our ordinary 3-space as embedded in Euclidean 4-space.}} Einstein did this as a [[W:Gedankenexperiment|gedankenexperiment]] in the context of investigating whether his equations of general relativity predicted an infinite or a finite universe, in his 1921 Princeton lecture.<ref>{{Cite book|url=http://www.gutenberg.org/ebooks/36276|title=The Meaning of Relativity|last=Einstein|first=Albert|publisher=Princeton University Press|year=1923|isbn=|location=|pages=110-111}}</ref> He invited us to imagine "A spherical manifold of three dimensions, embedded in a Euclidean continuum of four dimensions", but he was careful to disclaim parenthetically that "The aid of a fourth space dimension has naturally no significance except that of a mathematical artifice." Informally, the Euclidean 4-dimensional theory of relativity may be given as a sort of reciprocal to that disclaimer of Einstein's: ''The Minkowski spacetime has naturally no significance except that of a mathematical artifice, as an aid to understanding how things will appear to an observer from their perspective; the foreshortenings, clock desynchronizations and other Lorentz transformations it predicts are proper calculations of actual perspective effects; but real space is a flat, Euclidean continuum of four orthogonal spatial dimensions, and in it the ordinary laws of a flat vector space hold (such as the Pythagorean theorem), and all sightline calculations work classically, so long as you consider all four spatial dimensions.'' The Euclidean theory of relativity differs from the special theory of relativity in ascribing to the physical universe a geometry of four or more orthogonal spatial dimensions, rather than the special theory's [[w:Minkowski spacetime|Minkowski spacetime]] geometry, in which three spatial dimensions and a time dimension comprise a unified spacetime of four dimensions. Anco and Maghadam found that <math>SO(4)</math> breaks to <math>\mathbb{S}^3</math> (the 3-sphere) if the energy in the Kepler orbit is negative (an elliptical orbit), and to <math>H^3</math> (Minkowski spacetime) if the energy is positive (a hyperbolic orbit). Therefore the fact that the planets orbit on ellipses in our 3-space suggests that they orbit on a 3-sphere embedded in Euclidean 4-space which is the actual geometry of our physical universe, and Minkowski spacetime is an abstraction; the reciprocal of Einstein's disclaimer is the direct model. Of course spacetime remains a true and useful abstraction, although it must relinquish its privileged position as our exclusive conception of our place in space.{{Efn| ...origins of the Euclidean 4-space insight in the observations of Fock, Atkinson, Moser and others.}} The invention of Euclidean geometry of more than three spatial dimensions preceded Einstein's theories by more than fifty years, when it was worked out originally by the Swiss mathematician [[w:Ludwig Schläfli|Ludwig Schläfli]] before 1853.{{Sfn|Coxeter|1973|loc=§7. Ordinary Polytopes in Higher Space; §7.x. Historical remarks|pp=141-144|ps=; "Practically all the ideas in this chapter ... are due to Schläfli, who discovered them before 1853 — a time when Cayley, Grassmann and Möbius were the only other people who had ever conceived the possibility of geometry in more than three dimensions."}} Schläfli extended Euclid's geometry of one, two, and three dimensions in a direct way to four or more dimensions, generalizing the rules and terms of [[w:Euclidean geometry|Euclidean geometry]] to spaces of any number of dimensions. He coined the general term ''[[polyscheme]]'' to mean geometric forms of any number of dimensions, including two-dimensional [[w:polygon|polygons]], three-dimensional [[w:polyhedron|polyhedra]], four dimensional [[w:polychoron|polychora]], and so on, and in the process he found all of the [[w:Regular polytope|regular polyschemes]] that are possible in every dimension, including in particular the [[User:Dc.samizdat/Rotations#Sequence of regular 4-polytopes|six convex regular polychora]] which can be constructed in a Euclidean space of four dimensions (the set analogous to the five [[w:Platonic solid|Platonic solids]] the ancients found in three dimensional space). Thus Schläfli was the first to explore the fourth dimension, reveal its emergent geometric properties, and discover its astonishing regular objects. Because his work was only published posthumously in 1901, and remained almost completely unknown until Coxeter published [[w:Regular_Polytopes_(book)|Regular Polytopes]] in 1947, other researchers had more than fifty years to rediscover the regular polychora, and competing terms were coined; today [[w:Reinhold_Hoppe|Reinhold Hoppe]]'s word ''[[w:Polytope|polytope]]'' is the commonly used term for ''polyscheme.''{{Efn|[[w:Reinhold_Hoppe|Reinhold Hoppe]]'s German word ''polytop'' was introduced into English by [[W:Alicia Boole Stott|Alicia Boole Stott]], who like Hoppe and [[W:Thorold Gosset|Thorold Gosset]] rediscovered Schlafli's six regular convex 4-polytopes, with no knowledge of their prior discovery. Today Schläfli's original ''polyschem'', with its echo of ''schema'' as in the configurations of information structures, seems even more fitting in its generality than ''polytope'' -- perhaps analogously as information software (programming) is even more general than information hardware (computers).}} Because of this century-long lag in the dissemination of a scientific discovery, the regular 4-polytopes appear to have played no role at all, by any name, in the twentieth century discovery and evolution of the theories of relativity and quantum mechanics.{{Efn|One could argue that the higher-dimensional polytopes have barely influenced science or culture at all thus far. The physicist John Edward Huth's comprehensive deep dive through the history of cultural and scientific concepts of physical space, from ancient flatland models of the world through general relativity and quantum mechancs, shows exactly how we got to our present standard model of the universe, although it includes no mention of higher-dimensional Euclidean space.<ref>{{Cite book|last=Huth|first=John Edward|title=A Sense of Space: A local's guide to a flat earth, the edge of the cosmos, and other curious places|year=2025|publisher=University of Chicago Press}}</ref>}} == Boundaries == <blockquote>Ever since we discovered that Earth is round and turns like a mad-spinning top, we have understood that reality is not as it appears to us: every time we glimpse a new aspect of it, it is a deeply emotional experience. Another veil has fallen.<ref>{{Cite book|author=Carlo Rovelli|author-link=W:Carlo Rovelli|title=Seven Brief Lessons on Physics|publisher=Riverhead|year=2016|isbn=978-0399184413}}</ref></blockquote> Of course it is strange to consciously contemplate this world we inhabit, our planet, our solar system, our 3-sphere surface in our vast galaxy, as the merest film, a boundary no thicker in the places we inhabit than the diameter of an electron (though much thicker in some places we cannot inhabit, such as the interior of stars). But is not our unconscious traditional concept of the boundary of our world even stranger? Since the enlightenment we are accustomed to thinking that there is nothing beyond three dimensional space: no boundary, because there is nothing else to separate us from. But anyone who knows the [[polyscheme]]s Schläfli discovered knows that space can have any number of dimensions, and that there are fundamental objects and motions to be discovered in four dimensions that are even more various and interesting than those we can discover in three. The strange thing, when we think about it that way, is that there ''is'' a boundary between three and four dimensional space. ''Why'' can't we move (or apparently, see) in more than three dimensions? Why is our physical world apparently only three dimensional? Why would it have just ''three'' dimensions, and not four, or five, or the ''n'' dimensions that Schläfli mapped? What is the nature of the boundary which confines us to just three dimensions? We know that in Euclidean geometry the boundary between three and four dimensions is itself a spherical three dimensional space, so we should suspect that we are materially confined within such a curved boundary surface. Light need not be confined with us within our three dimensional boundary space. We would look directly through four dimensional space in our natural way, by receiving light signals that travelled through it to us on straight lines. In that case the reason we do not observe a fourth spatial dimension in our vicinity is that there are no nearby objects in it, just off our hyperplane in the wild. The nearest four-dimensional object we can see with our eyes is our sun, which lies equatorially in our own hyperplane, though it bulges out of it above and below. But when we look up at the heavens, every pinprick of light we observe is itself a four-dimensional object off our hyperplane, and they are distributed all around us in four-dimensional space through which we gaze. We are four-dimensionally sighted creatures, even though our bodies are three-dimensional objects, thin as an atom in the fourth dimension. But that should not perplex us: we can see into three dimensional space even though our retinas are two dimensional objects, thin as a photoreceptor cell. Our unconscious provincial concept is that there is nothing else outside our three dimensional world: no boundary, because there is nothing else to separate us from. But Schläfli discovered something else: all the astonishing regular objects that exist in higher dimensions, which vastly extend our notions of the beauty and mystery of space itself, and the intrinsic spatial symmetries of our universe which geometry reveals. Space is more commodious than we thought it was, and permits previously unimagined objects and motions. So our provincial conception of our place in it now has the same kind of status as our idea that the sun rises in the east and passes overhead: it is mere appearance, not a true model and no longer a proper explanation. An inertial boundary is an explanation, be it ever so thin. And would a boundary of ''no'' thickness, a mere abstraction with no physical power to separate, be a more suitable explanation? We must look for a physically powerful explanation in the geometry of space itself, which general relativity properly associates with the gravitational or inertial force. <blockquote>The number of dimensions possessed by a figure is the number of straight lines each perpendicular to all the others which can be drawn on it. Thus a point has no dimensions, a straight line one, a plane surface two, and a solid three .... In space as we now know it only three lines can be imagined perpendicular to each other. A fourth line, perpendicular to all the other three would be quite invisible and unimaginable to us. We ourselves and all the material things around us probably possess a fourth dimension, of which we are quite unaware. If not, from a four-dimensional point of view we are mere geometrical abstractions, like geometrical surfaces, lines, and points are to us. But this thickness in the fourth dimension must be exceedingly minute, if it exists at all. That is, we could only draw an exceedingly small line perpendicular to our three perpendicular lines, length, breadth and thickness, so small that no microscope could ever perceive it. We can find out something about the conditions of the fourth and higher dimensions if they exist, without being certain that they do exist, by a process which I have termed "Dimensional Analogy."<ref>{{Citation|title=Dimensional Analogy|last=Coxeter|first=Donald|date=February 1923|publisher=Coxeter Fonds, University of Toronto Archives|authorlink=W:Harold Scott MacDonald Coxeter|series=|postscript=|work=}}</ref></blockquote> I believe, but I cannot prove, that we live in real space, which is Schläfli's Euclidean space of ''n'' analogous dimensions. As Grassmann showed first, space cannot be limited to any finite number of dimensions. There will always be higher dimensions to discover, first in imagination and then to explore physically, each an astonishing new enlightenment.<ref>{{Cite book|first=T.S.|last=Eliot|title=Little Gidding|volume=Four Quartets|year=1943}}<blockquote> :We shall not cease from exploration :And the end of all our exploring :Will be to arrive where we started :And know the place for the first time. :Through the unknown, remembered gate :When the last of earth left to discover :Is that which was the beginning; :At the source of the longest river :The voice of the hidden waterfall :And the children in the apple-tree :Not known, because not looked for :But heard, half-heard, in the stillness :Between two waves of the sea. </blockquote></ref> Schläfli discovered every regular convex polytope that exists in any dimension, but that was only the beginning of the story of dimensional analogy, not its end or even the end of its beginning. That project is forever beginning anew. Coxeter discovered that Schläfli's Euclidean space is an expression of intrinsic symmetries, as Noether discovered all of physics is. Kappraff and Adamson discovered that even the sequences of humble regular polygons have fractal complexity. Symmetry itself is chaotic, always reachable but forever beyond our complete grasp. We are on a Wilderness Project, and just at its beginning, but already we observe a Euclidean space of four or more orthogonal spatial dimensions in which all objects with mass move ceaselessly at the constant velocity <math>c</math>, the universal rate at which everything moves, quantum events occur, and each of our proper times evolves. I believe these facts explain the experimentally verified theories of relativity and quantum mechanics, by revealing their unified polycentric geometry, the same way the facts about Copernicus's heliocentric solar system explained the observed motions of the planets, by revealing the geometry of gravity. But others will have to do the math, work out the physics, and perform experiments to prove or disprove all of this, because I don't have the mathematics; entirely unlike Coxeter and Einstein, I am illiterate in those languages. <blockquote> ::::::BEECH :Where my imaginary line :Bends square in woods, an iron spine :And pile of real rocks have been founded. :And off this corner in the wild, :Where these are driven in and piled, :One tree, by being deeply wounded, :Has been impressed as Witness Tree :And made commit to memory :My proof of being not unbounded. :Thus truth's established and borne out, :Though circumstanced with dark and doubt— :Though by a world of doubt surrounded. :::::::—''The Moodie Forester''<ref>{{Cite book|title=A Witness Tree|last=Frost|first=Robert|year=1942|series=The Poetry of Robert Frost|publisher=Holt, Rinehart and Winston|edition=1969|}}</ref> </blockquote> == Appendix: Sequence of regular 4-polytopes == {{Regular convex 4-polytopes|wiki=W:|columns=7}} == ... == {{Efn|In a ''[[W:William Kingdon Clifford|Clifford]] displacement'', also known as an [[W:Rotations in 4-dimensional Euclidean space#Isoclinic rotations|isoclinic rotation]], all the Clifford parallel{{Efn|name=Clifford parallels}} invariant planes are displaced in four orthogonal directions (two completely orthogonal planes) at once: they are rotated by the same angle, and at the same time they are tilted ''sideways'' by that same angle. A [[W:Rotations in 4-dimensional Euclidean space#Isoclinic rotations|Clifford displacement]] is [[W:8-cell#Radial equilateral symmetry|4-dimensionally diagonal]].{{Efn|name=isoclinic 4-dimensional diagonal}} Every plane that is Clifford parallel to one of the completely orthogonal planes (including in this case an entire Clifford parallel bundle of 4 hexagons, but not all 16 hexagons) is invariant under the isoclinic rotation: all the points in the plane rotate in circles but remain in the plane, even as the whole plane tilts sideways. All 16 hexagons rotate by the same angle (though only 4 of them do so invariantly). All 16 hexagons are rotated by 60 degrees, and also displaced sideways by 60 degrees to a Clifford parallel hexagon. All of the other central polygons (e.g. squares) are also displaced to a Clifford parallel polygon 60 degrees away.|name=Clifford displacement}} {{Efn|It is not difficult to visualize four hexagonal planes intersecting at 60 degrees to each other, even in three dimensions. Four hexagonal central planes intersect at 60 degrees in the [[W:cuboctahedron|cuboctahedron]]. Four of the 24-cell's 16 hexagonal central planes (lying in the same 3-dimensional hyperplane) intersect at each of the 24-cell's vertices exactly the way they do at the center of a cuboctahedron. But the ''edges'' around the vertex do not meet as the radii do at the center of a cuboctahedron; the 24-cell has 8 edges around each vertex, not 12, so its vertex figure is the cube, not the cuboctahedron. The 8 edges meet exactly the way 8 edges do at the apex of a canonical [[W:cubic pyramid]|cubic pyramid]].{{Efn|name=24-cell vertex figure}}|name=cuboctahedral hexagons}} {{Efn|name=radially equilateral}} {{Efn|Eight {{sqrt|1}} edges converge in curved 3-dimensional space from the corners of the 24-cell's cubical vertex figure{{Efn|The [[W:vertex figure|vertex figure]] is the facet which is made by truncating a vertex; canonically, at the mid-edges incident to the vertex. But one can make similar vertex figures of different radii by truncating at any point along those edges, up to and including truncating at the adjacent vertices to make a ''full size'' vertex figure. Stillwell defines the vertex figure as "the convex hull of the neighbouring vertices of a given vertex".{{Sfn|Stillwell|2001|p=17}} That is what serves the illustrative purpose here.|name=full size vertex figure}} and meet at its center (the vertex), where they form 4 straight lines which cross there. The 8 vertices of the cube are the eight nearest other vertices of the 24-cell. The straight lines are geodesics: two {{sqrt|1}}-length segments of an apparently straight line (in the 3-space of the 24-cell's curved surface) that is bent in the 4th dimension into a great circle hexagon (in 4-space). Imagined from inside this curved 3-space, the bends in the hexagons are invisible. From outside (if we could view the 24-cell in 4-space), the straight lines would be seen to bend in the 4th dimension at the cube centers, because the center is displaced outward in the 4th dimension, out of the hyperplane defined by the cube's vertices. Thus the vertex cube is actually a [[W:cubic pyramid|cubic pyramid]]. Unlike a cube, it seems to be radially equilateral (like the tesseract and the 24-cell itself): its "radius" equals its edge length.{{Efn|The vertex cubic pyramid is not actually radially equilateral,{{Efn|name=radially equilateral}} because the edges radiating from its apex are not actually its radii: the apex of the [[W:cubic pyramid|cubic pyramid]] is not actually its center, just one of its vertices.}}|name=24-cell vertex figure}} {{Efn|The hexagons are inclined (tilted) at 60 degrees with respect to the unit radius coordinate system's orthogonal planes. Each hexagonal plane contains only ''one'' of the 4 coordinate system axes.{{Efn|Each great hexagon of the 24-cell contains one axis (one pair of antipodal vertices) belonging to each of the three inscribed 16-cells. The 24-cell contains three disjoint inscribed 16-cells, rotated 60° isoclinically{{Efn|name=isoclinic 4-dimensional diagonal}} with respect to each other (so their corresponding vertices are 120° {{=}} {{radic|3}} apart). A [[16-cell#Coordinates|16-cell is an orthonormal ''basis'']] for a 4-dimensional coordinate system, because its 8 vertices define the four orthogonal axes. In any choice of a vertex-up coordinate system (such as the unit radius coordinates used in this article), one of the three inscribed 16-cells is the basis for the coordinate system, and each hexagon has only ''one'' axis which is a coordinate system axis.|name=three basis 16-cells}} The hexagon consists of 3 pairs of opposite vertices (three 24-cell diameters): one opposite pair of ''integer'' coordinate vertices (one of the four coordinate axes), and two opposite pairs of ''half-integer'' coordinate vertices (not coordinate axes). For example: {{indent|17}}({{spaces|2}}0,{{spaces|2}}0,{{spaces|2}}1,{{spaces|2}}0) {{indent|5}}({{spaces|2}}{{sfrac|1|2}},–{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},–{{sfrac|1|2}}){{spaces|3}}({{spaces|2}}{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}}) {{indent|5}}(–{{sfrac|1|2}},–{{sfrac|1|2}},–{{sfrac|1|2}},–{{sfrac|1|2}}){{spaces|3}}(–{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},–{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}}) {{indent|17}}({{spaces|2}}0,{{spaces|2}}0,–1,{{spaces|2}}0)<br> is a hexagon on the ''y'' axis. Unlike the {{sqrt|2}} squares, the hexagons are actually made of 24-cell edges, so they are visible features of the 24-cell.|name=non-orthogonal hexagons|group=}} {{Efn|Visualize the three [[16-cell]]s inscribed in the 24-cell (left, right, and middle), and the rotation which takes them to each other. [[24-cell#Reciprocal constructions from 8-cell and 16-cell|The vertices of the middle 16-cell lie on the (w, x, y, z) coordinate axes]];{{Efn|name=six orthogonal planes of the Cartesian basis}} the other two are rotated 60° [[W:Rotations in 4-dimensional Euclidean space#Isoclinic rotations|isoclinically]] to its left and its right. The 24-vertex 24-cell is a compound of three 16-cells, whose three sets of 8 vertices are distributed around the 24-cell symmetrically; each vertex is surrounded by 8 others (in the 3-dimensional space of the 4-dimensional 24-cell's ''surface''), the way the vertices of a cube surround its center.{{Efn|name=24-cell vertex figure}} The 8 surrounding vertices (the cube corners) lie in other 16-cells: 4 in the other 16-cell to the left, and 4 in the other 16-cell to the right. They are the vertices of two tetrahedra inscribed in the cube, one belonging (as a cell) to each 16-cell. If the 16-cell edges are {{radic|2}}, each vertex of the compound of three 16-cells is {{radic|1}} away from its 8 surrounding vertices in other 16-cells. Now visualize those {{radic|1}} distances as the edges of the 24-cell (while continuing to visualize the disjoint 16-cells). The {{radic|1}} edges form great hexagons of 6 vertices which run around the 24-cell in a central plane. ''Four'' hexagons cross at each vertex (and its antipodal vertex), inclined at 60° to each other.{{Efn|name=cuboctahedral hexagons}} The [[24-cell#Hexagons|hexagons]] are not perpendicular to each other, or to the 16-cells' perpendicular [[24-cell#Squares|square central planes]].{{Efn|name=non-orthogonal hexagons}} The left and right 16-cells form a tesseract.{{Efn|Each pair of the three 16-cells inscribed in the 24-cell forms a 4-dimensional [[W:tesseract|hypercube (a tesseract or 8-cell)]], in [[24-cell#Relationships among interior polytopes|dimensional analogy]] to the way two tetrahedra form a cube: the two 8-vertex 16-cells are inscribed in the 16-vertex tesseract, occupying its alternate vertices. The third 16-cell does not lie within the tesseract; its 8 vertices protrude from the sides of the tesseract, forming a cubic pyramid on each of the tesseract's cubic cells. The three pairs of 16-cells form three tesseracts.{{Efn|name=three 8-cells}} The tesseracts share vertices, but the 16-cells are completely disjoint.{{Efn|name=completely disjoint}}|name=three 16-cells form three tesseracts}} Two 16-cells have vertex-pairs which are one {{radic|1}} edge (one hexagon edge) apart. But a [[24-cell#Simple rotations|''simple'' rotation]] of 60° will not take one whole 16-cell to another 16-cell, because their vertices are 60° apart in different directions, and a simple rotation has only one hexagonal plane of rotation. One 16-cell ''can'' be taken to another 16-cell by a 60° [[24-cell#Isoclinic rotations|''isoclinic'' rotation]], because an isoclinic rotation is [[3-sphere]] symmetric: four [[24-cell#Clifford parallel polytopes|Clifford parallel hexagonal planes]] rotate together, but in four different rotational directions,{{Efn|name=Clifford displacement}} taking each 16-cell to another 16-cell. But since an isoclinic 60° rotation is a ''diagonal'' rotation by 60° in ''two'' completely orthogonal directions at once,{{Efn|name=isoclinic geodesic}} the corresponding vertices of the 16-cell and the 16-cell it is taken to are 120° apart: ''two'' {{radic|1}} hexagon edges (or one {{radic|3}} hexagon chord) apart, not one {{radic|1}} edge (60°) apart as in a simple rotation.{{Efn|name=isoclinic 4-dimensional diagonal}} By the [[W:chiral|chiral]] diagonal nature of isoclinic rotations, the 16-cell ''cannot'' reach the adjacent 16-cell by rotating toward it; it can only reach the 16-cell ''beyond'' it. But of course, the 16-cell beyond the 16-cell to its right is the 16-cell to its left. So a 60° isoclinic rotation ''will'' take every 16-cell to another 16-cell: a 60° ''right'' isoclinic rotation will take the middle 16-cell to the 16-cell we may have originally visualized as the ''left'' 16-cell, and a 60° ''left'' isoclinic rotation will take the middle 16-cell to the 16-cell we visualized as the ''right'' 16-cell. (If so, that was our error in visualization; the 16-cell to the "left" is in fact the one reached by the left isoclinic rotation, as that is the only sense in which the two 16-cells are left or right of each other.)|name=three isoclinic 16-cells}} {{Efn|In a double rotation each vertex can be said to move along two completely orthogonal great circles at the same time, but it does not stay within the central plane of either of those original great circles; rather, it moves along a helical geodesic that traverses diagonally between great circles. The two completely orthogonal planes of rotation are said to be ''invariant'' because the points in each stay in the plane ''as the plane moves'', tilting sideways by the same angle that the other plane rotates.|name=helical geodesic}} {{Efn|A point under isoclinic rotation traverses the diagonal{{Efn|name=isoclinic 4-dimensional diagonal}} straight line of a single '''isoclinic geodesic''', reaching its destination directly, instead of the bent line of two successive '''simple geodesics'''. A '''[[W:geodesic|geodesic]]''' is the ''shortest path'' through a space (intuitively, a string pulled taught between two points). Simple geodesics are great circles lying in a central plane (the only kind of geodesics that occur in 3-space on the 2-sphere). Isoclinic geodesics are different: they do ''not'' lie in a single plane; they are 4-dimensional [[W:helix|spirals]] rather than simple 2-dimensional circles.{{Efn|name=helical geodesic}} But they are not like 3-dimensional [[W:screw threads|screw threads]] either, because they form a closed loop like any circle (after ''two'' revolutions). Isoclinic geodesics are ''4-dimensional great circles'', and they are just as circular as 2-dimensional circles: in fact, twice as circular, because they curve in a circle in two completely orthogonal directions at once.{{Efn|Isoclinic geodesics are ''4-dimensional great circles'' in the sense that they are 1-dimensional geodesic ''lines'' that curve in 4-space in two completely orthogonal planes at once. They should not be confused with ''great 2-spheres'',{{Sfn|Stillwell|2001|p=24}} which are the 4-dimensional analogues of 2-dimensional great circles (great 1-spheres).}} These '''isoclines''' are geodesic 1-dimensional lines embedded in a 4-dimensional space. On the 3-sphere{{Efn|All isoclines are geodesics, and isoclines on the 3-sphere are circles (curving equally in each dimension), but not all isoclines on 3-manifolds in 4-space are circles.}} they always occur in [[W:chiral|chiral]] pairs and form a pair of [[W:Villarceau circle|Villarceau circle]]s on the [[W:Clifford torus|Clifford torus]],{{Efn|Isoclines on the 3-sphere occur in non-intersecting chiral pairs. A left and a right isocline form a [[W:Hopf link|Hopf link]] called the {1,1} torus knot{{Sfn|Dorst|2019|loc=§1. Villarceau Circles|p=44|ps=; "In mathematics, the path that the (1, 1) knot on the torus traces is also known as a [[W:Villarceau circle|Villarceau circle]]. Villarceau circles are usually introduced as two intersecting circles that are the cross-section of a torus by a well-chosen plane cutting it. Picking one such circle and rotating it around the torus axis, the resulting family of circles can be used to rule the torus. By nesting tori smartly, the collection of all such circles then form a [[W:Hopf fibration|Hopf fibration]].... we prefer to consider the Villarceau circle as the (1, 1) torus knot [a [[W:Hopf link|Hopf link]]] rather than as a planar cut [two intersecting circles]."}} in which ''each'' of the two linked circles traverses all four dimensions.}} the paths of the left and the right [[W:Rotations in 4-dimensional Euclidean space#Double rotations|isoclinic rotation]]. They are [[W:Helix|helices]] bent into a [[W:Möbius strip|Möbius loop]] in the fourth dimension, taking a diagonal [[W:Winding number|winding route]] twice around the 3-sphere through the non-adjacent vertices of a 4-polytope's [[W:Skew polygon#Regular skew polygons in four dimensions|skew polygon]].|name=isoclinic geodesic}} {{Efn|[[File:Hopf band wikipedia.png|thumb|150px|Two [[W:Clifford parallel|Clifford parallel]] great circles spanned by a twisted [[W:Annulus (mathematics)|annulus]].]][[W:Clifford parallel|Clifford parallel]]s are non-intersecting curved lines that are parallel in the sense that the perpendicular (shortest) distance between them is the same at each point. A double helix is an example of Clifford parallelism in ordinary 3-dimensional Euclidean space. In 4-space Clifford parallels occur as geodesic great circles on the [[W:3-sphere|3-sphere]].{{Sfn|Kim|Rote|2016|pp=8-10|loc=Relations to Clifford Parallelism}} Whereas in 3-dimensional space, any two geodesic great circles on the [[W:2-sphere|2-sphere]] will always intersect at two antipodal points, in 4-dimensional space not all great circles intersect. In 4-polytopes various discrete sets of Clifford parallel non-intersecting geodesic great circles can be found on the 3-sphere. They spiral around each other in [[W:Hopf fibration|Hopf fiber bundles]] which visit all the vertices just once. The simplest example is that six mutually orthogonal great circles can be drawn on the 3-sphere, as three pairs of completely orthogonal great circles, intersecting at 8 points defining a [[16-cell]]. Each completely orthogonal pair of circles is Clifford parallel. They cannot intersect at all, because they lie in planes which intersect at only one point: the center of the 16-cell. Because they are perpendicular and share a common center, the two circles are obviously not parallel and separate in the usual way of parallel circles in 3 dimensions; rather they are connected like adjacent links in a chain, each passing through the other without intersecting at any points, forming a [[W:Hopf link|Hopf link]]|name=Clifford parallels}} {{Efn|In the 24-cell each great square plane is completely orthogonal{{Efn|name=completely orthogonal planes}} to another great square plane, and each great hexagon plane is completely orthogonal to a plane which intersects only two vertices: a great [[W:digon|digon]] plane.|name=pairs of completely orthogonal planes}} {{Efn|In an [[24-cell#Isoclinic rotations|isoclinic rotation]], each point anywhere in the 4-polytope moves an equal distance in four orthogonal directions at once, on a [[W:8-cell#Radial equilateral symmetry|4-dimensional diagonal]]. The point is displaced a total [[W:Pythagorean distance]] equal to the square root of four times the square of that distance. For example, when the unit-radius 24-cell rotates isoclinically 60° in a hexagon invariant plane and 60° in its completely orthogonal invariant plane,{{Efn|name=pairs of completely orthogonal planes}} all vertices are displaced to a vertex two edge lengths away. Each vertex is displaced to another vertex {{radic|3}} (120°) away, moving {{radic|3/4}} in four orthogonal coordinate directions.|name=isoclinic 4-dimensional diagonal}} {{Efn|Each square plane is isoclinic (Clifford parallel) to five other square planes but completely orthogonal{{Efn|name=completely orthogonal planes}} to only one of them.{{Efn|name=Clifford parallel squares in the 16-cell and 24-cell}} Every pair of completely orthogonal planes has Clifford parallel great circles, but not all Clifford parallel great circles are orthogonal (e.g., none of the hexagonal geodesics in the 24-cell are mutually orthogonal).|name=only some Clifford parallels are orthogonal}} {{Efn|In the [[16-cell#Rotations|16-cell]] the 6 orthogonal great squares form 3 pairs of completely orthogonal great circles; each pair is Clifford parallel. In the 24-cell, the 3 inscribed 16-cells lie rotated 60 degrees isoclinically{{Efn|name=isoclinic 4-dimensional diagonal}} with respect to each other; consequently their corresponding vertices are 120 degrees apart on a hexagonal great circle. Pairing their vertices which are 90 degrees apart reveals corresponding square great circles which are Clifford parallel. Each of the 18 square great circles is Clifford parallel not only to one other square great circle in the same 16-cell (the completely orthogonal one), but also to two square great circles (which are completely orthogonal to each other) in each of the other two 16-cells. (Completely orthogonal great circles are Clifford parallel, but not all Clifford parallels are orthogonal.{{Efn|name=only some Clifford parallels are orthogonal}}) A 60 degree isoclinic rotation of the 24-cell in hexagonal invariant planes takes each square great circle to a Clifford parallel (but non-orthogonal) square great circle in a different 16-cell.|name=Clifford parallel squares in the 16-cell and 24-cell}} {{Efn|In 4 dimensional space we can construct 4 perpendicular axes and 6 perpendicular planes through a point. Without loss of generality, we may take these to be the axes and orthogonal central planes of a (w, x, y, z) Cartesian coordinate system. In 4 dimensions we have the same 3 orthogonal planes (xy, xz, yz) that we have in 3 dimensions, and also 3 others (wx, wy, wz). Each of the 6 orthogonal planes shares an axis with 4 of the others, and is ''completely orthogonal'' to just one of the others: the only one with which it does not share an axis. Thus there are 3 pairs of completely orthogonal planes: xy and wz intersect only at the origin; xz and wy intersect only at the origin; yz and wx intersect only at the origin.|name=six orthogonal planes of the Cartesian basis}} {{Efn|Two planes in 4-dimensional space can have four possible reciprocal positions: (1) they can coincide (be exactly the same plane); (2) they can be parallel (the only way they can fail to intersect at all); (3) they can intersect in a single line, as two non-parallel planes do in 3-dimensional space; or (4) '''they can intersect in a single point'''{{Efn|To visualize how two planes can intersect in a single point in a four dimensional space, consider the Euclidean space (w, x, y, z) and imagine that the w dimension represents time rather than a spatial dimension. The xy central plane (where w{{=}}0, z{{=}}0) shares no axis with the wz central plane (where x{{=}}0, y{{=}}0). The xy plane exists at only a single instant in time (w{{=}}0); the wz plane (and in particular the w axis) exists all the time. Thus their only moment and place of intersection is at the origin point (0,0,0,0).|name=how planes intersect at a single point}} (and they ''must'', if they are completely orthogonal).{{Efn|Two flat planes A and B of a Euclidean space of four dimensions are called ''completely orthogonal'' if and only if every line in A is orthogonal to every line in B. In that case the planes A and B intersect at a single point O, so that if a line in A intersects with a line in B, they intersect at O.{{Efn|name=six orthogonal planes of the Cartesian basis}}|name=completely orthogonal planes}}|name=how planes intersect}} {{Efn|Polytopes are '''completely disjoint''' if all their ''element sets'' are disjoint: they do not share any vertices, edges, faces or cells. They may still overlap in space, sharing 4-content, volume, area, or lineage.|name=completely disjoint}} {{Efn|If the [[W:Euclidean distance|Pythagorean distance]] between any two vertices is {{sqrt|1}}, their geodesic distance is 1; they may be two adjacent vertices (in the curved 3-space of the surface), or a vertex and the center (in 4-space). If their Pythagorean distance is {{sqrt|2}}, their geodesic distance is 2 (whether via 3-space or 4-space, because the path along the edges is the same straight line with one 90^o bend in it as the path through the center). If their Pythagorean distance is {{sqrt|3}}, their geodesic distance is still 2 (whether on a hexagonal great circle past one 60^o bend, or as a straight line with one 60^o bend in it through the center). Finally, if their Pythagorean distance is {{sqrt|4}}, their geodesic distance is still 2 in 4-space (straight through the center), but it reaches 3 in 3-space (by going halfway around a hexagonal great circle).|name=Geodesic distance}} {{Efn|Two angles are required to fix the relative positions of two planes in 4-space.{{Sfn|Kim|Rote|2016|p=7|loc=§6 Angles between two Planes in 4-Space|ps=; "In four (and higher) dimensions, we need two angles to fix the relative position between two planes. (More generally, ''k'' angles are defined between ''k''-dimensional subspaces.)"}} Since all planes in the same [[W:hyperplane|hyperplane]] are 0 degrees apart in one of the two angles, only one angle is required in 3-space. Great hexagons in different hyperplanes are 60 degrees apart in ''both'' angles. Great squares in different hyperplanes are 90 degrees apart in ''both'' angles (completely orthogonal){{Efn|name=completely orthogonal planes}} or 60 degrees apart in ''both'' angles.{{Efn||name=Clifford parallel squares in the 16-cell and 24-cell}} Planes which are separated by two equal angles are called ''isoclinic''. Planes which are isoclinic have [[W:Clifford parallel|Clifford parallel]] great circles.{{Efn|name=Clifford parallels}} A great square and a great hexagon in different hyperplanes are neither isoclinic nor Clifford parallel; they are separated by a 90 degree angle ''and'' a 60 degree angle.|name=two angles between central planes}} {{Efn|The 24-cell contains 3 distinct 8-cells (tesseracts), rotated 60° isoclinically with respect to each other. The corresponding vertices of two 8-cells are {{radic|3}} (120°) apart. Each 8-cell contains 8 cubical cells, and each cube contains four {{radic|3}} chords (its long diagonals). The 8-cells are not completely disjoint{{Efn|name=completely disjoint}} (they share vertices), but each cube and each {{radic|3}} chord belongs to just one 8-cell. The {{radic|3}} chords joining the corresponding vertices of two 8-cells belong to the third 8-cell.|name=three 8-cells}} {{Efn|Departing from any vertex V₀ in the original great hexagon plane of isoclinic rotation P₀, the first vertex reached V₁ is 120 degrees away along a {{radic|3}} chord lying in a different hexagonal plane P₁. P₁ is inclined to P₀ at a 60° angle.{{Efn|P₀ and P₁ lie in the same hyperplane (the same central cuboctahedron) so their other angle of separation is 0.{{Efn|name=two angles between central planes}}}} The second vertex reached V₂ is 120 degrees beyond V₁ along a second {{radic|3}} chord lying in another hexagonal plane P₂ that is Clifford parallel to P₀.{{Efn|P₀ and P₂ are 60° apart in ''both'' angles of separation.{{Efn|name=two angles between central planes}} Clifford parallel planes are isoclinic (which means they are separated by two equal angles), and their corresponding vertices are all the same distance apart. Although V₀ and V₂ are ''two'' {{radic|3}} chords apart{{Efn|V₀ and V₂ are two {{radic|3}} chords apart on the geodesic path of this rotational isocline, but that is not the shortest geodesic path between them. In the 24-cell, it is impossible for two vertices to be more distant than ''one'' {{radic|3}} chord, unless they are antipodal vertices {{radic|4}} apart.{{Efn|name=Geodesic distance}} V₀ and V₂ are ''one'' {{radic|3}} chord apart on some other isocline. More generally, isoclines are geodesics because the distance between their ''adjacent'' vertices is the shortest distance between those two vertices, but a path between two vertices along a geodesic is not always the shortest distance between them (even on ordinary great circle geodesics).}}, P₀ and P₂ are just one {{radic|1}} edge apart (at every pair of ''nearest'' vertices).}} (Notice that V₁ lies in both intersecting planes P₁ and P₂, as V₀ lies in both P₀ and P₁. But P₀ and P₂ have ''no'' vertices in common; they do not intersect.) The third vertex reached V₃ is 120 degrees beyond V₂ along a third {{radic|3}} chord lying in another hexagonal plane P₃ that is Clifford parallel to P₁. The three {{radic|3}} chords lie in different 8-cells.{{Efn|name=three 8-cells}} V₀ to V₃ is a 360° isoclinic rotation.|name=360 degree geodesic path visiting 3 hexagonal planes}} {{Sfn|Mamone, Pileio & Levitt|2010|loc=§4.5 Regular Convex 4-Polytopes|pp=1438-1439|ps=; the 24-cell has 1152 symmetry operations (rotations and reflections) as enumerated in Table 2, symmetry group 𝐹₄.}} ==Notes== {{Regular convex 4-polytopes Notelist|wiki=W:}} ==Citations== {{Regular convex 4-polytopes Reflist|wiki=W:}} ==References== {{Refbegin}} * {{Cite book|title=A Week on the Concord and Merrimack Rivers|last=Thoreau|first=Henry David|author-link=W:Thoreau|publisher=James Munroe and Company|year=1849|isbn=|location=Boston|ref={{SfnRef|Thoreau|1849}}}} * {{Cite journal|title=Theoretical Evidence for Principles of Special Relativity Based on Isotropic and Uniform Four-Dimensional Space|first=Takuya|last=Yamashita|date=25 May 2023|doi= 10.20944/preprints202305.1785.v1|journal=Preprints|volume=2023|issue=2023051785|url=https://doi.org/10.20944/preprints202305.1785.v1}} * {{Cite_arXiv | arxiv=2512.02903v2 | date=2 January 2026 | title=Symmetry transformation group arising from the Laplace–Runge–Lenz vector | first1=Stephen C. | last1=Anco | first2=Mahdieh Gol Bashmani | last2=Moghadam | class=math-ph}} === [[Polyscheme|Polyschemes]] === {{Regular convex 4-polytopes Refs|wiki=W:}} {{Refend}} r6uz1hokne3t8261eqfzwlgchw1ina2 2835214 2835212 2026-09-30T17:32:38Z Dc.samizdat 2856930 /* An object's motion in space is the product of its discrete self-reflections */ 2835214 wikitext text/x-wiki {{align|center|David Brooks Christie}} {{align|center|dc@samizdat.org}} {{align|center|Draft in progress}} {{align|center|June 2023 - September 2026}} <blockquote>'''Abstract:''' The physical universe is properly visualized as Euclidean space <math>\mathbb{R}^4</math> of four orthogonal spatial dimensions. Space itself has a fourth perpendicular dimension, of which we are unaware in ordinary life. Atoms are 4-polytopes, small round 4-dimensional objects, and stars are 4-balls of atomic plasma, large round 4-dimensional objects. We ourselves and our planet are only 3-dimensional objects, but nonetheless we can see in four dimensions of space. We have been unaware that when we look up at night we see stars and galaxies, themselves large 4-dimensional objects, distributed all around us in 4-dimensional Euclidean space, and moving through it, like us, at the constant velocity <math>c</math>. Light from them reaches us directly, on straight lines through 4-space. This view of the observed universe is compatible with special and general relativity, and with quantum mechanics. It furnishes those theories with an explanatory geometric model.</blockquote> == Summary == We observe that: * Physical space has four perpendicular dimensions, not just three. * Atoms are [[W:4-polytope|4-polytopes]]. * The sun is a [[W:4-ball|4-ball]] that is round in four dimensions. * Everything of intermediate size between an atom and a star, including us and our planet, lies in a 3-dimensional manifold of ordinary space. * Our entire 3-space manifold is moving through Euclidean 4-space at the speed of light, in a direction perpendicular to its three interior dimensions. * Special relativity describes the linear motion of objects and light signals in four-dimensional Euclidean space. == A theory of the Euclidean cosmos == The physical universe is properly visualized as [[w:Four-dimensional_space|real Euclidean space of four orthogonal spatial dimensions]] <math>\mathbb{R}^4</math>. Space itself has a fourth perpendicular dimension, of which we are unaware in ordinary life. Atoms are [[w:4-polytope|4-polytopes]], small round 4-dimensional objects, and stars are [[W:4-ball|4-balls]] of atomic plasma, large round 4-dimensional objects. Objects intermediate in size between atoms and stars, including molecules, people, and planets, are so flat as to be essentially 3-dimensional, having only the thickness of an atom in the orthogonal fourth dimension. All objects with mass move inertially through Euclidean 4-space at constant velocity <math>c</math> as long as they exist, and acceleration only varies their direction. Objects moving in the same direction are in the same inertial reference frame. Their direction of motion through 4-space at velocity <math>c</math> is their proper time dimension, simply because their direction and velocity of motion through time is the same as their direction and velocity of motion through space. A typical galaxy such as ours occupies a 4-ball of mostly empty space, with stars and other objects distributed non-uniformly within it. The galaxy's orbital center may be nothing: a smaller 4-ball of empty space they surround. The stars in our spiral galaxy appear from our accustomed point of view to occupy a disk-like region of 3-dimensional space, with a denser ball-like center, but they are not so confined: they are distributed within a region of 4-dimensional space. The disk and ball have thickness not only in the third dimension, but in the fourth spatial dimension as well. Light from stars and galaxies reaches us on straight lines through Euclidean 4-space, so from our viewpoint, in what we have always imagined to be a 3-space universe, we look into the surrounding 4-space. Although we are physically confined within a 3-dimensional hyperplane by the inertia of our motion through 4-space at constant velocity <math>c</math>, light signals are not so confined, so we observe all the cosmological objects surrounding us, both in and above or below our hyperplane, without perceiving their separation in our fourth orthogonal dimension, the direction of our motion. We may perceive a galaxy as elliptical when it is actually spherical, because that is how its image projects from its 4-ball shape into a 3-ball region in our hyperplane, where we measure it with our 3-dimensional bodies. More generally, orbits are circular in 4-space, but elliptical in the 3-space of their elliptic hyperplane. The galaxy as a whole, or more properly its orbital barycenter, is translating through 4-space at velocity <math>c</math>, in a distinct direction orthogonal to all three dimensions of our ordinary proper 3-space. Stars within the galaxy are translating with it at the same velocity <math>c</math> in the same direction, but on spiral trajectories as they pursue their various orbits within the galaxy. The galaxy as a whole occupies a 4-ball within its proper inertial reference frame (that is, in the moving frame of reference in which the galaxy considers itself to be a stationary rotating 4-ball). Over time, the galaxy 4-ball occupies a 4-dimensional cylinder and progresses along the cylinder's axis at velocity <math>c</math>. In this more universal inertial reference frame, the stars in the galaxy follow helical geodesic paths through the 4-cylinder; their trajectories are screw-translations through 4-space, the compound of a simple rotation and a completely orthogonal linear translation. The gravitational force and the inertial tendency to follow a geodesic are the same phenomenon, by the equivalence principle. That said, they can be distinguished, and the galaxy is held together primarily by gravity as inertia, not by gravity as attraction to a central mass toward which objects fall in orbit. There is not enough mass in the galaxy to hold it together by attraction, there is just enough to bend the stars' trajectories toward each other, in helical orbits around a barycentric axis of motion. It is the tremendous inertial force of stars in translational motion at velocity <math>c</math> that holds the cylinder of motion together, not some invisible dark matter. The observed universe as a whole appears to be a [[W:3-sphere|3-sphere]] expanding radially from a central origin point at velocity <math>c</math>, the invariant velocity of mass-carrying objects through 4-space, also the propagation speed of light relative to any moving 3-space manifold, as measured by all observers. A 3-sphere is a hypersphere in Euclidean 4-space, but the enclosing surface of a 3-sphere is a curved, finite 3-space, dimensionally analogous to the surface of the earth which is a curved, finite 2-space. This 3-sphere could be the domain of our visible cosmos, but of course we do not know for certain that all the cosmological objects we observe lie near the surface of our expanding 3-sphere, since it is only our assumption that they must all have originated in the same big bang long ago. Possibly some of the more distant objects we observe did not, and lie elsewhere, outside our big-bang's 3-sphere of outflying matter or even inside its 3-sphere, below its surface. We cannot assume that all objects in the 4-space universe lie near the surface of the same expanding 3-sphere. For all observers, the conjectured big-bang of their origin corresponds not only to a now-distant point in their proper time past, it also corresponds to a distinct now-distant point in 4-dimensional space: the same point in the same Euclidean 4-space for all observers with the same origin. Our big bang had a distinct origin point in real space as well as in real time. More generally, time and Euclidean 4-space can be measured independently, just as time and Euclidean 3-space were measured classically, without the necessity to combine them as spacetime. The same inertial force which holds the galactic cylinder of motion together also confines us physically to an exceedingly thin three-dimensional surface manifold moving through 4-space at velocity <math>c</math>. All objects in our solar system except the sun itself lie within this thinest three-dimensional manifold, and have only the thickness of an atom in their direction-of-motion fourth dimension. That is why we are 3-dimensional objects ourselves, and why we cannot construct more than three perpendiculars through a single point in our local 3-dimensional space. A spherical region of 4-space is called a [[W:4-ball|4-ball]]. The enclosing surface of a 4-ball of any size is a finite, curved (non-Euclidean) 3-dimensional space called a [[w:3-sphere|3-sphere]]. Our entire big-bang-origin universe appears to be the largest 3-sphere we observe, but each of the cosmological objects within it (including our galaxy and our sun) is contained in a smaller 3-sphere shell of its own, lying (we assume) on the largest 3-sphere embedded in its surface, like a soap bubble on the surface of a larger soap bubble. All the 3-dimensional surfaces are expanding, as the largest 3-sphere inflates at radial velocity <math>c</math>. We ourselves live within such an expanding 3-dimensional surface, in an infinitesimally curved 3-manifold surface embedded in Euclidean 4-space. That surface is the ordinary 3-dimensional space we experience, and it contains the earth, all the planets and the 3-dimensional space between them. Our solar system is only a small patch on the surface of a dimensionally rounder space, although that surface is not infinite. It is curved, and finite, analogous to the way the 2-dimensional surface of the earth -- once thought to be flat -- is curved and finite. Our solar system occupies a small patch on a filmy 4-dimensional soap-bubble of galactic size rounded by gravity, that is thicker-skinned than the diameter of an atom only in the interior of stars and supermassive objects. Our 3-manifold of ordinary space, as a surface within our moving 4-ball galaxy, is translating through 4-space at velocity <math>c</math> with the galaxy, in a distinct direction orthogonal to the manifold's three orthogonal dimensions of interior space. At every material point in the manifold (at every atom), the translation through 4-space is following a geometric law of motion discovered by Coxeter, that governs the propagation of individual objects through Euclidean space by the actions of their symmetry groups. The solar system's atoms of mass are 4-polytopes that are simultaneously rotating and translating, and as they advance together they define a moving 3-dimensional manifold by their own collective inertia, also called gravity, the property of matter's ceaseless propagation through 4-space at the constant velocity <math>c</math>, the universal rate of causality at which quantum events occur, all objects move, and the universe evolves. Any moving 3-dimensional manifold such as ours is an evolving surface boundary that is empty in most places, occupied by single atoms in comparatively fewer places, and occupied by bound complexes of multiple atoms (molecules) in still fewer places. In all these places it is no thicker than one atom in the dimension corresponding to its direction of translation, because molecules are 3-dimensional complexes of atoms that add no thickness to the manifold. Every object which we find occurring naturally in the solar system other than the sun itself, even the largest of 3-dimensional objects a planet, is a 3-dimensional smear of atoms no thicker than one atom in its fourth dimension, the direction of its linear translation through 4-space at velocity <math>c</math>. The moving surface manifold cannot be thicker than one atom at any point unless and until there is enough mass near that point for the force of gravity as attraction to overcome the force of gravity as inertia, allowing atoms to be "heaped up" into larger 4-dimensional objects that form a lump in its moving surface. We have little understanding of such 4-dimensional lumps thicker than one atom, since they occur naturally in our vicinity only in the interior of the sun. In fact the sun is the only such lump occurring naturally in our solar system. We refer to such 4-dimensional lumps of matter as atomic plasma, and have little experimental knowledge of their internal geometry or processes. We know that such a lump as the sun burns at its surface 3-sphere and emits radiation, and we know a good deal about those surface processes which are nuclear atomic processes, but we know almost nothing about its interior 4-ball, a dimensionally rounder enclosed space whose existence we did not suspect. Every moving surface boundary of matter in the observed universe is evolving in four dimensions at velocity <math>c</math>. The current location in 4-space of any of its material objects corresponds to the present moment in the proper time of that object's inertial reference frame. The object's direction of movement at velocity <math>c</math> corresponds to its proper time dimension, which is a spiral over time, not a Euclidean (straight-line) dimension, since its direction is changing in its orbit. Objects with mass of all sizes, from subatomic particles to the largest objects observed in the cosmos, are perpetually in inertial rotational motion in some orbit, and simultaneously in inertial translational motion propagating themselves through 4-space, in two completely orthogonal inertial motions each at the constant universal rate of transformation <math>c</math>. Every object with mass moves relative to universal 4-coordinate Euclidean space on its own distinct geodesic spiral, a screw displacement trajectory that is the compound of its two completely orthogonal inertial motions, a rotation and a translation. Objects without mass such as photons lie off such moving surface boundaries of matter from which they were emitted, and their motion is of a different nature. They are in translational motion at velocity <math>c</math> through all four dimensions concurrently, without any rotational component of motion, so they move through 4-space on straight lines at a compound velocity. The propagation speed of light measured on a straight line through Euclidean 4-space is <math>c\prime = 2c</math>, so we can see in four dimensions, even though we are physically confined to a 3-dimensional manifold that is moving at velocity <math>c</math>. For example, we can look across the center of the mostly-empty 4-ball containing our galaxy and see stars in the opposite sides of its concentric 3-sphere orbital surfaces. We have been unaware that when we look up at night we see stars and galaxies, themselves large 4-dimensional objects, distributed all around us in 4-dimensional Euclidean space, and moving through it, like us, at the constant velocity <math>c</math>. They move in the 4-space direction corresponding to their proper time, perpendicular to all three dimensions of their proper 3-space, and generally the farther they are from us the greater the divergence of their direction of motion from our direction of motion: the greater the relative motion between us and their Hubble redshift. Light from them reaches us directly, propagating on straight lines through 4-space at twice the velocity at which they, and we ourselves, are propagating through 4-space. This physical model of the observed universe is compatible with the theories of special and general relativity, and with the atomic theory of quantum mechanics. It explains those theories geometrically, as expressions of intrinsic symmetries in Euclidean space. == Symmetries == It is common to speak of nature as a web, and so it is, the great web of our physical experiences. Every web must have its root systems somewhere, and nature in this sense must be rooted in the symmetries which underlie physics and geometry, the [[W:Group (mathematics)|mathematics of groups]].{{Sfn|Conway, Burgiel & Goodman-Strauss|2008}} As I understand [[W:Noether's theorem|Noether's theorem]] (which is not mathematically), hers is the deepest meta-theory of nature yet, deeper than [[W:Theory of relativity|Einstein's relativity]] or [[W:Evolution|Darwin's evolution]] or [[W:Euclidean geometry|Euclid's geometry]]. It finds that all fundamental findings in physics are based on conservation laws which can be laid at the doors of distinct [[W:symmetry group |symmetry group]]s. Thus all fundamental systems in physics, as examples [[W:quantum chromodynamics|quantum chromodynamics]] (QCD) the theory of the strong force binding the atomic nucleus and [[W:quantum electrodynamics|quantum electrodynamics]] (QED) the theory of the electromagnetic force, each have a corresponding symmetry [[W:group theory|group theory]] of which they are an expression. [[W:Coxeter group|Coxeter's theory of symmetry groups]] generated by reflections did for geometry what Noether's theorem and Einstein's relativity did for physics. [[W:Coxeter|Coxeter]] showed that Euclidean geometry is based on conservation laws that correspond to distinct symmetry groups, and that their group actions express the principle of relativity. Here is Coxeter's formulation of the motions of objects (their congruent transformations) in an ''n''-dimensional Euclidean space, excerpted:{{Sfn|Coxeter|1973|pp=217-218|loc=§12.2 Congruent transformations}} <blockquote>Let <math>\mathrm{Q}</math> denote a rotation, <math>\mathrm{R}</math> a reflection, <math>\mathrm{T}</math> a translation, and let <math>\mathrm{Q}^q \mathrm{R}^r\mathrm{T}</math> denote a product of several such transformations, all commutative with one another. Then <math>\mathrm{RT}</math> is a glide-reflection (in two or three dimensions), <math>\mathrm{QR}</math> is a rotary-reflection, <math>\mathrm{QT}</math> is a screw-displacement, and <math>\mathrm{Q^2}</math> is a double rotation (in four dimensions).<br> Every orthogonal transformation is expressible as:<br> :<math>\mathrm{Q}^q \mathrm{R}^r</math><br> where <math>(2^q + r \le n)</math>, the number of dimensions.<br> Transformations involving a translation are also expressible as:<br> :<math>\mathrm{Q}^q \mathrm{R}^r \mathrm{T}</math><br> where <math>(2^q + r + 1 \le n)</math>.<br> For <math>(n = 4)</math> in particular, every displacement is either a double rotation <math>\mathrm{Q}^2</math>, or a screw-displacement <math>\mathrm{QT}</math> [where the rotation component <math>\mathrm{Q}</math> is a simple rotation, but the <math>\mathrm{QT}</math> is chiral like a <math>\mathrm{Q^2}</math>]. Every enantiomorphous transformation in 4-space (reversing chirality) is a <math>\mathrm{QRT}</math>.</blockquote> If we begin with this most elemental [[w:Kinematics|kinematics]] of Coxeter's, and also assume the [[W:Galilean relativity|Galilean principle of relativity]], every displacement in 4-space can be viewed as either a <math>\mathrm{Q^2}</math> or a <math>\mathrm{QT}</math>, because we can view any <math>\mathrm{QT}</math> as a <math>\mathrm{Q^2}</math> in a linearly moving (translating) reference frame. Therefore any transformation from one inertial reference frame to another is expressable as a <math>\mathrm{Q^2}</math>. By the same principle, we can view any <math>\mathrm{QT}</math> or <math>\mathrm{Q^2}</math> as an isoclinic (equi-angled) <math>\mathrm{Q^2}</math> by proper choice of reference frame.{{Efn|[[W:Arthur Cayley|Cayley]] showed that any rotation in 4-space can be decomposed into two isoclinic rotations, which intuitively we might see follows from the fact that any transformation from one inertial reference frame to another is expressable as a [[W:SO(4)|rotation in 4-dimensional Euclidean space]].|name=Cayley's rotation factorization into two isoclinic reference frame transformations}} Coxeter's relation is thus a mathematical statement of the principle of relativity, on group-theoretic grounds. It correctly captures the limits to [[W:General relativity|general relativity]], in that we can only exchange the translation (<math>\mathrm{T}</math>) for ''one'' of the two rotations (<math>\mathrm{Q}</math>). An observer in any inertial reference frame can always measure the presence, direction and velocity of ''one'' rotation (<math>\mathrm{Q}</math>) up to uncertainty, and can always distinguish the direction of their own proper time translation (<math>\mathrm{T}</math>). As I understand Coxeter theory (which is not mathematically), the symmetry groups underlying physics seem to have an expression in a [[W:Euclidean space|Euclidean space]] of four [[W:dimension|dimension]]s, that is, they are [[W:Euclidean geometry#Higher dimensions|four-dimensional Euclidean geometry]]. Therefore as I understand that geometry (which is entirely by synthetic methods rather than by Clifford's algebraic methods), the [[W:Atom|atom]] seems to have a distinct Euclidean geometry, such that atoms and their constituent particles are four-dimensional geometric objects (4-polytopes), and nature can be understood in terms of their [[W:group action|group actions]], including centrally their group <math>SO(4)</math> [[W:rotations in 4-dimensional Euclidean space|rotations in 4-dimensional Euclidean space]]. The distinct Coxeter symmetry groups have characteristic <math>SO(4)</math> rotational expressions as the [[W:Regular_4-polytope|regular 4-polytopes]]. Their discrete isoclinic rotations are distinguishing properties of fundamental objects in geometry, relativity and quantum mechanics. For example, atoms exhibit <math>SO(4)</math> symmetries of the discrete isoclinic (equi-angled) double rotations (<math>\mathrm{Q^2}</math>) of a set of regular 4-polytopes that is characteristic of their [[w:Atomic_number|atomic number]]. == Special relativity describes Euclidean 4-space == <blockquote>Our entire model of the universe is built on symmetries. Some, like isotropy (the laws are the same in all directions), homogeneity (same in all places), and time invariance (same at all times) seem natural enough. Even relativity, the Lorentz Invariance that allows everyone to observe a constant speed of light, has an elegance to it that makes it seem natural.<ref>{{Cite book|first=Dave|last=Goldberg|title=The Universe in the Rearview Mirror: How Hidden Symmetries Shape Reality|chapter=§10. Hidden Symmetries: Why some symmetries but not others?|year=2013|publisher=Dutton Penguin Group|isbn=978-0-525-95366-1|ref={{SfnRef|Goldberg|2013}}}}</ref></blockquote> Although the Minkowski spacetime of relativity is a non-Euclidean 4-dimensional space,{{Efn|Spacetime is a non-Euclidean (curved) 4-dimensional space because it consists of three orthogonal space dimensions and a time dimension. The time dimension is not orthogonal to the three spatial dimensions; the time coordinate has the opposite sign to the three space coordinates so spacetime is hyperbolic, not a flat Euclidean 4-space at all.}} it has been noticed that its 3-dimensional space component could be modeled as a [[W:3-sphere|3-sphere]] embedded in 4-dimensional Euclidean (flat) space. That is, we could imagine that the ordinary 3-dimensional space we perceive is the curved 3-dimensional surface of a 4-dimensional ball (since the surface of a 4-ball is a curved 3-dimensional space called a 3-sphere, just as the surface of a 3-ball like the earth is a curved 2-dimensional space called a 2-sphere). This was [[#Origins of the theory|imagined by Einstein]] himself in 1921, as a thought experiment in which he carefully described his fourth orthogonal spatial dimension as merely a mathematical abstraction. Subsequently it was noticed by others (not mainstream physicists) that if physical space were really embedded in Euclidean 4-dimensional space (with our 3-dimensional space embedded in 4-space as some non-Euclidean 3-manifold, not necessarily a 3-sphere), then the Lorentz transformation effects of special relativity (spatial forshortenings and time dilations and so forth) could all be explained by ordinary perspective geometry in 4-dimensional Euclidean space. Special relativity reduces to classical vector space geometry (based on the 4-dimensional version of the Pythagorean theorem), but if and only if every observer is moving through 4-space at a universal constant velocity <math>c</math>, in some 4-space direction.{{Sfn|Yamashita|2023}} This counter-intuitive alternative geometric model of relativity, which has usually been called [[W:Formulations of special relativity#Euclidean relativity|Euclidean relativity]], is motivated by the fact that in every kind of relativity, but originally in Einstein's special relativity, each observer moves on a vector through a Euclidean four-dimensional space consisting of their three proper spatial dimensions and their proper time dimension, and the Pythagorean vector-sum of their motion through this kind of proper 4-space is always <math>c</math>, as measured by all observers from any inertial reference frame.{{Efn|Each observer is stationary in space in their own proper reference frame, while they move at maximum velocity {{Math|c}} through their own proper time. Observed from another reference frame in relative motion, they appear foreshortened in space in their direction of motion, and their clocks appear to be slowed to less than the maximum velocity {{Math|c}}.}} This is the Lorentz invariant, that allows everyone to observe a constant speed of light, regardless of their motion relative to the light source.{{Efn| ...cite Lewis Epstein's elegant explanation of the Lorentz Invariance as observers moving at constant velocity {{Math|c}} through space and proper time.}} But no physicists have taken the leap of claiming that therefore, our universe is physically [[W:Euclidean geometry#Higher dimensions|this kind of Euclidean 4-space]], and that observers are actually moving through it at velocity <math>c</math>. In physics as it has been universally understood, observers are not supposed to be able to move at velocity <math>c</math>. Their motion takes place in 3-space and in universal coordinate time (in Minkowski spacetime), and the cosmos is considered to be a non-Euclidean 3-space, generally a closed (finite) expanding 3-space, but with only three spatial dimensions, not four. In the Euclidean relativity alternative view, however, every observer is always moving at velocity <math>c</math> through the universe, which is real Euclidean 4-dimensional space <math>\mathbb{R}^4</math>. The direction in which they are moving is called their proper time axis.{{Efn|Time in spacetime is universal coordinate time, but there is another kind of time in relativity, the proper time in each inertial reference frame. Your proper time is the time you experience, and every observer has his own proper time; proper time runs at different rates in different inertial reference frames. It runs slower (compared to universal coordinate time) in a gravitational field (according to general relativity), and observers in motion with respect to each other view each other's clocks as running slower than their own clocks (according to special relativity).}} Their movement in time is not just modelled as movement in an abstract fourth dimension (as it is in Minkowski spacetime), their movement in time is isomorphic to their movement through physical space in a distinct direction at velocity <math>c</math>. Two observers' directions of movement through space may be different (or not, if they happen to be going in the same direction). Your proper time dimension is whichever direction you are moving. The other three directions perpendicular to your proper time axis are the three dimensions of your ordinary proper space, which again, will be different directions for you than for other observers moving in a different direction. There are four orthogonal spatial dimensions which we all share, but we share the same orthogonal proper time axis and ordinary proper 3-space axes only if we are at rest with respect to each other, actually moving in the same direction at velocity <math>c</math>, in the same inertial reference frame. Your proper 4-space coordinate system is rotated with respect to another observer's proper 4-space coordinate system, precisely as your vectors (directions of motion) are rotated in Euclidean 4-space with respect to each other, but there are no metric distortions (no Lorentz transformations) between your proper Euclidean 4-space coordinate systems; you are both embedded in the same Euclidean 4-dimensional space <math>\mathbb{R}^4</math>. Lorentz transformations are required only to convert between your respective proper Minkowski spacetime coordinate systems. So in this novel alternate view of relativity, every mass in the universe must be perpetually in motion at velocity <math>c</math> through Euclidean 4-space, along with all the masses in its vicinity that are going in (nearly) the same direction. The entire solar system, for example, must be translating in the fourth dimension at the "speed of light" <math>c</math>, although we do not notice it, since we are all moving in that same direction together. Acceleration of an object varies its direction of motion through 4-space, but never its velocity, which is invariant for all objects with mass. Two objects which are in motion relative to each other are both actually in motion at the same velocity <math>c</math>, but in at least slightly different directions.{{Efn|The angular divergence between two observer's motion vectors is proportional to their relative velocity: the more they diverge, the greater their relative velocity, up to the maximum divergence possible in the space. In Euclidean relativity all observers are in motion at velocity {{Math|c}} relative to universal Cartesian 4-coordinate space, so the maximum relative velocity between two observers is {{Math|2c}} when they are moving in exactly opposite directions in 4-space. This is not a contradiction of special relativity, which limits the maximum relative velocity between two observers to {{Math|c}}, it is the same measurement in different units. Special relativity measures all velocities in Minkowski spacetime (in a non-Euclidean 3-space). Euclidean relativity measures all velocities in Euclidean 4-space.}} In Einstein's relativity, the invariant <math>c</math> is the speed of light through 3-space. In Euclidean relativity, the invariant <math>c</math> is the speed of matter through 4-space! The speed of light through 3-space is also perceived as <math>c</math> by all observers, because they are each living in a moving 3-manifold that is translating through 4-space at velocity <math>c</math>. Despite their extreme differences in viewpoint, Einstein's relativity and Euclidean relativity are equivalent theories in complete agreement with each other, by definition. The two theories make exactly the same special relativity predictions of how observers in different inertial reference frames will perceive each other's motions in time and space. It is beyond the scope of this present paper to show how they also agree on the predictions of general relativity, but it is important to understand that our formulation of Euclidean relativity requires our acceptance of the experimentally verified findings of special relativity, general relativity and quantum mechanics. Our model and the standard model both describe the same geometric relations of space and time based on the same evidence, but as embedded in two very different universal host spaces: Euclidean 4-space versus Minkowski spacetime. In some instances our model provides a geometric explanation for physical phenomena where the standard model has none, as yet. An example is the two models' differing explanations for the gravitational coherence of galaxies: either their inertial motion at velocity <math>c</math>, or their possession of experimentally undetected dark matter. A more central example is our use of Coxeter's kinematics to explain the laws of relativistic motion geometrically. More generally, our model is related to deep geometric properties of number elucidated by Coxeter and other geometers.{{Efn| ...cite Kappraff & Adamson's 2003 paper on The Relationship of the Cotangent Function to Special Relativity Theory, geometry and properties of number,{{Sfn|Kappraff & Adamson|2003|loc=Special Relativity Theory, Geometry and properties of number}} which shows how the Lorentz coefficient is a function of a deep geometric property of number{{Sfn|Kappraff & Adamson|2000|loc=A Fresh Look at Number}} discovered by Steinbach,{{Sfn|Steinbach|1997|loc=Golden Fields: A Case for the Heptagon}} by means of which the root formula of geometry in any Euclidean dimension, the Pythagorean theorem, may be derived solely in terms of the addition of polygon side lengths, without recourse to their products or squares. More generally, Steinbach found that in the relations among regular polytope chords, to add is to multiply; every chord is both the product (quotient) of a pair of chords and the sum (difference) of another pair of chords.}} Euclidean relativity is not even a fringe theory; no physicists or astronomers have adopted it. There are many good reasons why the revolutionary leap to a four orthogonal spatial dimensions viewpoint has not been taken, beginning with the universally observed fact that we can only construct three perpendiculars through a point in our immediate space, which appears to be resolutely 3-dimensional, not 4-dimensional. Euclidean relativity offers a nice geometric explanation of the reasons for the Lorentz transformations, but only at the cost of raising other mysteries, which have been difficult for its aficionados to explain. Another mystery is how light signals between observers in relative motion could "catch up" with the receiver moving on a diverging path through 4-space from the emitter. If both observers are already moving at <math>c</math> (on diverging paths), the propagation speed of light through 4-space between them would have to be greater than <math>c</math>. Euclidean relativity is a revolutionary theory indeed, in which <math>c</math> cannot possibly be the speed of light! We conclude that, for a theory of Euclidean 4-space to be physically viable (that is, for <math>\mathbb{R}^4</math> to be our real space and not merely an abstract mathematical space), the speed of light through Euclidean 4-space must be <math>c\prime = 2c</math>, with massless photons translating through 4-space at twice the speed of mass-carrying objects. Photons must translate the diagonal distance through 4-space along the long diameter of a unit 4-hypercube, in the same time that massive particles translate inertially along the edge (or the radius) of a unit 4-hypercube. This is conceivable in Euclidean 4-space (and in no other Euclidean space of any dimensionality) because the long diagonal of the unit 4-hypercube is the natural number <math>\sqrt{4}</math>. == An object's motion in space is the product of its discrete self-reflections == Coxeter theory describes all the possible motions of an object in space as local functions of the object's discrete geometry (its shape). Coxeter observed that in a Euclidean space of any number of dimensions, any displacement of a geometric object from one place to another, and any rotation of the object from one orientation to another, can be broken down into the product of a number of discrete self-reflections. Any action of a polytope that transforms its position and orientation in space may be measured as a distinct sequence of self-reflections of the object in its own surfaces. Any motion of the object whatsoever may be precisely described as the object propagating itself through space by a discrete sequence of local self-reflections. This is a purely kinematic description of motion which does not give any account of forces acting on the object that cause it to move. Coxeter found that both changes in position (translations) and changes in orientation (rotations) can be broken down into the simplest of all displacements (self-reflections). A translation occurs when an object self-reflects twice, in two distinct surfaces which are parallel to each other. A rotation also occurs when an object self-reflects twice, but in two distinct surfaces which intersect each other. When a object self-reflects once, it turns itself inside out (it reverses its chirality), but in translations and rotations it self-reflects twice, preserving its chirality. Coxeter's laws of kinematics are a geometric counterpart to Newton's algebraic laws of motion in three dimensional Euclidean space. They are helpful because they can be understood as geometric pictures, which may help us to visualize the relationships between translation and rotation in classic Newtonian physics problems, such as the Kepler problem of the motion of the planets.<ref>{{Cite book|last=Feynman|first=Richard|title=Feynman's Lost Lecture: The Motion of Planets Around the Sun|date=1996|publisher=W. W. Norton & Company|isbn=978-0393039184}}</ref> But they are also a revolutionary advance beyond Newton's laws, because Coxeter formulated them in Euclidean spaces of any number of dimensions. In particular, they give us geometric pictures of all the possible motions of objects in 4-dimensional Euclidean space: <blockquote>Every orthogonal transformation in 4-space is expressible as:<br> :<math>\mathrm{Q}^q \mathrm{R}^r \mathrm{T}^t</math><br> where <math>(2^q + r + t \le 4)</math>. Every displacement is either a double rotation <math>\mathrm{Q}^2</math>, or a screw-displacement <math>\mathrm{QT}</math> [where the rotation component <math>\mathrm{Q}</math> is a simple rotation, but the <math>\mathrm{QT}</math> is chiral like a <math>\mathrm{Q^2}</math>]. Every enantiomorphous transformation in 4-space (reversing chirality) is a <math>\mathrm{QRT}</math>.</blockquote> While this description should be understood as geometric pictures, some of the pictures may not be easy for us to visualize, since we have no physical experience in 4-dimensional space. Rotation (<math>\mathrm{Q}</math>), reflection (<math>\mathrm{R}</math>) and translation (<math>\mathrm{T}</math>) are obvious analogues of what they are in three-dimensional space, but double rotation (<math>\mathrm{Q}^2</math>) is something new and unprecedented in our physical experience, because double rotations cannot occur until there are four or more dimensions of space in which to rotate. A point in 4-space may be in motion on two circles in two completely orthogonal rotation planes simultaneously. Nothing constrains the two circles to be of the same radius, or constrains either circle from being of infinite radius such that the point moves in a straight line within its rotation plane: a translation <math>\mathrm{T}</math> rather than a rotation <math>\mathrm{Q}</math>. The motion of a rigid object defined by multiple points is constrained by its rigidity, such that the radii of both circles may approach infinity, but only one of the two radii may actually reach infinity. Only one of the two rotations may actually be a translation. Four dimensional Euclidean space can contain no such thing as a <math>\mathrm{Q}^2\mathrm{T}</math>. A translating double rotation <math>\mathrm{Q}^2</math>, like a translating simple rotation <math>\mathrm{Q}</math>, is simply a screw translation <math>\mathrm{QT}</math>. That is the essence of the way the principle of relativity operates in Euclidean 4-space. An object which is double-rotating in its own proper inertial reference frame may be seen to be performing nothing more mysterious than a screw translation, when observed from an inertial reference frame from which the object is in relative translational motion. In a universe which is four-dimensional Euclidean space <math>\mathbb{R}^4</math>, wherein these motions occur only at the constant velocity <math>c</math>, there is a universal Cartesian 4-coordinate reference frame in which every rigid object is translating on a <math>\mathrm{QT}</math> at velocity <math>c</math>. That universal inertial reference frame is not the proper reference frame of any object or observer, wherein the object or observer is stationary, but it is the common reference frame of all observers. == Light propagates through 4-space at twice its apparent velocity <math>c</math>== Coxeter's laws of kinematics in 4-dimensional Euclidean space apply to all objects with mass, but we find there is an additional kind of displacement which applies only to massless particles such as photons. Light quanta (photons) translate through 4-space by 4-dimensional reflection <math>\mathrm{R}^4</math>, which may be termed a double translation <math>\mathrm{T}^2</math>, a pure translation via two pairs of parallel reflections without any rotation component <math>\mathrm{Q}</math>. Matter (atoms and all particles with mass) are perpetually rotating and translating through 4-space by <math>\mathrm{QT}</math>, a screw translation of a rotating object, which is relativistically equivalent to a stationary isoclinic <math>\mathrm{Q^2}</math>, an isoclinically rotating object such as an atom. A simple rotation <math>\mathrm{Q}</math> or simple translation <math>\mathrm{T}</math> is a double reflection <math>\mathrm{R^2}</math>, so a <math>\mathrm{QT}</math> or <math>\mathrm{Q^2}</math> is an <math>\mathrm{R^4}</math>, but not with the same group of reflection angles as a light signal <math>\mathrm{R^4}</math>. A translation <math>\mathrm{T = R^2}</math> is a double reflection in two parallel planes, and a rotation <math>\mathrm{Q = R^2}</math> is a double reflection in two intersecting planes, as in a <math>\mathrm{QT = R^4}</math> which is both at once. A double translation <math>\mathrm{T^2 = R^4}</math> is two double reflections in pairs of parallel planes at once, a reflection in four non-intersecting parallel planes; it is all translation and no rotation. In a <math>\mathrm{T^2}</math> all the motion goes to translation, so the translation goes twice as far as the simple translation <math>\mathrm{T}</math> in a <math>\mathrm{QT}</math>. A double translation <math>\mathrm{T^2 = R^4}</math> is the opposite of a double rotation <math>\mathrm{Q^2 = R^4}</math>, which is stationary but rotates twice as far as the simple rotation <math>\mathrm{Q}</math> in a <math>\mathrm{QT}</math>. The product of the two translations in a <math>\mathrm{T^2}</math> is a diagonal 4-space translation over the long diameter of the unit 4-hypercube, exactly twice the distance of a simple <math>\mathrm{T}</math> over the edge length (or radius) of the unit 4-hypercube. The [[w:Tesseract|4-hypercube (also known as the 8-cell or tesseract)]] is ''radially equilateral'', which means its edge length is equal to its radius, like the hexagon, so its long diameter (twice its radius) is exactly twice its edge length. The photon moves an equal distance in four orthogonal directions. By the four-dimensional Pythagorean theorem, each of those four distances is half the total distance the photon moves: one edge length (one radius) is half the total diagonal distance moved (the long diameter). That total movement is a double-the-distance translation, but without any rotation component, so it cannot carry any mass with it. A <math>\mathrm{T^2}</math> cannot reposition a 4-polytope the way a <math>\mathrm{QT}</math> does, it can only reposition a quantum of energy that has no distinguishing rotational symmetry, such as a photon. That is the price light pays to move exactly twice as fast as matter.{{Efn| ...lensing of double translations <math>\mathrm{T^2 = R^4}</math> in more than two pairs of parallel planes at once...relationship to the frequency of light emitted and the coherence length of the wave packet...}} == Special relativity is Galilean relativity in a Euclidean space of four orthogonal dimensions == {{Efn|...TAC suggests this section is needed sooner, i.e. in the preceding Special Relativity section, as it explains how Euclidean relativity reduces special relativity to 4D perspective geometry...it's misplaced (too late) here...}} Perspective effects known as the Lorentz transformations occur because each observer's proper 3-dimensional space is a moving curved manifold embedded in flat 4-dimensional Euclidean space. The curvature of their 3-space complicates sightline calculations for observers; they sometimes require Lorentz transformations to produce the actual 4-space Cartesian coordinates of objects in the scene being observed. But if all four spatial dimensions are considered, no Lorentz transformations are required (or permitted) in correct scene construction, except when an observer wants to calculate a projection, that is, the shadow of how things will appear to them from a three-dimensional viewpoint (not how they really are).{{Sfn|Yamashita|2023}} Space really has four orthogonal dimensions, and space and time behave there just as they do in a classical vector space, only bigger by one dimension. It is not necessary to combine 4-space with time in a unified spacetime to explain 4-dimensional perspective effects at high relative velocities, because Euclidean 4-space is already 4-dimensional, and those effects fall out naturally from the 4-dimensional Pythagorean theorem, exactly as ordinary visual perspective does in three dimensions from the 3-dimensional Pythagorean theorem. Because one of the four spatial dimensions corresponds to an observer's direction of motion (in both space and proper time), and all observers and all scenes being observed are in motion (at constant velocity) in their respective proper time directions, we observe perspective foreshortenings in time as well as in a spatial dimension. In special relativity these perspective effects are reciprocal, precisely because they are only apparent, not actual, changes in size and duration. (In general relativity the actual rate of physical processes varies from place to place, and reference frame differences are neither reciprocal nor illusory.) None of these Lorentz effects are beyond geometric explanation or paradoxical. The universe is unexpectedly strange to us in precisely the ways the Euclidean fourth dimension is strange to us; but that does hold many surprises. Euclidean 4-space is much more interesting than Euclidean 3-space, analogous to the way 3-space is much more interesting and deeply explanatory to us than it would be if we experienced it only as a 2-space with many folds and curves, as perhaps an ant does. The emergent properties of 4-space are hard for us to visualize because they lie so wholly beyond our physical experience, just as it was hard for our ancestors to imagine the earth as round like a ball. However, Euclidean spaces of successive dimensions are analogous, and so higher dimensional spaces can be anticipated and explored: that is Schläfli's great discovery. Moreover dimensional analogy itself, like everything else in nature, is an exact expression of intrinsic group-theoretic symmetries: that is Nother's great discovery. == Dimensional relativity == Coxeter's kinetic law of <math>n</math>-dimensional congruent Euclidean transformations may be called ''dimensional relativity'', since it captures the theories of special and general relativity, and has its roots in dimensional analogy. Dimensional analogy is the exploration of [[w:Hermann_Grassmann#Mathematician|Hermann Grassmann's vector space principle]], in which space cannot be limited to any finite number of dimensions. The geometry of higher-dimensional space is accessable by reason of direct analogy, as [[w:Ludwig Schläfli|Ludwig Schläfli]] subsequently demonstrated. By analogy to the surface of the earth, the bounding surface of a spherical region of <math>n</math>-dimensional Euclidean space is an <math>(n-1)</math>-sphere, a spherical space of one fewer dimensions than the <math>n</math>-ball of Euclidean space it surrounds. In dimensional relativity the sky is not a ceiling, but an infinite regress of alternating spherical and Euclidean <math>n</math>-spaces of increasing <math>n</math>, accessible from each observer's point of view. By dimensional analogy, each observer looks up into their own reference frame's regress of concentric alternating <math>n</math>-spaces. By the capacity for dimensional analogy which they possess, some observers see deeper into <math>n</math>-dimensional space than others. == Polycentric spherical relativity == An intelligent observer equipped with the principle of relativity may perceive the universe from any inertial reference frame, not only from their own proper stationary reference frame in the <math>n</math>-space universe in which they physically locate themself. We see that every observer may also properly view themself as stationary and the universe as an <math>(n+1)</math>-sphere with themself at the center observing it, perceptually equidistant from all points on its <math>n</math>-space surface, including their own physical location which is one of those surface points, distinguished to them but moving on the surface, and not the center of anything. This ''polycentric model'' of the universe is a further restatement of the principle of relativity. It is compatible with Galileo's relativity of uniformly moving objects in ordinary space, Einstein's special relativity of inertial reference frames in 4-dimensional spacetime, Einstein's general relativity of all reference frames in non-Euclidean spacetime, and Coxeter's dimensional relativity of orthogonal group actions in Euclidean and spherical spaces of any number of dimensions. It should be known as Thoreau's principle of ''spherical relativity'', since the first precise written statement of it appears in 1849: "The universe is a sphere whose center is wherever there is intelligence."{{Sfn|Thoreau|1849|p=349|ps=; "The universe is a sphere whose center is wherever there is intelligence." [Contemporaneous and independent of [[W:Ludwig Schlafli|Ludwig Schlafli]]'s pioneering work enumerating the complete set of regular polyschemes in any number of dimensions.]}} == Revolutions == The original Copernican revolution in 1543 displaced the center of the universe from the center of the earth to a point farther away, the center of the sun, with the earth performing a ''revolution'' around the sun, and the stars remaining on a fixed 2-sphere around the sun instead of around the earth. But this led inevitably to the recognition that the sun must be a star itself, not equidistant from all the stars, and the center of but one of many spheres, no monotheistic center at all. In such fashion the Euclidean four-dimensional revolution, emerging three to five centuries later, initially lends itself to the big bang theory of a single origin of the whole universe, but leads inevitably to the recognition that all the galaxies need not be equidistant from a single origin in time, any more than all the stars lie in the same galaxy, equidistant from a single center in space. The expanding sphere of matter on the surface of which we find ourselves living is likely to be one of many 3-spheres expanding at velocity <math>c</math>, with their big bang origins occurring at distinct times and places in the ''n''-dimensional universe. The most distant objects we see when we look up at night may not all have the same origin in space and time. As recently as Copernicus we believed all the stars lay on a single 2-sphere embedded in Euclidean 3-space, with our sun at its center. During the enlightenment we dispersed those stars into an infinite Euclidean 3-space, and relinquished our privileged position at the center. Then Einstein showed that our 3-space could not be Euclidean, that it must be a 3-manifold curved in every place in obedience to Newton's inverse-square law of gravity; and in a geometry related to time, at least, it must be 4-dimensional. In this work we suggest a theory of ''n''-dimensional real space and how light travels in it, a theory which says we can see into four orthogonal dimensions of Euclidean space, and so when we look up at night we see cosmological objects distributed in at least four dimensions of space around us, rather than all located in our own local 3-space. Looking still deeper and farther out, the universe viewed as a 4-sphere might, or might not, be expanding, and the most distant objects we see when we look up at night may, or may not, lie in our 4-dimensional hyperplane. Real space has ''n'' dimensions as [[w:Hermann_Grassmann|Grassmann]] and [[w:Schläfli|Schläfli]] showed, and we do not know how many dimensions the most distant objects we see may be distributed in. They need not all lie within the four spatial dimensions in which we have now learned to observe them, any more than they lie in the three dimensional hyperplane of local space in which we find everything residing in our solar system. When we look up at the objects that surround us, we have no way of discerning how many dimensions beyond three the space we are looking into has. We know their distance from us primarily by virtue of how long it takes their light to reach us. We can measure their distribution around us in 3-space or 4-space, but that is simply how we choose to measure their positions, not an actual finding of how they are distributed. Even if it is now evident that they do not all lie in the same 3-space, how many more dimensions than three are needed to contain them? We observe that our 4-ball galaxy is embedded in Euclidean ''n''-space as one of many 4-ball galaxies, each translating in a distinct direction through 4-space at velocity <math>c</math>, on more or less divergent paths from each other. But only much closer observation will reveal evidence of whether everything we see lies in the same Euclidean 4-space, or if it is distributed in five or more dimensions, and how it is moving there. To remain in agreement with the theory of relativity, the Euclidean four-dimensional viewpoint requires that all mass-carrying objects be in motion in some distinct direction through 4-space at the constant velocity <math>c</math>, although the relative velocity between nearby objects is much smaller since they move on similar vectors, aimed away from a common origin point in the past. It is natural to expect that objects moving at constant velocity away from a common origin will be distributed roughly on the surface of an expanding 3-sphere. Although their paths away from their origin are not straight lines but various helical isoclines (screw translations), nearby objects must be translating radially at the same velocity, since the objects in a system (such as our solar system or galaxy) do not separate rapidly over time but remain in orbital formation. Each system's screw translation has ''two'' [[w:Completely_orthogonal|completely orthogonal]] components of motion in 4-space, an orbital rotation (such as the earth's around our sun) and a linear translation of the entire system at velocity <math>c</math> in the direction of the original 3-sphere's radial expansion (along the system's proper time vector). Of course the view from our solar system does not suggest that each galaxy's own distinct 3-sphere is expanding at this great rate from its galactic center. The standard theory has been that the entire observable universe is expanding from a single big bang origin in time, with galaxies forming later. While the Euclidean four-dimensional viewpoint lends itself to that standard theory, it also supports theories which require no single origin point in space and time. These are the voyages of starship Earth, to boldly go where no one has gone before. We made the jump to lightspeed long ago, in whatever big bang our atoms emerged from, and have never slowed down since. == Origins of the theory == Einstein himself may have been the first to imagine the universe as the three-dimensional surface of a four-dimensional Euclidean 3-sphere, in what was narrowly the first written articulation of the geometry of Euclidean 4-space relativity, contemporaneous with the teen-aged Coxeter's (quoted below).{{Efn|[[W:William Rowan Hamilton|Hamilton]]'s algebra '''H''' of [[W:Quaternions|quaternions]] contains the notion of a [[W:Three-dimensional sphere|three-dimensional sphere]] embedded in a four-dimensional space, but Hamilton did not conceive of the quaternions as the Cartesian 4-coordinates of a Euclidean 4-space, and did not describe our ordinary 3-space as embedded in Euclidean 4-space.}} Einstein did this as a [[W:Gedankenexperiment|gedankenexperiment]] in the context of investigating whether his equations of general relativity predicted an infinite or a finite universe, in his 1921 Princeton lecture.<ref>{{Cite book|url=http://www.gutenberg.org/ebooks/36276|title=The Meaning of Relativity|last=Einstein|first=Albert|publisher=Princeton University Press|year=1923|isbn=|location=|pages=110-111}}</ref> He invited us to imagine "A spherical manifold of three dimensions, embedded in a Euclidean continuum of four dimensions", but he was careful to disclaim parenthetically that "The aid of a fourth space dimension has naturally no significance except that of a mathematical artifice." Informally, the Euclidean 4-dimensional theory of relativity may be given as a sort of reciprocal to that disclaimer of Einstein's: ''The Minkowski spacetime has naturally no significance except that of a mathematical artifice, as an aid to understanding how things will appear to an observer from their perspective; the foreshortenings, clock desynchronizations and other Lorentz transformations it predicts are proper calculations of actual perspective effects; but real space is a flat, Euclidean continuum of four orthogonal spatial dimensions, and in it the ordinary laws of a flat vector space hold (such as the Pythagorean theorem), and all sightline calculations work classically, so long as you consider all four spatial dimensions.'' The Euclidean theory of relativity differs from the special theory of relativity in ascribing to the physical universe a geometry of four or more orthogonal spatial dimensions, rather than the special theory's [[w:Minkowski spacetime|Minkowski spacetime]] geometry, in which three spatial dimensions and a time dimension comprise a unified spacetime of four dimensions. Anco and Maghadam found that <math>SO(4)</math> breaks to <math>\mathbb{S}^3</math> (the 3-sphere) if the energy in the Kepler orbit is negative (an elliptical orbit), and to <math>H^3</math> (Minkowski spacetime) if the energy is positive (a hyperbolic orbit). Therefore the fact that the planets orbit on ellipses in our 3-space suggests that they orbit on a 3-sphere embedded in Euclidean 4-space which is the actual geometry of our physical universe, and Minkowski spacetime is an abstraction; the reciprocal of Einstein's disclaimer is the direct model. Of course spacetime remains a true and useful abstraction, although it must relinquish its privileged position as our exclusive conception of our place in space.{{Efn| ...origins of the Euclidean 4-space insight in the observations of Fock, Atkinson, Moser and others.}} The invention of Euclidean geometry of more than three spatial dimensions preceded Einstein's theories by more than fifty years, when it was worked out originally by the Swiss mathematician [[w:Ludwig Schläfli|Ludwig Schläfli]] before 1853.{{Sfn|Coxeter|1973|loc=§7. Ordinary Polytopes in Higher Space; §7.x. Historical remarks|pp=141-144|ps=; "Practically all the ideas in this chapter ... are due to Schläfli, who discovered them before 1853 — a time when Cayley, Grassmann and Möbius were the only other people who had ever conceived the possibility of geometry in more than three dimensions."}} Schläfli extended Euclid's geometry of one, two, and three dimensions in a direct way to four or more dimensions, generalizing the rules and terms of [[w:Euclidean geometry|Euclidean geometry]] to spaces of any number of dimensions. He coined the general term ''[[polyscheme]]'' to mean geometric forms of any number of dimensions, including two-dimensional [[w:polygon|polygons]], three-dimensional [[w:polyhedron|polyhedra]], four dimensional [[w:polychoron|polychora]], and so on, and in the process he found all of the [[w:Regular polytope|regular polyschemes]] that are possible in every dimension, including in particular the [[User:Dc.samizdat/Rotations#Sequence of regular 4-polytopes|six convex regular polychora]] which can be constructed in a Euclidean space of four dimensions (the set analogous to the five [[w:Platonic solid|Platonic solids]] the ancients found in three dimensional space). Thus Schläfli was the first to explore the fourth dimension, reveal its emergent geometric properties, and discover its astonishing regular objects. Because his work was only published posthumously in 1901, and remained almost completely unknown until Coxeter published [[w:Regular_Polytopes_(book)|Regular Polytopes]] in 1947, other researchers had more than fifty years to rediscover the regular polychora, and competing terms were coined; today [[w:Reinhold_Hoppe|Reinhold Hoppe]]'s word ''[[w:Polytope|polytope]]'' is the commonly used term for ''polyscheme.''{{Efn|[[w:Reinhold_Hoppe|Reinhold Hoppe]]'s German word ''polytop'' was introduced into English by [[W:Alicia Boole Stott|Alicia Boole Stott]], who like Hoppe and [[W:Thorold Gosset|Thorold Gosset]] rediscovered Schlafli's six regular convex 4-polytopes, with no knowledge of their prior discovery. Today Schläfli's original ''polyschem'', with its echo of ''schema'' as in the configurations of information structures, seems even more fitting in its generality than ''polytope'' -- perhaps analogously as information software (programming) is even more general than information hardware (computers).}} Because of this century-long lag in the dissemination of a scientific discovery, the regular 4-polytopes appear to have played no role at all, by any name, in the twentieth century discovery and evolution of the theories of relativity and quantum mechanics.{{Efn|One could argue that the higher-dimensional polytopes have barely influenced science or culture at all thus far. The physicist John Edward Huth's comprehensive deep dive through the history of cultural and scientific concepts of physical space, from ancient flatland models of the world through general relativity and quantum mechancs, shows exactly how we got to our present standard model of the universe, although it includes no mention of higher-dimensional Euclidean space.<ref>{{Cite book|last=Huth|first=John Edward|title=A Sense of Space: A local's guide to a flat earth, the edge of the cosmos, and other curious places|year=2025|publisher=University of Chicago Press}}</ref>}} == Boundaries == <blockquote>Ever since we discovered that Earth is round and turns like a mad-spinning top, we have understood that reality is not as it appears to us: every time we glimpse a new aspect of it, it is a deeply emotional experience. Another veil has fallen.<ref>{{Cite book|author=Carlo Rovelli|author-link=W:Carlo Rovelli|title=Seven Brief Lessons on Physics|publisher=Riverhead|year=2016|isbn=978-0399184413}}</ref></blockquote> Of course it is strange to consciously contemplate this world we inhabit, our planet, our solar system, our 3-sphere surface in our vast galaxy, as the merest film, a boundary no thicker in the places we inhabit than the diameter of an electron (though much thicker in some places we cannot inhabit, such as the interior of stars). But is not our unconscious traditional concept of the boundary of our world even stranger? Since the enlightenment we are accustomed to thinking that there is nothing beyond three dimensional space: no boundary, because there is nothing else to separate us from. But anyone who knows the [[polyscheme]]s Schläfli discovered knows that space can have any number of dimensions, and that there are fundamental objects and motions to be discovered in four dimensions that are even more various and interesting than those we can discover in three. The strange thing, when we think about it that way, is that there ''is'' a boundary between three and four dimensional space. ''Why'' can't we move (or apparently, see) in more than three dimensions? Why is our physical world apparently only three dimensional? Why would it have just ''three'' dimensions, and not four, or five, or the ''n'' dimensions that Schläfli mapped? What is the nature of the boundary which confines us to just three dimensions? We know that in Euclidean geometry the boundary between three and four dimensions is itself a spherical three dimensional space, so we should suspect that we are materially confined within such a curved boundary surface. Light need not be confined with us within our three dimensional boundary space. We would look directly through four dimensional space in our natural way, by receiving light signals that travelled through it to us on straight lines. In that case the reason we do not observe a fourth spatial dimension in our vicinity is that there are no nearby objects in it, just off our hyperplane in the wild. The nearest four-dimensional object we can see with our eyes is our sun, which lies equatorially in our own hyperplane, though it bulges out of it above and below. But when we look up at the heavens, every pinprick of light we observe is itself a four-dimensional object off our hyperplane, and they are distributed all around us in four-dimensional space through which we gaze. We are four-dimensionally sighted creatures, even though our bodies are three-dimensional objects, thin as an atom in the fourth dimension. But that should not perplex us: we can see into three dimensional space even though our retinas are two dimensional objects, thin as a photoreceptor cell. Our unconscious provincial concept is that there is nothing else outside our three dimensional world: no boundary, because there is nothing else to separate us from. But Schläfli discovered something else: all the astonishing regular objects that exist in higher dimensions, which vastly extend our notions of the beauty and mystery of space itself, and the intrinsic spatial symmetries of our universe which geometry reveals. Space is more commodious than we thought it was, and permits previously unimagined objects and motions. So our provincial conception of our place in it now has the same kind of status as our idea that the sun rises in the east and passes overhead: it is mere appearance, not a true model and no longer a proper explanation. An inertial boundary is an explanation, be it ever so thin. And would a boundary of ''no'' thickness, a mere abstraction with no physical power to separate, be a more suitable explanation? We must look for a physically powerful explanation in the geometry of space itself, which general relativity properly associates with the gravitational or inertial force. <blockquote>The number of dimensions possessed by a figure is the number of straight lines each perpendicular to all the others which can be drawn on it. Thus a point has no dimensions, a straight line one, a plane surface two, and a solid three .... In space as we now know it only three lines can be imagined perpendicular to each other. A fourth line, perpendicular to all the other three would be quite invisible and unimaginable to us. We ourselves and all the material things around us probably possess a fourth dimension, of which we are quite unaware. If not, from a four-dimensional point of view we are mere geometrical abstractions, like geometrical surfaces, lines, and points are to us. But this thickness in the fourth dimension must be exceedingly minute, if it exists at all. That is, we could only draw an exceedingly small line perpendicular to our three perpendicular lines, length, breadth and thickness, so small that no microscope could ever perceive it. We can find out something about the conditions of the fourth and higher dimensions if they exist, without being certain that they do exist, by a process which I have termed "Dimensional Analogy."<ref>{{Citation|title=Dimensional Analogy|last=Coxeter|first=Donald|date=February 1923|publisher=Coxeter Fonds, University of Toronto Archives|authorlink=W:Harold Scott MacDonald Coxeter|series=|postscript=|work=}}</ref></blockquote> I believe, but I cannot prove, that we live in real space, which is Schläfli's Euclidean space of ''n'' analogous dimensions. As Grassmann showed first, space cannot be limited to any finite number of dimensions. There will always be higher dimensions to discover, first in imagination and then to explore physically, each an astonishing new enlightenment.<ref>{{Cite book|first=T.S.|last=Eliot|title=Little Gidding|volume=Four Quartets|year=1943}}<blockquote> :We shall not cease from exploration :And the end of all our exploring :Will be to arrive where we started :And know the place for the first time. :Through the unknown, remembered gate :When the last of earth left to discover :Is that which was the beginning; :At the source of the longest river :The voice of the hidden waterfall :And the children in the apple-tree :Not known, because not looked for :But heard, half-heard, in the stillness :Between two waves of the sea. </blockquote></ref> Schläfli discovered every regular convex polytope that exists in any dimension, but that was only the beginning of the story of dimensional analogy, not its end or even the end of its beginning. That project is forever beginning anew. Coxeter discovered that Schläfli's Euclidean space is an expression of intrinsic symmetries, as Noether discovered all of physics is. Kappraff and Adamson discovered that even the sequences of humble regular polygons have fractal complexity. Symmetry itself is chaotic, always reachable but forever beyond our complete grasp. We are on a Wilderness Project, and just at its beginning, but already we observe a Euclidean space of four or more orthogonal spatial dimensions in which all objects with mass move ceaselessly at the constant velocity <math>c</math>, the universal rate at which everything moves, quantum events occur, and each of our proper times evolves. I believe these facts explain the experimentally verified theories of relativity and quantum mechanics, by revealing their unified polycentric geometry, the same way the facts about Copernicus's heliocentric solar system explained the observed motions of the planets, by revealing the geometry of gravity. But others will have to do the math, work out the physics, and perform experiments to prove or disprove all of this, because I don't have the mathematics; entirely unlike Coxeter and Einstein, I am illiterate in those languages. <blockquote> ::::::BEECH :Where my imaginary line :Bends square in woods, an iron spine :And pile of real rocks have been founded. :And off this corner in the wild, :Where these are driven in and piled, :One tree, by being deeply wounded, :Has been impressed as Witness Tree :And made commit to memory :My proof of being not unbounded. :Thus truth's established and borne out, :Though circumstanced with dark and doubt— :Though by a world of doubt surrounded. :::::::—''The Moodie Forester''<ref>{{Cite book|title=A Witness Tree|last=Frost|first=Robert|year=1942|series=The Poetry of Robert Frost|publisher=Holt, Rinehart and Winston|edition=1969|}}</ref> </blockquote> == Appendix: Sequence of regular 4-polytopes == {{Regular convex 4-polytopes|wiki=W:|columns=7}} == ... == {{Efn|In a ''[[W:William Kingdon Clifford|Clifford]] displacement'', also known as an [[W:Rotations in 4-dimensional Euclidean space#Isoclinic rotations|isoclinic rotation]], all the Clifford parallel{{Efn|name=Clifford parallels}} invariant planes are displaced in four orthogonal directions (two completely orthogonal planes) at once: they are rotated by the same angle, and at the same time they are tilted ''sideways'' by that same angle. A [[W:Rotations in 4-dimensional Euclidean space#Isoclinic rotations|Clifford displacement]] is [[W:8-cell#Radial equilateral symmetry|4-dimensionally diagonal]].{{Efn|name=isoclinic 4-dimensional diagonal}} Every plane that is Clifford parallel to one of the completely orthogonal planes (including in this case an entire Clifford parallel bundle of 4 hexagons, but not all 16 hexagons) is invariant under the isoclinic rotation: all the points in the plane rotate in circles but remain in the plane, even as the whole plane tilts sideways. All 16 hexagons rotate by the same angle (though only 4 of them do so invariantly). All 16 hexagons are rotated by 60 degrees, and also displaced sideways by 60 degrees to a Clifford parallel hexagon. All of the other central polygons (e.g. squares) are also displaced to a Clifford parallel polygon 60 degrees away.|name=Clifford displacement}} {{Efn|It is not difficult to visualize four hexagonal planes intersecting at 60 degrees to each other, even in three dimensions. Four hexagonal central planes intersect at 60 degrees in the [[W:cuboctahedron|cuboctahedron]]. Four of the 24-cell's 16 hexagonal central planes (lying in the same 3-dimensional hyperplane) intersect at each of the 24-cell's vertices exactly the way they do at the center of a cuboctahedron. But the ''edges'' around the vertex do not meet as the radii do at the center of a cuboctahedron; the 24-cell has 8 edges around each vertex, not 12, so its vertex figure is the cube, not the cuboctahedron. The 8 edges meet exactly the way 8 edges do at the apex of a canonical [[W:cubic pyramid]|cubic pyramid]].{{Efn|name=24-cell vertex figure}}|name=cuboctahedral hexagons}} {{Efn|name=radially equilateral}} {{Efn|Eight {{sqrt|1}} edges converge in curved 3-dimensional space from the corners of the 24-cell's cubical vertex figure{{Efn|The [[W:vertex figure|vertex figure]] is the facet which is made by truncating a vertex; canonically, at the mid-edges incident to the vertex. But one can make similar vertex figures of different radii by truncating at any point along those edges, up to and including truncating at the adjacent vertices to make a ''full size'' vertex figure. Stillwell defines the vertex figure as "the convex hull of the neighbouring vertices of a given vertex".{{Sfn|Stillwell|2001|p=17}} That is what serves the illustrative purpose here.|name=full size vertex figure}} and meet at its center (the vertex), where they form 4 straight lines which cross there. The 8 vertices of the cube are the eight nearest other vertices of the 24-cell. The straight lines are geodesics: two {{sqrt|1}}-length segments of an apparently straight line (in the 3-space of the 24-cell's curved surface) that is bent in the 4th dimension into a great circle hexagon (in 4-space). Imagined from inside this curved 3-space, the bends in the hexagons are invisible. From outside (if we could view the 24-cell in 4-space), the straight lines would be seen to bend in the 4th dimension at the cube centers, because the center is displaced outward in the 4th dimension, out of the hyperplane defined by the cube's vertices. Thus the vertex cube is actually a [[W:cubic pyramid|cubic pyramid]]. Unlike a cube, it seems to be radially equilateral (like the tesseract and the 24-cell itself): its "radius" equals its edge length.{{Efn|The vertex cubic pyramid is not actually radially equilateral,{{Efn|name=radially equilateral}} because the edges radiating from its apex are not actually its radii: the apex of the [[W:cubic pyramid|cubic pyramid]] is not actually its center, just one of its vertices.}}|name=24-cell vertex figure}} {{Efn|The hexagons are inclined (tilted) at 60 degrees with respect to the unit radius coordinate system's orthogonal planes. Each hexagonal plane contains only ''one'' of the 4 coordinate system axes.{{Efn|Each great hexagon of the 24-cell contains one axis (one pair of antipodal vertices) belonging to each of the three inscribed 16-cells. The 24-cell contains three disjoint inscribed 16-cells, rotated 60° isoclinically{{Efn|name=isoclinic 4-dimensional diagonal}} with respect to each other (so their corresponding vertices are 120° {{=}} {{radic|3}} apart). A [[16-cell#Coordinates|16-cell is an orthonormal ''basis'']] for a 4-dimensional coordinate system, because its 8 vertices define the four orthogonal axes. In any choice of a vertex-up coordinate system (such as the unit radius coordinates used in this article), one of the three inscribed 16-cells is the basis for the coordinate system, and each hexagon has only ''one'' axis which is a coordinate system axis.|name=three basis 16-cells}} The hexagon consists of 3 pairs of opposite vertices (three 24-cell diameters): one opposite pair of ''integer'' coordinate vertices (one of the four coordinate axes), and two opposite pairs of ''half-integer'' coordinate vertices (not coordinate axes). For example: {{indent|17}}({{spaces|2}}0,{{spaces|2}}0,{{spaces|2}}1,{{spaces|2}}0) {{indent|5}}({{spaces|2}}{{sfrac|1|2}},–{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},–{{sfrac|1|2}}){{spaces|3}}({{spaces|2}}{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}}) {{indent|5}}(–{{sfrac|1|2}},–{{sfrac|1|2}},–{{sfrac|1|2}},–{{sfrac|1|2}}){{spaces|3}}(–{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},–{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}}) {{indent|17}}({{spaces|2}}0,{{spaces|2}}0,–1,{{spaces|2}}0)<br> is a hexagon on the ''y'' axis. Unlike the {{sqrt|2}} squares, the hexagons are actually made of 24-cell edges, so they are visible features of the 24-cell.|name=non-orthogonal hexagons|group=}} {{Efn|Visualize the three [[16-cell]]s inscribed in the 24-cell (left, right, and middle), and the rotation which takes them to each other. [[24-cell#Reciprocal constructions from 8-cell and 16-cell|The vertices of the middle 16-cell lie on the (w, x, y, z) coordinate axes]];{{Efn|name=six orthogonal planes of the Cartesian basis}} the other two are rotated 60° [[W:Rotations in 4-dimensional Euclidean space#Isoclinic rotations|isoclinically]] to its left and its right. The 24-vertex 24-cell is a compound of three 16-cells, whose three sets of 8 vertices are distributed around the 24-cell symmetrically; each vertex is surrounded by 8 others (in the 3-dimensional space of the 4-dimensional 24-cell's ''surface''), the way the vertices of a cube surround its center.{{Efn|name=24-cell vertex figure}} The 8 surrounding vertices (the cube corners) lie in other 16-cells: 4 in the other 16-cell to the left, and 4 in the other 16-cell to the right. They are the vertices of two tetrahedra inscribed in the cube, one belonging (as a cell) to each 16-cell. If the 16-cell edges are {{radic|2}}, each vertex of the compound of three 16-cells is {{radic|1}} away from its 8 surrounding vertices in other 16-cells. Now visualize those {{radic|1}} distances as the edges of the 24-cell (while continuing to visualize the disjoint 16-cells). The {{radic|1}} edges form great hexagons of 6 vertices which run around the 24-cell in a central plane. ''Four'' hexagons cross at each vertex (and its antipodal vertex), inclined at 60° to each other.{{Efn|name=cuboctahedral hexagons}} The [[24-cell#Hexagons|hexagons]] are not perpendicular to each other, or to the 16-cells' perpendicular [[24-cell#Squares|square central planes]].{{Efn|name=non-orthogonal hexagons}} The left and right 16-cells form a tesseract.{{Efn|Each pair of the three 16-cells inscribed in the 24-cell forms a 4-dimensional [[W:tesseract|hypercube (a tesseract or 8-cell)]], in [[24-cell#Relationships among interior polytopes|dimensional analogy]] to the way two tetrahedra form a cube: the two 8-vertex 16-cells are inscribed in the 16-vertex tesseract, occupying its alternate vertices. The third 16-cell does not lie within the tesseract; its 8 vertices protrude from the sides of the tesseract, forming a cubic pyramid on each of the tesseract's cubic cells. The three pairs of 16-cells form three tesseracts.{{Efn|name=three 8-cells}} The tesseracts share vertices, but the 16-cells are completely disjoint.{{Efn|name=completely disjoint}}|name=three 16-cells form three tesseracts}} Two 16-cells have vertex-pairs which are one {{radic|1}} edge (one hexagon edge) apart. But a [[24-cell#Simple rotations|''simple'' rotation]] of 60° will not take one whole 16-cell to another 16-cell, because their vertices are 60° apart in different directions, and a simple rotation has only one hexagonal plane of rotation. One 16-cell ''can'' be taken to another 16-cell by a 60° [[24-cell#Isoclinic rotations|''isoclinic'' rotation]], because an isoclinic rotation is [[3-sphere]] symmetric: four [[24-cell#Clifford parallel polytopes|Clifford parallel hexagonal planes]] rotate together, but in four different rotational directions,{{Efn|name=Clifford displacement}} taking each 16-cell to another 16-cell. But since an isoclinic 60° rotation is a ''diagonal'' rotation by 60° in ''two'' completely orthogonal directions at once,{{Efn|name=isoclinic geodesic}} the corresponding vertices of the 16-cell and the 16-cell it is taken to are 120° apart: ''two'' {{radic|1}} hexagon edges (or one {{radic|3}} hexagon chord) apart, not one {{radic|1}} edge (60°) apart as in a simple rotation.{{Efn|name=isoclinic 4-dimensional diagonal}} By the [[W:chiral|chiral]] diagonal nature of isoclinic rotations, the 16-cell ''cannot'' reach the adjacent 16-cell by rotating toward it; it can only reach the 16-cell ''beyond'' it. But of course, the 16-cell beyond the 16-cell to its right is the 16-cell to its left. So a 60° isoclinic rotation ''will'' take every 16-cell to another 16-cell: a 60° ''right'' isoclinic rotation will take the middle 16-cell to the 16-cell we may have originally visualized as the ''left'' 16-cell, and a 60° ''left'' isoclinic rotation will take the middle 16-cell to the 16-cell we visualized as the ''right'' 16-cell. (If so, that was our error in visualization; the 16-cell to the "left" is in fact the one reached by the left isoclinic rotation, as that is the only sense in which the two 16-cells are left or right of each other.)|name=three isoclinic 16-cells}} {{Efn|In a double rotation each vertex can be said to move along two completely orthogonal great circles at the same time, but it does not stay within the central plane of either of those original great circles; rather, it moves along a helical geodesic that traverses diagonally between great circles. The two completely orthogonal planes of rotation are said to be ''invariant'' because the points in each stay in the plane ''as the plane moves'', tilting sideways by the same angle that the other plane rotates.|name=helical geodesic}} {{Efn|A point under isoclinic rotation traverses the diagonal{{Efn|name=isoclinic 4-dimensional diagonal}} straight line of a single '''isoclinic geodesic''', reaching its destination directly, instead of the bent line of two successive '''simple geodesics'''. A '''[[W:geodesic|geodesic]]''' is the ''shortest path'' through a space (intuitively, a string pulled taught between two points). Simple geodesics are great circles lying in a central plane (the only kind of geodesics that occur in 3-space on the 2-sphere). Isoclinic geodesics are different: they do ''not'' lie in a single plane; they are 4-dimensional [[W:helix|spirals]] rather than simple 2-dimensional circles.{{Efn|name=helical geodesic}} But they are not like 3-dimensional [[W:screw threads|screw threads]] either, because they form a closed loop like any circle (after ''two'' revolutions). Isoclinic geodesics are ''4-dimensional great circles'', and they are just as circular as 2-dimensional circles: in fact, twice as circular, because they curve in a circle in two completely orthogonal directions at once.{{Efn|Isoclinic geodesics are ''4-dimensional great circles'' in the sense that they are 1-dimensional geodesic ''lines'' that curve in 4-space in two completely orthogonal planes at once. They should not be confused with ''great 2-spheres'',{{Sfn|Stillwell|2001|p=24}} which are the 4-dimensional analogues of 2-dimensional great circles (great 1-spheres).}} These '''isoclines''' are geodesic 1-dimensional lines embedded in a 4-dimensional space. On the 3-sphere{{Efn|All isoclines are geodesics, and isoclines on the 3-sphere are circles (curving equally in each dimension), but not all isoclines on 3-manifolds in 4-space are circles.}} they always occur in [[W:chiral|chiral]] pairs and form a pair of [[W:Villarceau circle|Villarceau circle]]s on the [[W:Clifford torus|Clifford torus]],{{Efn|Isoclines on the 3-sphere occur in non-intersecting chiral pairs. A left and a right isocline form a [[W:Hopf link|Hopf link]] called the {1,1} torus knot{{Sfn|Dorst|2019|loc=§1. Villarceau Circles|p=44|ps=; "In mathematics, the path that the (1, 1) knot on the torus traces is also known as a [[W:Villarceau circle|Villarceau circle]]. Villarceau circles are usually introduced as two intersecting circles that are the cross-section of a torus by a well-chosen plane cutting it. Picking one such circle and rotating it around the torus axis, the resulting family of circles can be used to rule the torus. By nesting tori smartly, the collection of all such circles then form a [[W:Hopf fibration|Hopf fibration]].... we prefer to consider the Villarceau circle as the (1, 1) torus knot [a [[W:Hopf link|Hopf link]]] rather than as a planar cut [two intersecting circles]."}} in which ''each'' of the two linked circles traverses all four dimensions.}} the paths of the left and the right [[W:Rotations in 4-dimensional Euclidean space#Double rotations|isoclinic rotation]]. They are [[W:Helix|helices]] bent into a [[W:Möbius strip|Möbius loop]] in the fourth dimension, taking a diagonal [[W:Winding number|winding route]] twice around the 3-sphere through the non-adjacent vertices of a 4-polytope's [[W:Skew polygon#Regular skew polygons in four dimensions|skew polygon]].|name=isoclinic geodesic}} {{Efn|[[File:Hopf band wikipedia.png|thumb|150px|Two [[W:Clifford parallel|Clifford parallel]] great circles spanned by a twisted [[W:Annulus (mathematics)|annulus]].]][[W:Clifford parallel|Clifford parallel]]s are non-intersecting curved lines that are parallel in the sense that the perpendicular (shortest) distance between them is the same at each point. A double helix is an example of Clifford parallelism in ordinary 3-dimensional Euclidean space. In 4-space Clifford parallels occur as geodesic great circles on the [[W:3-sphere|3-sphere]].{{Sfn|Kim|Rote|2016|pp=8-10|loc=Relations to Clifford Parallelism}} Whereas in 3-dimensional space, any two geodesic great circles on the [[W:2-sphere|2-sphere]] will always intersect at two antipodal points, in 4-dimensional space not all great circles intersect. In 4-polytopes various discrete sets of Clifford parallel non-intersecting geodesic great circles can be found on the 3-sphere. They spiral around each other in [[W:Hopf fibration|Hopf fiber bundles]] which visit all the vertices just once. The simplest example is that six mutually orthogonal great circles can be drawn on the 3-sphere, as three pairs of completely orthogonal great circles, intersecting at 8 points defining a [[16-cell]]. Each completely orthogonal pair of circles is Clifford parallel. They cannot intersect at all, because they lie in planes which intersect at only one point: the center of the 16-cell. Because they are perpendicular and share a common center, the two circles are obviously not parallel and separate in the usual way of parallel circles in 3 dimensions; rather they are connected like adjacent links in a chain, each passing through the other without intersecting at any points, forming a [[W:Hopf link|Hopf link]]|name=Clifford parallels}} {{Efn|In the 24-cell each great square plane is completely orthogonal{{Efn|name=completely orthogonal planes}} to another great square plane, and each great hexagon plane is completely orthogonal to a plane which intersects only two vertices: a great [[W:digon|digon]] plane.|name=pairs of completely orthogonal planes}} {{Efn|In an [[24-cell#Isoclinic rotations|isoclinic rotation]], each point anywhere in the 4-polytope moves an equal distance in four orthogonal directions at once, on a [[W:8-cell#Radial equilateral symmetry|4-dimensional diagonal]]. The point is displaced a total [[W:Pythagorean distance]] equal to the square root of four times the square of that distance. For example, when the unit-radius 24-cell rotates isoclinically 60° in a hexagon invariant plane and 60° in its completely orthogonal invariant plane,{{Efn|name=pairs of completely orthogonal planes}} all vertices are displaced to a vertex two edge lengths away. Each vertex is displaced to another vertex {{radic|3}} (120°) away, moving {{radic|3/4}} in four orthogonal coordinate directions.|name=isoclinic 4-dimensional diagonal}} {{Efn|Each square plane is isoclinic (Clifford parallel) to five other square planes but completely orthogonal{{Efn|name=completely orthogonal planes}} to only one of them.{{Efn|name=Clifford parallel squares in the 16-cell and 24-cell}} Every pair of completely orthogonal planes has Clifford parallel great circles, but not all Clifford parallel great circles are orthogonal (e.g., none of the hexagonal geodesics in the 24-cell are mutually orthogonal).|name=only some Clifford parallels are orthogonal}} {{Efn|In the [[16-cell#Rotations|16-cell]] the 6 orthogonal great squares form 3 pairs of completely orthogonal great circles; each pair is Clifford parallel. In the 24-cell, the 3 inscribed 16-cells lie rotated 60 degrees isoclinically{{Efn|name=isoclinic 4-dimensional diagonal}} with respect to each other; consequently their corresponding vertices are 120 degrees apart on a hexagonal great circle. Pairing their vertices which are 90 degrees apart reveals corresponding square great circles which are Clifford parallel. Each of the 18 square great circles is Clifford parallel not only to one other square great circle in the same 16-cell (the completely orthogonal one), but also to two square great circles (which are completely orthogonal to each other) in each of the other two 16-cells. (Completely orthogonal great circles are Clifford parallel, but not all Clifford parallels are orthogonal.{{Efn|name=only some Clifford parallels are orthogonal}}) A 60 degree isoclinic rotation of the 24-cell in hexagonal invariant planes takes each square great circle to a Clifford parallel (but non-orthogonal) square great circle in a different 16-cell.|name=Clifford parallel squares in the 16-cell and 24-cell}} {{Efn|In 4 dimensional space we can construct 4 perpendicular axes and 6 perpendicular planes through a point. Without loss of generality, we may take these to be the axes and orthogonal central planes of a (w, x, y, z) Cartesian coordinate system. In 4 dimensions we have the same 3 orthogonal planes (xy, xz, yz) that we have in 3 dimensions, and also 3 others (wx, wy, wz). Each of the 6 orthogonal planes shares an axis with 4 of the others, and is ''completely orthogonal'' to just one of the others: the only one with which it does not share an axis. Thus there are 3 pairs of completely orthogonal planes: xy and wz intersect only at the origin; xz and wy intersect only at the origin; yz and wx intersect only at the origin.|name=six orthogonal planes of the Cartesian basis}} {{Efn|Two planes in 4-dimensional space can have four possible reciprocal positions: (1) they can coincide (be exactly the same plane); (2) they can be parallel (the only way they can fail to intersect at all); (3) they can intersect in a single line, as two non-parallel planes do in 3-dimensional space; or (4) '''they can intersect in a single point'''{{Efn|To visualize how two planes can intersect in a single point in a four dimensional space, consider the Euclidean space (w, x, y, z) and imagine that the w dimension represents time rather than a spatial dimension. The xy central plane (where w{{=}}0, z{{=}}0) shares no axis with the wz central plane (where x{{=}}0, y{{=}}0). The xy plane exists at only a single instant in time (w{{=}}0); the wz plane (and in particular the w axis) exists all the time. Thus their only moment and place of intersection is at the origin point (0,0,0,0).|name=how planes intersect at a single point}} (and they ''must'', if they are completely orthogonal).{{Efn|Two flat planes A and B of a Euclidean space of four dimensions are called ''completely orthogonal'' if and only if every line in A is orthogonal to every line in B. In that case the planes A and B intersect at a single point O, so that if a line in A intersects with a line in B, they intersect at O.{{Efn|name=six orthogonal planes of the Cartesian basis}}|name=completely orthogonal planes}}|name=how planes intersect}} {{Efn|Polytopes are '''completely disjoint''' if all their ''element sets'' are disjoint: they do not share any vertices, edges, faces or cells. They may still overlap in space, sharing 4-content, volume, area, or lineage.|name=completely disjoint}} {{Efn|If the [[W:Euclidean distance|Pythagorean distance]] between any two vertices is {{sqrt|1}}, their geodesic distance is 1; they may be two adjacent vertices (in the curved 3-space of the surface), or a vertex and the center (in 4-space). If their Pythagorean distance is {{sqrt|2}}, their geodesic distance is 2 (whether via 3-space or 4-space, because the path along the edges is the same straight line with one 90^o bend in it as the path through the center). If their Pythagorean distance is {{sqrt|3}}, their geodesic distance is still 2 (whether on a hexagonal great circle past one 60^o bend, or as a straight line with one 60^o bend in it through the center). Finally, if their Pythagorean distance is {{sqrt|4}}, their geodesic distance is still 2 in 4-space (straight through the center), but it reaches 3 in 3-space (by going halfway around a hexagonal great circle).|name=Geodesic distance}} {{Efn|Two angles are required to fix the relative positions of two planes in 4-space.{{Sfn|Kim|Rote|2016|p=7|loc=§6 Angles between two Planes in 4-Space|ps=; "In four (and higher) dimensions, we need two angles to fix the relative position between two planes. (More generally, ''k'' angles are defined between ''k''-dimensional subspaces.)"}} Since all planes in the same [[W:hyperplane|hyperplane]] are 0 degrees apart in one of the two angles, only one angle is required in 3-space. Great hexagons in different hyperplanes are 60 degrees apart in ''both'' angles. Great squares in different hyperplanes are 90 degrees apart in ''both'' angles (completely orthogonal){{Efn|name=completely orthogonal planes}} or 60 degrees apart in ''both'' angles.{{Efn||name=Clifford parallel squares in the 16-cell and 24-cell}} Planes which are separated by two equal angles are called ''isoclinic''. Planes which are isoclinic have [[W:Clifford parallel|Clifford parallel]] great circles.{{Efn|name=Clifford parallels}} A great square and a great hexagon in different hyperplanes are neither isoclinic nor Clifford parallel; they are separated by a 90 degree angle ''and'' a 60 degree angle.|name=two angles between central planes}} {{Efn|The 24-cell contains 3 distinct 8-cells (tesseracts), rotated 60° isoclinically with respect to each other. The corresponding vertices of two 8-cells are {{radic|3}} (120°) apart. Each 8-cell contains 8 cubical cells, and each cube contains four {{radic|3}} chords (its long diagonals). The 8-cells are not completely disjoint{{Efn|name=completely disjoint}} (they share vertices), but each cube and each {{radic|3}} chord belongs to just one 8-cell. The {{radic|3}} chords joining the corresponding vertices of two 8-cells belong to the third 8-cell.|name=three 8-cells}} {{Efn|Departing from any vertex V₀ in the original great hexagon plane of isoclinic rotation P₀, the first vertex reached V₁ is 120 degrees away along a {{radic|3}} chord lying in a different hexagonal plane P₁. P₁ is inclined to P₀ at a 60° angle.{{Efn|P₀ and P₁ lie in the same hyperplane (the same central cuboctahedron) so their other angle of separation is 0.{{Efn|name=two angles between central planes}}}} The second vertex reached V₂ is 120 degrees beyond V₁ along a second {{radic|3}} chord lying in another hexagonal plane P₂ that is Clifford parallel to P₀.{{Efn|P₀ and P₂ are 60° apart in ''both'' angles of separation.{{Efn|name=two angles between central planes}} Clifford parallel planes are isoclinic (which means they are separated by two equal angles), and their corresponding vertices are all the same distance apart. Although V₀ and V₂ are ''two'' {{radic|3}} chords apart{{Efn|V₀ and V₂ are two {{radic|3}} chords apart on the geodesic path of this rotational isocline, but that is not the shortest geodesic path between them. In the 24-cell, it is impossible for two vertices to be more distant than ''one'' {{radic|3}} chord, unless they are antipodal vertices {{radic|4}} apart.{{Efn|name=Geodesic distance}} V₀ and V₂ are ''one'' {{radic|3}} chord apart on some other isocline. More generally, isoclines are geodesics because the distance between their ''adjacent'' vertices is the shortest distance between those two vertices, but a path between two vertices along a geodesic is not always the shortest distance between them (even on ordinary great circle geodesics).}}, P₀ and P₂ are just one {{radic|1}} edge apart (at every pair of ''nearest'' vertices).}} (Notice that V₁ lies in both intersecting planes P₁ and P₂, as V₀ lies in both P₀ and P₁. But P₀ and P₂ have ''no'' vertices in common; they do not intersect.) The third vertex reached V₃ is 120 degrees beyond V₂ along a third {{radic|3}} chord lying in another hexagonal plane P₃ that is Clifford parallel to P₁. The three {{radic|3}} chords lie in different 8-cells.{{Efn|name=three 8-cells}} V₀ to V₃ is a 360° isoclinic rotation.|name=360 degree geodesic path visiting 3 hexagonal planes}} {{Sfn|Mamone, Pileio & Levitt|2010|loc=§4.5 Regular Convex 4-Polytopes|pp=1438-1439|ps=; the 24-cell has 1152 symmetry operations (rotations and reflections) as enumerated in Table 2, symmetry group 𝐹₄.}} ==Notes== {{Regular convex 4-polytopes Notelist|wiki=W:}} ==Citations== {{Regular convex 4-polytopes Reflist|wiki=W:}} ==References== {{Refbegin}} * {{Cite book|title=A Week on the Concord and Merrimack Rivers|last=Thoreau|first=Henry David|author-link=W:Thoreau|publisher=James Munroe and Company|year=1849|isbn=|location=Boston|ref={{SfnRef|Thoreau|1849}}}} * {{Cite journal|title=Theoretical Evidence for Principles of Special Relativity Based on Isotropic and Uniform Four-Dimensional Space|first=Takuya|last=Yamashita|date=25 May 2023|doi= 10.20944/preprints202305.1785.v1|journal=Preprints|volume=2023|issue=2023051785|url=https://doi.org/10.20944/preprints202305.1785.v1}} * {{Cite_arXiv | arxiv=2512.02903v2 | date=2 January 2026 | title=Symmetry transformation group arising from the Laplace–Runge–Lenz vector | first1=Stephen C. | last1=Anco | first2=Mahdieh Gol Bashmani | last2=Moghadam | class=math-ph}} === [[Polyscheme|Polyschemes]] === {{Regular convex 4-polytopes Refs|wiki=W:}} {{Refend}} oy08ibs8sa59hd0cl4xqb9i1g65t1y6 2835260 2835214 2026-10-01T02:54:52Z Dc.samizdat 2856930 /* A theory of the Euclidean cosmos */ 2835260 wikitext text/x-wiki {{align|center|David Brooks Christie}} {{align|center|dc@samizdat.org}} {{align|center|Draft in progress}} {{align|center|June 2023 - September 2026}} <blockquote>'''Abstract:''' The physical universe is properly visualized as Euclidean space <math>\mathbb{R}^4</math> of four orthogonal spatial dimensions. Space itself has a fourth perpendicular dimension, of which we are unaware in ordinary life. Atoms are 4-polytopes, small round 4-dimensional objects, and stars are 4-balls of atomic plasma, large round 4-dimensional objects. We ourselves and our planet are only 3-dimensional objects, but nonetheless we can see in four dimensions of space. We have been unaware that when we look up at night we see stars and galaxies, themselves large 4-dimensional objects, distributed all around us in 4-dimensional Euclidean space, and moving through it, like us, at the constant velocity <math>c</math>. Light from them reaches us directly, on straight lines through 4-space. This view of the observed universe is compatible with special and general relativity, and with quantum mechanics. It furnishes those theories with an explanatory geometric model.</blockquote> == Summary == We observe that: * Physical space has four perpendicular dimensions, not just three. * Atoms are [[W:4-polytope|4-polytopes]]. * The sun is a [[W:4-ball|4-ball]] that is round in four dimensions. * Everything of intermediate size between an atom and a star, including us and our planet, lies in a 3-dimensional manifold of ordinary space. * Our entire 3-space manifold is moving through Euclidean 4-space at the speed of light, in a direction perpendicular to its three interior dimensions. * Special relativity describes the linear motion of objects and light signals in four-dimensional Euclidean space. == A theory of the Euclidean cosmos == The physical universe is properly visualized as [[w:Four-dimensional_space|real Euclidean space <math>\mathbb{R}^4</math>]] of four orthogonal spatial dimensions. Space itself has a fourth perpendicular dimension, of which we are unaware in ordinary life. Atoms are [[w:4-polytope|4-polytopes]], small round 4-dimensional objects, and stars are [[W:4-ball|4-balls]] of atomic plasma, large round 4-dimensional objects. Objects intermediate in size between atoms and stars, including molecules, people, and planets, are so flat as to be essentially 3-dimensional, having only the thickness of an atom in the orthogonal fourth dimension. All objects with mass move inertially through Euclidean 4-space at constant velocity <math>c</math> as long as they exist, and acceleration only varies their direction. Objects moving in the same direction are in the same inertial reference frame. Their direction of motion through 4-space at velocity <math>c</math> is their proper time dimension, simply because their direction and velocity of motion through time is the same as their direction and velocity of motion through space. A typical galaxy such as ours occupies a 4-ball of mostly empty space, with stars and other objects distributed non-uniformly within it. The galaxy's orbital center may be nothing: a smaller 4-ball of empty space they surround. The stars in our spiral galaxy appear from our accustomed point of view to occupy a disk-like region of 3-dimensional space, with a denser ball-like center, but they are not so confined: they are distributed within a region of 4-dimensional space. The disk and ball have thickness not only in the third dimension, but in the fourth spatial dimension as well. Light from stars and galaxies reaches us on straight lines through Euclidean 4-space, so from our viewpoint, in what we have always imagined to be a 3-space universe, we look into the surrounding 4-space. Although we are physically confined within a 3-dimensional hyperplane by the inertia of our motion through 4-space at constant velocity <math>c</math>, light signals are not so confined, so we observe all the cosmological objects surrounding us, both in and above or below our hyperplane, without perceiving their separation in our fourth orthogonal dimension, the direction of our motion. We may perceive a galaxy as elliptical when it is actually spherical, because that is how its image projects from its 4-ball shape into a 3-ball region in our hyperplane, where we measure it with our 3-dimensional bodies. More generally, orbits are circular in 4-space, but elliptical in the 3-space of their elliptic hyperplane. The galaxy as a whole, or more properly its orbital barycenter, is translating through 4-space at velocity <math>c</math>, in a distinct direction orthogonal to all three dimensions of our ordinary proper 3-space. Stars within the galaxy are translating with it at the same velocity <math>c</math> in the same direction, but on spiral trajectories as they pursue their various orbits within the galaxy. The galaxy as a whole occupies a 4-ball within its proper inertial reference frame (that is, in the moving frame of reference in which the galaxy considers itself to be a stationary rotating 4-ball). Over time, the galaxy 4-ball occupies a 4-dimensional cylinder and progresses along the cylinder's axis at velocity <math>c</math>. In this more universal inertial reference frame, the stars in the galaxy follow helical geodesic paths through the 4-cylinder; their trajectories are screw-translations through 4-space, the compound of a simple rotation and a completely orthogonal linear translation. The gravitational force and the inertial tendency to follow a geodesic are the same phenomenon, by the equivalence principle. That said, they can be distinguished, and the galaxy is held together primarily by gravity as inertia, not by gravity as attraction to a central mass toward which objects fall in orbit. There is not enough mass in the galaxy to hold it together by attraction, there is just enough to bend the stars' trajectories toward each other, in helical orbits around a barycentric axis of motion. It is the tremendous inertial force of stars in translational motion at velocity <math>c</math> that holds the cylinder of motion together, not some invisible dark matter. The observed universe as a whole appears to be a [[W:3-sphere|3-sphere]] expanding radially from a central origin point at velocity <math>c</math>, the invariant velocity of mass-carrying objects through 4-space, also the propagation speed of light relative to any moving 3-space manifold, as measured by all observers. A 3-sphere is a hypersphere in Euclidean 4-space, but the enclosing surface of a 3-sphere is a curved, finite 3-space, dimensionally analogous to the surface of the earth which is a curved, finite 2-space. This 3-sphere could be the domain of our visible cosmos, but of course we do not know for certain that all the cosmological objects we observe lie near the surface of our expanding 3-sphere, since it is only our assumption that they must all have originated in the same big bang long ago. Possibly some of the more distant objects we observe did not, and lie elsewhere, outside our big-bang's 3-sphere of outflying matter or even inside its 3-sphere, below its surface. We cannot assume that all objects in the 4-space universe lie near the surface of the same expanding 3-sphere. For all observers, the conjectured big-bang of their origin corresponds not only to a now-distant point in their proper time past, it also corresponds to a distinct now-distant point in 4-dimensional space: the same point in the same Euclidean 4-space for all observers with the same origin. Our big bang had a distinct origin point in real space as well as in real time. More generally, time and Euclidean 4-space can be measured independently, just as time and Euclidean 3-space were measured classically, without the necessity to combine them as spacetime. The same inertial force which holds the galactic cylinder of motion together also confines us physically to an exceedingly thin three-dimensional surface manifold moving through 4-space at velocity <math>c</math>. All objects in our solar system except the sun itself lie within this thinest three-dimensional manifold, and have only the thickness of an atom in their direction-of-motion fourth dimension. That is why we are 3-dimensional objects ourselves, and why we cannot construct more than three perpendiculars through a single point in our local 3-dimensional space. A spherical region of 4-space is called a [[W:4-ball|4-ball]]. The enclosing surface of a 4-ball of any size is a finite, curved (non-Euclidean) 3-dimensional space called a [[w:3-sphere|3-sphere]]. Our entire big-bang-origin universe appears to be the largest 3-sphere we observe, but each of the cosmological objects within it (including our galaxy and our sun) is contained in a smaller 3-sphere shell of its own, lying (we assume) on the largest 3-sphere embedded in its surface, like a soap bubble on the surface of a larger soap bubble. All the 3-dimensional surfaces are expanding, as the largest 3-sphere inflates at radial velocity <math>c</math>. We ourselves live within such an expanding 3-dimensional surface, in an infinitesimally curved 3-manifold surface embedded in Euclidean 4-space. That surface is the ordinary 3-dimensional space we experience, and it contains the earth, all the planets and the 3-dimensional space between them. Our solar system is only a small patch on the surface of a dimensionally rounder space, although that surface is not infinite. It is curved, and finite, analogous to the way the 2-dimensional surface of the earth -- once thought to be flat -- is curved and finite. Our solar system occupies a small patch on a filmy 4-dimensional soap-bubble of galactic size rounded by gravity, that is thicker-skinned than the diameter of an atom only in the interior of stars and supermassive objects. Our 3-manifold of ordinary space, as a surface within our moving 4-ball galaxy, is translating through 4-space at velocity <math>c</math> with the galaxy, in a distinct direction orthogonal to the manifold's three orthogonal dimensions of interior space. At every material point in the manifold (at every atom), the translation through 4-space is following a geometric law of motion discovered by Coxeter, that governs the propagation of individual objects through Euclidean space by the actions of their symmetry groups. The solar system's atoms of mass are 4-polytopes that are simultaneously rotating and translating, and as they advance together they define a moving 3-dimensional manifold by their own collective inertia, also called gravity, the property of matter's ceaseless propagation through 4-space at the constant velocity <math>c</math>, the universal rate of causality at which quantum events occur, all objects move, and the universe evolves. Any moving 3-dimensional manifold such as ours is an evolving surface boundary that is empty in most places, occupied by single atoms in comparatively fewer places, and occupied by bound complexes of multiple atoms (molecules) in still fewer places. In all these places it is no thicker than one atom in the dimension corresponding to its direction of translation, because molecules are 3-dimensional complexes of atoms that add no thickness to the manifold. Every object which we find occurring naturally in the solar system other than the sun itself, even the largest of 3-dimensional objects a planet, is a 3-dimensional smear of atoms no thicker than one atom in its fourth dimension, the direction of its linear translation through 4-space at velocity <math>c</math>. The moving surface manifold cannot be thicker than one atom at any point unless and until there is enough mass near that point for the force of gravity as attraction to overcome the force of gravity as inertia, allowing atoms to be "heaped up" into larger 4-dimensional objects that form a lump in its moving surface. We have little understanding of such 4-dimensional lumps thicker than one atom, since they occur naturally in our vicinity only in the interior of the sun. In fact the sun is the only such lump occurring naturally in our solar system. We refer to such 4-dimensional lumps of matter as atomic plasma, and have little experimental knowledge of their internal geometry or processes. We know that such a lump as the sun burns at its surface 3-sphere and emits radiation, and we know a good deal about those surface processes which are nuclear atomic processes, but we know almost nothing about its interior 4-ball, a dimensionally rounder enclosed space whose existence we did not suspect. Every moving surface boundary of matter in the observed universe is evolving in four dimensions at velocity <math>c</math>. The current location in 4-space of any of its material objects corresponds to the present moment in the proper time of that object's inertial reference frame. The object's direction of movement at velocity <math>c</math> corresponds to its proper time dimension, which is a spiral over time, not a Euclidean (straight-line) dimension, since its direction is changing in its orbit. Objects with mass of all sizes, from subatomic particles to the largest objects observed in the cosmos, are perpetually in inertial rotational motion in some orbit, and simultaneously in inertial translational motion propagating themselves through 4-space, in two completely orthogonal inertial motions each at the constant universal rate of transformation <math>c</math>. Every object with mass moves relative to universal 4-coordinate Euclidean space on its own distinct geodesic spiral, a screw displacement trajectory that is the compound of its two completely orthogonal inertial motions, a rotation and a translation. Objects without mass such as photons lie off such moving surface boundaries of matter from which they were emitted, and their motion is of a different nature. They are in translational motion at velocity <math>c</math> through all four dimensions concurrently, without any rotational component of motion, so they move through 4-space on straight lines at a compound velocity. The propagation speed of light measured on a straight line through Euclidean 4-space is <math>c\prime = 2c</math>, so we can see in four dimensions, even though we are physically confined to a 3-dimensional manifold that is moving at velocity <math>c</math>. For example, we can look across the center of the mostly-empty 4-ball containing our galaxy and see stars in the opposite sides of its concentric 3-sphere orbital surfaces. We have been unaware that when we look up at night we see stars and galaxies, themselves large 4-dimensional objects, distributed all around us in 4-dimensional Euclidean space, and moving through it, like us, at the constant velocity <math>c</math>. They move in the 4-space direction corresponding to their proper time, perpendicular to all three dimensions of their proper 3-space, and generally the farther they are from us the greater the divergence of their direction of motion from our direction of motion: the greater the relative motion between us and their Hubble redshift. Light from them reaches us directly, propagating on straight lines through 4-space at twice the velocity at which they, and we ourselves, are propagating through 4-space. This physical model of the observed universe is compatible with the theories of special and general relativity, and with the atomic theory of quantum mechanics. It explains those theories geometrically, as expressions of intrinsic symmetries in Euclidean space. == Symmetries == It is common to speak of nature as a web, and so it is, the great web of our physical experiences. Every web must have its root systems somewhere, and nature in this sense must be rooted in the symmetries which underlie physics and geometry, the [[W:Group (mathematics)|mathematics of groups]].{{Sfn|Conway, Burgiel & Goodman-Strauss|2008}} As I understand [[W:Noether's theorem|Noether's theorem]] (which is not mathematically), hers is the deepest meta-theory of nature yet, deeper than [[W:Theory of relativity|Einstein's relativity]] or [[W:Evolution|Darwin's evolution]] or [[W:Euclidean geometry|Euclid's geometry]]. It finds that all fundamental findings in physics are based on conservation laws which can be laid at the doors of distinct [[W:symmetry group |symmetry group]]s. Thus all fundamental systems in physics, as examples [[W:quantum chromodynamics|quantum chromodynamics]] (QCD) the theory of the strong force binding the atomic nucleus and [[W:quantum electrodynamics|quantum electrodynamics]] (QED) the theory of the electromagnetic force, each have a corresponding symmetry [[W:group theory|group theory]] of which they are an expression. [[W:Coxeter group|Coxeter's theory of symmetry groups]] generated by reflections did for geometry what Noether's theorem and Einstein's relativity did for physics. [[W:Coxeter|Coxeter]] showed that Euclidean geometry is based on conservation laws that correspond to distinct symmetry groups, and that their group actions express the principle of relativity. Here is Coxeter's formulation of the motions of objects (their congruent transformations) in an ''n''-dimensional Euclidean space, excerpted:{{Sfn|Coxeter|1973|pp=217-218|loc=§12.2 Congruent transformations}} <blockquote>Let <math>\mathrm{Q}</math> denote a rotation, <math>\mathrm{R}</math> a reflection, <math>\mathrm{T}</math> a translation, and let <math>\mathrm{Q}^q \mathrm{R}^r\mathrm{T}</math> denote a product of several such transformations, all commutative with one another. Then <math>\mathrm{RT}</math> is a glide-reflection (in two or three dimensions), <math>\mathrm{QR}</math> is a rotary-reflection, <math>\mathrm{QT}</math> is a screw-displacement, and <math>\mathrm{Q^2}</math> is a double rotation (in four dimensions).<br> Every orthogonal transformation is expressible as:<br> :<math>\mathrm{Q}^q \mathrm{R}^r</math><br> where <math>(2^q + r \le n)</math>, the number of dimensions.<br> Transformations involving a translation are also expressible as:<br> :<math>\mathrm{Q}^q \mathrm{R}^r \mathrm{T}</math><br> where <math>(2^q + r + 1 \le n)</math>.<br> For <math>(n = 4)</math> in particular, every displacement is either a double rotation <math>\mathrm{Q}^2</math>, or a screw-displacement <math>\mathrm{QT}</math> [where the rotation component <math>\mathrm{Q}</math> is a simple rotation, but the <math>\mathrm{QT}</math> is chiral like a <math>\mathrm{Q^2}</math>]. Every enantiomorphous transformation in 4-space (reversing chirality) is a <math>\mathrm{QRT}</math>.</blockquote> If we begin with this most elemental [[w:Kinematics|kinematics]] of Coxeter's, and also assume the [[W:Galilean relativity|Galilean principle of relativity]], every displacement in 4-space can be viewed as either a <math>\mathrm{Q^2}</math> or a <math>\mathrm{QT}</math>, because we can view any <math>\mathrm{QT}</math> as a <math>\mathrm{Q^2}</math> in a linearly moving (translating) reference frame. Therefore any transformation from one inertial reference frame to another is expressable as a <math>\mathrm{Q^2}</math>. By the same principle, we can view any <math>\mathrm{QT}</math> or <math>\mathrm{Q^2}</math> as an isoclinic (equi-angled) <math>\mathrm{Q^2}</math> by proper choice of reference frame.{{Efn|[[W:Arthur Cayley|Cayley]] showed that any rotation in 4-space can be decomposed into two isoclinic rotations, which intuitively we might see follows from the fact that any transformation from one inertial reference frame to another is expressable as a [[W:SO(4)|rotation in 4-dimensional Euclidean space]].|name=Cayley's rotation factorization into two isoclinic reference frame transformations}} Coxeter's relation is thus a mathematical statement of the principle of relativity, on group-theoretic grounds. It correctly captures the limits to [[W:General relativity|general relativity]], in that we can only exchange the translation (<math>\mathrm{T}</math>) for ''one'' of the two rotations (<math>\mathrm{Q}</math>). An observer in any inertial reference frame can always measure the presence, direction and velocity of ''one'' rotation (<math>\mathrm{Q}</math>) up to uncertainty, and can always distinguish the direction of their own proper time translation (<math>\mathrm{T}</math>). As I understand Coxeter theory (which is not mathematically), the symmetry groups underlying physics seem to have an expression in a [[W:Euclidean space|Euclidean space]] of four [[W:dimension|dimension]]s, that is, they are [[W:Euclidean geometry#Higher dimensions|four-dimensional Euclidean geometry]]. Therefore as I understand that geometry (which is entirely by synthetic methods rather than by Clifford's algebraic methods), the [[W:Atom|atom]] seems to have a distinct Euclidean geometry, such that atoms and their constituent particles are four-dimensional geometric objects (4-polytopes), and nature can be understood in terms of their [[W:group action|group actions]], including centrally their group <math>SO(4)</math> [[W:rotations in 4-dimensional Euclidean space|rotations in 4-dimensional Euclidean space]]. The distinct Coxeter symmetry groups have characteristic <math>SO(4)</math> rotational expressions as the [[W:Regular_4-polytope|regular 4-polytopes]]. Their discrete isoclinic rotations are distinguishing properties of fundamental objects in geometry, relativity and quantum mechanics. For example, atoms exhibit <math>SO(4)</math> symmetries of the discrete isoclinic (equi-angled) double rotations (<math>\mathrm{Q^2}</math>) of a set of regular 4-polytopes that is characteristic of their [[w:Atomic_number|atomic number]]. == Special relativity describes Euclidean 4-space == <blockquote>Our entire model of the universe is built on symmetries. Some, like isotropy (the laws are the same in all directions), homogeneity (same in all places), and time invariance (same at all times) seem natural enough. Even relativity, the Lorentz Invariance that allows everyone to observe a constant speed of light, has an elegance to it that makes it seem natural.<ref>{{Cite book|first=Dave|last=Goldberg|title=The Universe in the Rearview Mirror: How Hidden Symmetries Shape Reality|chapter=§10. Hidden Symmetries: Why some symmetries but not others?|year=2013|publisher=Dutton Penguin Group|isbn=978-0-525-95366-1|ref={{SfnRef|Goldberg|2013}}}}</ref></blockquote> Although the Minkowski spacetime of relativity is a non-Euclidean 4-dimensional space,{{Efn|Spacetime is a non-Euclidean (curved) 4-dimensional space because it consists of three orthogonal space dimensions and a time dimension. The time dimension is not orthogonal to the three spatial dimensions; the time coordinate has the opposite sign to the three space coordinates so spacetime is hyperbolic, not a flat Euclidean 4-space at all.}} it has been noticed that its 3-dimensional space component could be modeled as a [[W:3-sphere|3-sphere]] embedded in 4-dimensional Euclidean (flat) space. That is, we could imagine that the ordinary 3-dimensional space we perceive is the curved 3-dimensional surface of a 4-dimensional ball (since the surface of a 4-ball is a curved 3-dimensional space called a 3-sphere, just as the surface of a 3-ball like the earth is a curved 2-dimensional space called a 2-sphere). This was [[#Origins of the theory|imagined by Einstein]] himself in 1921, as a thought experiment in which he carefully described his fourth orthogonal spatial dimension as merely a mathematical abstraction. Subsequently it was noticed by others (not mainstream physicists) that if physical space were really embedded in Euclidean 4-dimensional space (with our 3-dimensional space embedded in 4-space as some non-Euclidean 3-manifold, not necessarily a 3-sphere), then the Lorentz transformation effects of special relativity (spatial forshortenings and time dilations and so forth) could all be explained by ordinary perspective geometry in 4-dimensional Euclidean space. Special relativity reduces to classical vector space geometry (based on the 4-dimensional version of the Pythagorean theorem), but if and only if every observer is moving through 4-space at a universal constant velocity <math>c</math>, in some 4-space direction.{{Sfn|Yamashita|2023}} This counter-intuitive alternative geometric model of relativity, which has usually been called [[W:Formulations of special relativity#Euclidean relativity|Euclidean relativity]], is motivated by the fact that in every kind of relativity, but originally in Einstein's special relativity, each observer moves on a vector through a Euclidean four-dimensional space consisting of their three proper spatial dimensions and their proper time dimension, and the Pythagorean vector-sum of their motion through this kind of proper 4-space is always <math>c</math>, as measured by all observers from any inertial reference frame.{{Efn|Each observer is stationary in space in their own proper reference frame, while they move at maximum velocity {{Math|c}} through their own proper time. Observed from another reference frame in relative motion, they appear foreshortened in space in their direction of motion, and their clocks appear to be slowed to less than the maximum velocity {{Math|c}}.}} This is the Lorentz invariant, that allows everyone to observe a constant speed of light, regardless of their motion relative to the light source.{{Efn| ...cite Lewis Epstein's elegant explanation of the Lorentz Invariance as observers moving at constant velocity {{Math|c}} through space and proper time.}} But no physicists have taken the leap of claiming that therefore, our universe is physically [[W:Euclidean geometry#Higher dimensions|this kind of Euclidean 4-space]], and that observers are actually moving through it at velocity <math>c</math>. In physics as it has been universally understood, observers are not supposed to be able to move at velocity <math>c</math>. Their motion takes place in 3-space and in universal coordinate time (in Minkowski spacetime), and the cosmos is considered to be a non-Euclidean 3-space, generally a closed (finite) expanding 3-space, but with only three spatial dimensions, not four. In the Euclidean relativity alternative view, however, every observer is always moving at velocity <math>c</math> through the universe, which is real Euclidean 4-dimensional space <math>\mathbb{R}^4</math>. The direction in which they are moving is called their proper time axis.{{Efn|Time in spacetime is universal coordinate time, but there is another kind of time in relativity, the proper time in each inertial reference frame. Your proper time is the time you experience, and every observer has his own proper time; proper time runs at different rates in different inertial reference frames. It runs slower (compared to universal coordinate time) in a gravitational field (according to general relativity), and observers in motion with respect to each other view each other's clocks as running slower than their own clocks (according to special relativity).}} Their movement in time is not just modelled as movement in an abstract fourth dimension (as it is in Minkowski spacetime), their movement in time is isomorphic to their movement through physical space in a distinct direction at velocity <math>c</math>. Two observers' directions of movement through space may be different (or not, if they happen to be going in the same direction). Your proper time dimension is whichever direction you are moving. The other three directions perpendicular to your proper time axis are the three dimensions of your ordinary proper space, which again, will be different directions for you than for other observers moving in a different direction. There are four orthogonal spatial dimensions which we all share, but we share the same orthogonal proper time axis and ordinary proper 3-space axes only if we are at rest with respect to each other, actually moving in the same direction at velocity <math>c</math>, in the same inertial reference frame. Your proper 4-space coordinate system is rotated with respect to another observer's proper 4-space coordinate system, precisely as your vectors (directions of motion) are rotated in Euclidean 4-space with respect to each other, but there are no metric distortions (no Lorentz transformations) between your proper Euclidean 4-space coordinate systems; you are both embedded in the same Euclidean 4-dimensional space <math>\mathbb{R}^4</math>. Lorentz transformations are required only to convert between your respective proper Minkowski spacetime coordinate systems. So in this novel alternate view of relativity, every mass in the universe must be perpetually in motion at velocity <math>c</math> through Euclidean 4-space, along with all the masses in its vicinity that are going in (nearly) the same direction. The entire solar system, for example, must be translating in the fourth dimension at the "speed of light" <math>c</math>, although we do not notice it, since we are all moving in that same direction together. Acceleration of an object varies its direction of motion through 4-space, but never its velocity, which is invariant for all objects with mass. Two objects which are in motion relative to each other are both actually in motion at the same velocity <math>c</math>, but in at least slightly different directions.{{Efn|The angular divergence between two observer's motion vectors is proportional to their relative velocity: the more they diverge, the greater their relative velocity, up to the maximum divergence possible in the space. In Euclidean relativity all observers are in motion at velocity {{Math|c}} relative to universal Cartesian 4-coordinate space, so the maximum relative velocity between two observers is {{Math|2c}} when they are moving in exactly opposite directions in 4-space. This is not a contradiction of special relativity, which limits the maximum relative velocity between two observers to {{Math|c}}, it is the same measurement in different units. Special relativity measures all velocities in Minkowski spacetime (in a non-Euclidean 3-space). Euclidean relativity measures all velocities in Euclidean 4-space.}} In Einstein's relativity, the invariant <math>c</math> is the speed of light through 3-space. In Euclidean relativity, the invariant <math>c</math> is the speed of matter through 4-space! The speed of light through 3-space is also perceived as <math>c</math> by all observers, because they are each living in a moving 3-manifold that is translating through 4-space at velocity <math>c</math>. Despite their extreme differences in viewpoint, Einstein's relativity and Euclidean relativity are equivalent theories in complete agreement with each other, by definition. The two theories make exactly the same special relativity predictions of how observers in different inertial reference frames will perceive each other's motions in time and space. It is beyond the scope of this present paper to show how they also agree on the predictions of general relativity, but it is important to understand that our formulation of Euclidean relativity requires our acceptance of the experimentally verified findings of special relativity, general relativity and quantum mechanics. Our model and the standard model both describe the same geometric relations of space and time based on the same evidence, but as embedded in two very different universal host spaces: Euclidean 4-space versus Minkowski spacetime. In some instances our model provides a geometric explanation for physical phenomena where the standard model has none, as yet. An example is the two models' differing explanations for the gravitational coherence of galaxies: either their inertial motion at velocity <math>c</math>, or their possession of experimentally undetected dark matter. A more central example is our use of Coxeter's kinematics to explain the laws of relativistic motion geometrically. More generally, our model is related to deep geometric properties of number elucidated by Coxeter and other geometers.{{Efn| ...cite Kappraff & Adamson's 2003 paper on The Relationship of the Cotangent Function to Special Relativity Theory, geometry and properties of number,{{Sfn|Kappraff & Adamson|2003|loc=Special Relativity Theory, Geometry and properties of number}} which shows how the Lorentz coefficient is a function of a deep geometric property of number{{Sfn|Kappraff & Adamson|2000|loc=A Fresh Look at Number}} discovered by Steinbach,{{Sfn|Steinbach|1997|loc=Golden Fields: A Case for the Heptagon}} by means of which the root formula of geometry in any Euclidean dimension, the Pythagorean theorem, may be derived solely in terms of the addition of polygon side lengths, without recourse to their products or squares. More generally, Steinbach found that in the relations among regular polytope chords, to add is to multiply; every chord is both the product (quotient) of a pair of chords and the sum (difference) of another pair of chords.}} Euclidean relativity is not even a fringe theory; no physicists or astronomers have adopted it. There are many good reasons why the revolutionary leap to a four orthogonal spatial dimensions viewpoint has not been taken, beginning with the universally observed fact that we can only construct three perpendiculars through a point in our immediate space, which appears to be resolutely 3-dimensional, not 4-dimensional. Euclidean relativity offers a nice geometric explanation of the reasons for the Lorentz transformations, but only at the cost of raising other mysteries, which have been difficult for its aficionados to explain. Another mystery is how light signals between observers in relative motion could "catch up" with the receiver moving on a diverging path through 4-space from the emitter. If both observers are already moving at <math>c</math> (on diverging paths), the propagation speed of light through 4-space between them would have to be greater than <math>c</math>. Euclidean relativity is a revolutionary theory indeed, in which <math>c</math> cannot possibly be the speed of light! We conclude that, for a theory of Euclidean 4-space to be physically viable (that is, for <math>\mathbb{R}^4</math> to be our real space and not merely an abstract mathematical space), the speed of light through Euclidean 4-space must be <math>c\prime = 2c</math>, with massless photons translating through 4-space at twice the speed of mass-carrying objects. Photons must translate the diagonal distance through 4-space along the long diameter of a unit 4-hypercube, in the same time that massive particles translate inertially along the edge (or the radius) of a unit 4-hypercube. This is conceivable in Euclidean 4-space (and in no other Euclidean space of any dimensionality) because the long diagonal of the unit 4-hypercube is the natural number <math>\sqrt{4}</math>. == An object's motion in space is the product of its discrete self-reflections == Coxeter theory describes all the possible motions of an object in space as local functions of the object's discrete geometry (its shape). Coxeter observed that in a Euclidean space of any number of dimensions, any displacement of a geometric object from one place to another, and any rotation of the object from one orientation to another, can be broken down into the product of a number of discrete self-reflections. Any action of a polytope that transforms its position and orientation in space may be measured as a distinct sequence of self-reflections of the object in its own surfaces. Any motion of the object whatsoever may be precisely described as the object propagating itself through space by a discrete sequence of local self-reflections. This is a purely kinematic description of motion which does not give any account of forces acting on the object that cause it to move. Coxeter found that both changes in position (translations) and changes in orientation (rotations) can be broken down into the simplest of all displacements (self-reflections). A translation occurs when an object self-reflects twice, in two distinct surfaces which are parallel to each other. A rotation also occurs when an object self-reflects twice, but in two distinct surfaces which intersect each other. When a object self-reflects once, it turns itself inside out (it reverses its chirality), but in translations and rotations it self-reflects twice, preserving its chirality. Coxeter's laws of kinematics are a geometric counterpart to Newton's algebraic laws of motion in three dimensional Euclidean space. They are helpful because they can be understood as geometric pictures, which may help us to visualize the relationships between translation and rotation in classic Newtonian physics problems, such as the Kepler problem of the motion of the planets.<ref>{{Cite book|last=Feynman|first=Richard|title=Feynman's Lost Lecture: The Motion of Planets Around the Sun|date=1996|publisher=W. W. Norton & Company|isbn=978-0393039184}}</ref> But they are also a revolutionary advance beyond Newton's laws, because Coxeter formulated them in Euclidean spaces of any number of dimensions. In particular, they give us geometric pictures of all the possible motions of objects in 4-dimensional Euclidean space: <blockquote>Every orthogonal transformation in 4-space is expressible as:<br> :<math>\mathrm{Q}^q \mathrm{R}^r \mathrm{T}^t</math><br> where <math>(2^q + r + t \le 4)</math>. Every displacement is either a double rotation <math>\mathrm{Q}^2</math>, or a screw-displacement <math>\mathrm{QT}</math> [where the rotation component <math>\mathrm{Q}</math> is a simple rotation, but the <math>\mathrm{QT}</math> is chiral like a <math>\mathrm{Q^2}</math>]. Every enantiomorphous transformation in 4-space (reversing chirality) is a <math>\mathrm{QRT}</math>.</blockquote> While this description should be understood as geometric pictures, some of the pictures may not be easy for us to visualize, since we have no physical experience in 4-dimensional space. Rotation (<math>\mathrm{Q}</math>), reflection (<math>\mathrm{R}</math>) and translation (<math>\mathrm{T}</math>) are obvious analogues of what they are in three-dimensional space, but double rotation (<math>\mathrm{Q}^2</math>) is something new and unprecedented in our physical experience, because double rotations cannot occur until there are four or more dimensions of space in which to rotate. A point in 4-space may be in motion on two circles in two completely orthogonal rotation planes simultaneously. Nothing constrains the two circles to be of the same radius, or constrains either circle from being of infinite radius such that the point moves in a straight line within its rotation plane: a translation <math>\mathrm{T}</math> rather than a rotation <math>\mathrm{Q}</math>. The motion of a rigid object defined by multiple points is constrained by its rigidity, such that the radii of both circles may approach infinity, but only one of the two radii may actually reach infinity. Only one of the two rotations may actually be a translation. Four dimensional Euclidean space can contain no such thing as a <math>\mathrm{Q}^2\mathrm{T}</math>. A translating double rotation <math>\mathrm{Q}^2</math>, like a translating simple rotation <math>\mathrm{Q}</math>, is simply a screw translation <math>\mathrm{QT}</math>. That is the essence of the way the principle of relativity operates in Euclidean 4-space. An object which is double-rotating in its own proper inertial reference frame may be seen to be performing nothing more mysterious than a screw translation, when observed from an inertial reference frame from which the object is in relative translational motion. In a universe which is four-dimensional Euclidean space <math>\mathbb{R}^4</math>, wherein these motions occur only at the constant velocity <math>c</math>, there is a universal Cartesian 4-coordinate reference frame in which every rigid object is translating on a <math>\mathrm{QT}</math> at velocity <math>c</math>. That universal inertial reference frame is not the proper reference frame of any object or observer, wherein the object or observer is stationary, but it is the common reference frame of all observers. == Light propagates through 4-space at twice its apparent velocity <math>c</math>== Coxeter's laws of kinematics in 4-dimensional Euclidean space apply to all objects with mass, but we find there is an additional kind of displacement which applies only to massless particles such as photons. Light quanta (photons) translate through 4-space by 4-dimensional reflection <math>\mathrm{R}^4</math>, which may be termed a double translation <math>\mathrm{T}^2</math>, a pure translation via two pairs of parallel reflections without any rotation component <math>\mathrm{Q}</math>. Matter (atoms and all particles with mass) are perpetually rotating and translating through 4-space by <math>\mathrm{QT}</math>, a screw translation of a rotating object, which is relativistically equivalent to a stationary isoclinic <math>\mathrm{Q^2}</math>, an isoclinically rotating object such as an atom. A simple rotation <math>\mathrm{Q}</math> or simple translation <math>\mathrm{T}</math> is a double reflection <math>\mathrm{R^2}</math>, so a <math>\mathrm{QT}</math> or <math>\mathrm{Q^2}</math> is an <math>\mathrm{R^4}</math>, but not with the same group of reflection angles as a light signal <math>\mathrm{R^4}</math>. A translation <math>\mathrm{T = R^2}</math> is a double reflection in two parallel planes, and a rotation <math>\mathrm{Q = R^2}</math> is a double reflection in two intersecting planes, as in a <math>\mathrm{QT = R^4}</math> which is both at once. A double translation <math>\mathrm{T^2 = R^4}</math> is two double reflections in pairs of parallel planes at once, a reflection in four non-intersecting parallel planes; it is all translation and no rotation. In a <math>\mathrm{T^2}</math> all the motion goes to translation, so the translation goes twice as far as the simple translation <math>\mathrm{T}</math> in a <math>\mathrm{QT}</math>. A double translation <math>\mathrm{T^2 = R^4}</math> is the opposite of a double rotation <math>\mathrm{Q^2 = R^4}</math>, which is stationary but rotates twice as far as the simple rotation <math>\mathrm{Q}</math> in a <math>\mathrm{QT}</math>. The product of the two translations in a <math>\mathrm{T^2}</math> is a diagonal 4-space translation over the long diameter of the unit 4-hypercube, exactly twice the distance of a simple <math>\mathrm{T}</math> over the edge length (or radius) of the unit 4-hypercube. The [[w:Tesseract|4-hypercube (also known as the 8-cell or tesseract)]] is ''radially equilateral'', which means its edge length is equal to its radius, like the hexagon, so its long diameter (twice its radius) is exactly twice its edge length. The photon moves an equal distance in four orthogonal directions. By the four-dimensional Pythagorean theorem, each of those four distances is half the total distance the photon moves: one edge length (one radius) is half the total diagonal distance moved (the long diameter). That total movement is a double-the-distance translation, but without any rotation component, so it cannot carry any mass with it. A <math>\mathrm{T^2}</math> cannot reposition a 4-polytope the way a <math>\mathrm{QT}</math> does, it can only reposition a quantum of energy that has no distinguishing rotational symmetry, such as a photon. That is the price light pays to move exactly twice as fast as matter.{{Efn| ...lensing of double translations <math>\mathrm{T^2 = R^4}</math> in more than two pairs of parallel planes at once...relationship to the frequency of light emitted and the coherence length of the wave packet...}} == Special relativity is Galilean relativity in a Euclidean space of four orthogonal dimensions == {{Efn|...TAC suggests this section is needed sooner, i.e. in the preceding Special Relativity section, as it explains how Euclidean relativity reduces special relativity to 4D perspective geometry...it's misplaced (too late) here...}} Perspective effects known as the Lorentz transformations occur because each observer's proper 3-dimensional space is a moving curved manifold embedded in flat 4-dimensional Euclidean space. The curvature of their 3-space complicates sightline calculations for observers; they sometimes require Lorentz transformations to produce the actual 4-space Cartesian coordinates of objects in the scene being observed. But if all four spatial dimensions are considered, no Lorentz transformations are required (or permitted) in correct scene construction, except when an observer wants to calculate a projection, that is, the shadow of how things will appear to them from a three-dimensional viewpoint (not how they really are).{{Sfn|Yamashita|2023}} Space really has four orthogonal dimensions, and space and time behave there just as they do in a classical vector space, only bigger by one dimension. It is not necessary to combine 4-space with time in a unified spacetime to explain 4-dimensional perspective effects at high relative velocities, because Euclidean 4-space is already 4-dimensional, and those effects fall out naturally from the 4-dimensional Pythagorean theorem, exactly as ordinary visual perspective does in three dimensions from the 3-dimensional Pythagorean theorem. Because one of the four spatial dimensions corresponds to an observer's direction of motion (in both space and proper time), and all observers and all scenes being observed are in motion (at constant velocity) in their respective proper time directions, we observe perspective foreshortenings in time as well as in a spatial dimension. In special relativity these perspective effects are reciprocal, precisely because they are only apparent, not actual, changes in size and duration. (In general relativity the actual rate of physical processes varies from place to place, and reference frame differences are neither reciprocal nor illusory.) None of these Lorentz effects are beyond geometric explanation or paradoxical. The universe is unexpectedly strange to us in precisely the ways the Euclidean fourth dimension is strange to us; but that does hold many surprises. Euclidean 4-space is much more interesting than Euclidean 3-space, analogous to the way 3-space is much more interesting and deeply explanatory to us than it would be if we experienced it only as a 2-space with many folds and curves, as perhaps an ant does. The emergent properties of 4-space are hard for us to visualize because they lie so wholly beyond our physical experience, just as it was hard for our ancestors to imagine the earth as round like a ball. However, Euclidean spaces of successive dimensions are analogous, and so higher dimensional spaces can be anticipated and explored: that is Schläfli's great discovery. Moreover dimensional analogy itself, like everything else in nature, is an exact expression of intrinsic group-theoretic symmetries: that is Nother's great discovery. == Dimensional relativity == Coxeter's kinetic law of <math>n</math>-dimensional congruent Euclidean transformations may be called ''dimensional relativity'', since it captures the theories of special and general relativity, and has its roots in dimensional analogy. Dimensional analogy is the exploration of [[w:Hermann_Grassmann#Mathematician|Hermann Grassmann's vector space principle]], in which space cannot be limited to any finite number of dimensions. The geometry of higher-dimensional space is accessable by reason of direct analogy, as [[w:Ludwig Schläfli|Ludwig Schläfli]] subsequently demonstrated. By analogy to the surface of the earth, the bounding surface of a spherical region of <math>n</math>-dimensional Euclidean space is an <math>(n-1)</math>-sphere, a spherical space of one fewer dimensions than the <math>n</math>-ball of Euclidean space it surrounds. In dimensional relativity the sky is not a ceiling, but an infinite regress of alternating spherical and Euclidean <math>n</math>-spaces of increasing <math>n</math>, accessible from each observer's point of view. By dimensional analogy, each observer looks up into their own reference frame's regress of concentric alternating <math>n</math>-spaces. By the capacity for dimensional analogy which they possess, some observers see deeper into <math>n</math>-dimensional space than others. == Polycentric spherical relativity == An intelligent observer equipped with the principle of relativity may perceive the universe from any inertial reference frame, not only from their own proper stationary reference frame in the <math>n</math>-space universe in which they physically locate themself. We see that every observer may also properly view themself as stationary and the universe as an <math>(n+1)</math>-sphere with themself at the center observing it, perceptually equidistant from all points on its <math>n</math>-space surface, including their own physical location which is one of those surface points, distinguished to them but moving on the surface, and not the center of anything. This ''polycentric model'' of the universe is a further restatement of the principle of relativity. It is compatible with Galileo's relativity of uniformly moving objects in ordinary space, Einstein's special relativity of inertial reference frames in 4-dimensional spacetime, Einstein's general relativity of all reference frames in non-Euclidean spacetime, and Coxeter's dimensional relativity of orthogonal group actions in Euclidean and spherical spaces of any number of dimensions. It should be known as Thoreau's principle of ''spherical relativity'', since the first precise written statement of it appears in 1849: "The universe is a sphere whose center is wherever there is intelligence."{{Sfn|Thoreau|1849|p=349|ps=; "The universe is a sphere whose center is wherever there is intelligence." [Contemporaneous and independent of [[W:Ludwig Schlafli|Ludwig Schlafli]]'s pioneering work enumerating the complete set of regular polyschemes in any number of dimensions.]}} == Revolutions == The original Copernican revolution in 1543 displaced the center of the universe from the center of the earth to a point farther away, the center of the sun, with the earth performing a ''revolution'' around the sun, and the stars remaining on a fixed 2-sphere around the sun instead of around the earth. But this led inevitably to the recognition that the sun must be a star itself, not equidistant from all the stars, and the center of but one of many spheres, no monotheistic center at all. In such fashion the Euclidean four-dimensional revolution, emerging three to five centuries later, initially lends itself to the big bang theory of a single origin of the whole universe, but leads inevitably to the recognition that all the galaxies need not be equidistant from a single origin in time, any more than all the stars lie in the same galaxy, equidistant from a single center in space. The expanding sphere of matter on the surface of which we find ourselves living is likely to be one of many 3-spheres expanding at velocity <math>c</math>, with their big bang origins occurring at distinct times and places in the ''n''-dimensional universe. The most distant objects we see when we look up at night may not all have the same origin in space and time. As recently as Copernicus we believed all the stars lay on a single 2-sphere embedded in Euclidean 3-space, with our sun at its center. During the enlightenment we dispersed those stars into an infinite Euclidean 3-space, and relinquished our privileged position at the center. Then Einstein showed that our 3-space could not be Euclidean, that it must be a 3-manifold curved in every place in obedience to Newton's inverse-square law of gravity; and in a geometry related to time, at least, it must be 4-dimensional. In this work we suggest a theory of ''n''-dimensional real space and how light travels in it, a theory which says we can see into four orthogonal dimensions of Euclidean space, and so when we look up at night we see cosmological objects distributed in at least four dimensions of space around us, rather than all located in our own local 3-space. Looking still deeper and farther out, the universe viewed as a 4-sphere might, or might not, be expanding, and the most distant objects we see when we look up at night may, or may not, lie in our 4-dimensional hyperplane. Real space has ''n'' dimensions as [[w:Hermann_Grassmann|Grassmann]] and [[w:Schläfli|Schläfli]] showed, and we do not know how many dimensions the most distant objects we see may be distributed in. They need not all lie within the four spatial dimensions in which we have now learned to observe them, any more than they lie in the three dimensional hyperplane of local space in which we find everything residing in our solar system. When we look up at the objects that surround us, we have no way of discerning how many dimensions beyond three the space we are looking into has. We know their distance from us primarily by virtue of how long it takes their light to reach us. We can measure their distribution around us in 3-space or 4-space, but that is simply how we choose to measure their positions, not an actual finding of how they are distributed. Even if it is now evident that they do not all lie in the same 3-space, how many more dimensions than three are needed to contain them? We observe that our 4-ball galaxy is embedded in Euclidean ''n''-space as one of many 4-ball galaxies, each translating in a distinct direction through 4-space at velocity <math>c</math>, on more or less divergent paths from each other. But only much closer observation will reveal evidence of whether everything we see lies in the same Euclidean 4-space, or if it is distributed in five or more dimensions, and how it is moving there. To remain in agreement with the theory of relativity, the Euclidean four-dimensional viewpoint requires that all mass-carrying objects be in motion in some distinct direction through 4-space at the constant velocity <math>c</math>, although the relative velocity between nearby objects is much smaller since they move on similar vectors, aimed away from a common origin point in the past. It is natural to expect that objects moving at constant velocity away from a common origin will be distributed roughly on the surface of an expanding 3-sphere. Although their paths away from their origin are not straight lines but various helical isoclines (screw translations), nearby objects must be translating radially at the same velocity, since the objects in a system (such as our solar system or galaxy) do not separate rapidly over time but remain in orbital formation. Each system's screw translation has ''two'' [[w:Completely_orthogonal|completely orthogonal]] components of motion in 4-space, an orbital rotation (such as the earth's around our sun) and a linear translation of the entire system at velocity <math>c</math> in the direction of the original 3-sphere's radial expansion (along the system's proper time vector). Of course the view from our solar system does not suggest that each galaxy's own distinct 3-sphere is expanding at this great rate from its galactic center. The standard theory has been that the entire observable universe is expanding from a single big bang origin in time, with galaxies forming later. While the Euclidean four-dimensional viewpoint lends itself to that standard theory, it also supports theories which require no single origin point in space and time. These are the voyages of starship Earth, to boldly go where no one has gone before. We made the jump to lightspeed long ago, in whatever big bang our atoms emerged from, and have never slowed down since. == Origins of the theory == Einstein himself may have been the first to imagine the universe as the three-dimensional surface of a four-dimensional Euclidean 3-sphere, in what was narrowly the first written articulation of the geometry of Euclidean 4-space relativity, contemporaneous with the teen-aged Coxeter's (quoted below).{{Efn|[[W:William Rowan Hamilton|Hamilton]]'s algebra '''H''' of [[W:Quaternions|quaternions]] contains the notion of a [[W:Three-dimensional sphere|three-dimensional sphere]] embedded in a four-dimensional space, but Hamilton did not conceive of the quaternions as the Cartesian 4-coordinates of a Euclidean 4-space, and did not describe our ordinary 3-space as embedded in Euclidean 4-space.}} Einstein did this as a [[W:Gedankenexperiment|gedankenexperiment]] in the context of investigating whether his equations of general relativity predicted an infinite or a finite universe, in his 1921 Princeton lecture.<ref>{{Cite book|url=http://www.gutenberg.org/ebooks/36276|title=The Meaning of Relativity|last=Einstein|first=Albert|publisher=Princeton University Press|year=1923|isbn=|location=|pages=110-111}}</ref> He invited us to imagine "A spherical manifold of three dimensions, embedded in a Euclidean continuum of four dimensions", but he was careful to disclaim parenthetically that "The aid of a fourth space dimension has naturally no significance except that of a mathematical artifice." Informally, the Euclidean 4-dimensional theory of relativity may be given as a sort of reciprocal to that disclaimer of Einstein's: ''The Minkowski spacetime has naturally no significance except that of a mathematical artifice, as an aid to understanding how things will appear to an observer from their perspective; the foreshortenings, clock desynchronizations and other Lorentz transformations it predicts are proper calculations of actual perspective effects; but real space is a flat, Euclidean continuum of four orthogonal spatial dimensions, and in it the ordinary laws of a flat vector space hold (such as the Pythagorean theorem), and all sightline calculations work classically, so long as you consider all four spatial dimensions.'' The Euclidean theory of relativity differs from the special theory of relativity in ascribing to the physical universe a geometry of four or more orthogonal spatial dimensions, rather than the special theory's [[w:Minkowski spacetime|Minkowski spacetime]] geometry, in which three spatial dimensions and a time dimension comprise a unified spacetime of four dimensions. Anco and Maghadam found that <math>SO(4)</math> breaks to <math>\mathbb{S}^3</math> (the 3-sphere) if the energy in the Kepler orbit is negative (an elliptical orbit), and to <math>H^3</math> (Minkowski spacetime) if the energy is positive (a hyperbolic orbit). Therefore the fact that the planets orbit on ellipses in our 3-space suggests that they orbit on a 3-sphere embedded in Euclidean 4-space which is the actual geometry of our physical universe, and Minkowski spacetime is an abstraction; the reciprocal of Einstein's disclaimer is the direct model. Of course spacetime remains a true and useful abstraction, although it must relinquish its privileged position as our exclusive conception of our place in space.{{Efn| ...origins of the Euclidean 4-space insight in the observations of Fock, Atkinson, Moser and others.}} The invention of Euclidean geometry of more than three spatial dimensions preceded Einstein's theories by more than fifty years, when it was worked out originally by the Swiss mathematician [[w:Ludwig Schläfli|Ludwig Schläfli]] before 1853.{{Sfn|Coxeter|1973|loc=§7. Ordinary Polytopes in Higher Space; §7.x. Historical remarks|pp=141-144|ps=; "Practically all the ideas in this chapter ... are due to Schläfli, who discovered them before 1853 — a time when Cayley, Grassmann and Möbius were the only other people who had ever conceived the possibility of geometry in more than three dimensions."}} Schläfli extended Euclid's geometry of one, two, and three dimensions in a direct way to four or more dimensions, generalizing the rules and terms of [[w:Euclidean geometry|Euclidean geometry]] to spaces of any number of dimensions. He coined the general term ''[[polyscheme]]'' to mean geometric forms of any number of dimensions, including two-dimensional [[w:polygon|polygons]], three-dimensional [[w:polyhedron|polyhedra]], four dimensional [[w:polychoron|polychora]], and so on, and in the process he found all of the [[w:Regular polytope|regular polyschemes]] that are possible in every dimension, including in particular the [[User:Dc.samizdat/Rotations#Sequence of regular 4-polytopes|six convex regular polychora]] which can be constructed in a Euclidean space of four dimensions (the set analogous to the five [[w:Platonic solid|Platonic solids]] the ancients found in three dimensional space). Thus Schläfli was the first to explore the fourth dimension, reveal its emergent geometric properties, and discover its astonishing regular objects. Because his work was only published posthumously in 1901, and remained almost completely unknown until Coxeter published [[w:Regular_Polytopes_(book)|Regular Polytopes]] in 1947, other researchers had more than fifty years to rediscover the regular polychora, and competing terms were coined; today [[w:Reinhold_Hoppe|Reinhold Hoppe]]'s word ''[[w:Polytope|polytope]]'' is the commonly used term for ''polyscheme.''{{Efn|[[w:Reinhold_Hoppe|Reinhold Hoppe]]'s German word ''polytop'' was introduced into English by [[W:Alicia Boole Stott|Alicia Boole Stott]], who like Hoppe and [[W:Thorold Gosset|Thorold Gosset]] rediscovered Schlafli's six regular convex 4-polytopes, with no knowledge of their prior discovery. Today Schläfli's original ''polyschem'', with its echo of ''schema'' as in the configurations of information structures, seems even more fitting in its generality than ''polytope'' -- perhaps analogously as information software (programming) is even more general than information hardware (computers).}} Because of this century-long lag in the dissemination of a scientific discovery, the regular 4-polytopes appear to have played no role at all, by any name, in the twentieth century discovery and evolution of the theories of relativity and quantum mechanics.{{Efn|One could argue that the higher-dimensional polytopes have barely influenced science or culture at all thus far. The physicist John Edward Huth's comprehensive deep dive through the history of cultural and scientific concepts of physical space, from ancient flatland models of the world through general relativity and quantum mechancs, shows exactly how we got to our present standard model of the universe, although it includes no mention of higher-dimensional Euclidean space.<ref>{{Cite book|last=Huth|first=John Edward|title=A Sense of Space: A local's guide to a flat earth, the edge of the cosmos, and other curious places|year=2025|publisher=University of Chicago Press}}</ref>}} == Boundaries == <blockquote>Ever since we discovered that Earth is round and turns like a mad-spinning top, we have understood that reality is not as it appears to us: every time we glimpse a new aspect of it, it is a deeply emotional experience. Another veil has fallen.<ref>{{Cite book|author=Carlo Rovelli|author-link=W:Carlo Rovelli|title=Seven Brief Lessons on Physics|publisher=Riverhead|year=2016|isbn=978-0399184413}}</ref></blockquote> Of course it is strange to consciously contemplate this world we inhabit, our planet, our solar system, our 3-sphere surface in our vast galaxy, as the merest film, a boundary no thicker in the places we inhabit than the diameter of an electron (though much thicker in some places we cannot inhabit, such as the interior of stars). But is not our unconscious traditional concept of the boundary of our world even stranger? Since the enlightenment we are accustomed to thinking that there is nothing beyond three dimensional space: no boundary, because there is nothing else to separate us from. But anyone who knows the [[polyscheme]]s Schläfli discovered knows that space can have any number of dimensions, and that there are fundamental objects and motions to be discovered in four dimensions that are even more various and interesting than those we can discover in three. The strange thing, when we think about it that way, is that there ''is'' a boundary between three and four dimensional space. ''Why'' can't we move (or apparently, see) in more than three dimensions? Why is our physical world apparently only three dimensional? Why would it have just ''three'' dimensions, and not four, or five, or the ''n'' dimensions that Schläfli mapped? What is the nature of the boundary which confines us to just three dimensions? We know that in Euclidean geometry the boundary between three and four dimensions is itself a spherical three dimensional space, so we should suspect that we are materially confined within such a curved boundary surface. Light need not be confined with us within our three dimensional boundary space. We would look directly through four dimensional space in our natural way, by receiving light signals that travelled through it to us on straight lines. In that case the reason we do not observe a fourth spatial dimension in our vicinity is that there are no nearby objects in it, just off our hyperplane in the wild. The nearest four-dimensional object we can see with our eyes is our sun, which lies equatorially in our own hyperplane, though it bulges out of it above and below. But when we look up at the heavens, every pinprick of light we observe is itself a four-dimensional object off our hyperplane, and they are distributed all around us in four-dimensional space through which we gaze. We are four-dimensionally sighted creatures, even though our bodies are three-dimensional objects, thin as an atom in the fourth dimension. But that should not perplex us: we can see into three dimensional space even though our retinas are two dimensional objects, thin as a photoreceptor cell. Our unconscious provincial concept is that there is nothing else outside our three dimensional world: no boundary, because there is nothing else to separate us from. But Schläfli discovered something else: all the astonishing regular objects that exist in higher dimensions, which vastly extend our notions of the beauty and mystery of space itself, and the intrinsic spatial symmetries of our universe which geometry reveals. Space is more commodious than we thought it was, and permits previously unimagined objects and motions. So our provincial conception of our place in it now has the same kind of status as our idea that the sun rises in the east and passes overhead: it is mere appearance, not a true model and no longer a proper explanation. An inertial boundary is an explanation, be it ever so thin. And would a boundary of ''no'' thickness, a mere abstraction with no physical power to separate, be a more suitable explanation? We must look for a physically powerful explanation in the geometry of space itself, which general relativity properly associates with the gravitational or inertial force. <blockquote>The number of dimensions possessed by a figure is the number of straight lines each perpendicular to all the others which can be drawn on it. Thus a point has no dimensions, a straight line one, a plane surface two, and a solid three .... In space as we now know it only three lines can be imagined perpendicular to each other. A fourth line, perpendicular to all the other three would be quite invisible and unimaginable to us. We ourselves and all the material things around us probably possess a fourth dimension, of which we are quite unaware. If not, from a four-dimensional point of view we are mere geometrical abstractions, like geometrical surfaces, lines, and points are to us. But this thickness in the fourth dimension must be exceedingly minute, if it exists at all. That is, we could only draw an exceedingly small line perpendicular to our three perpendicular lines, length, breadth and thickness, so small that no microscope could ever perceive it. We can find out something about the conditions of the fourth and higher dimensions if they exist, without being certain that they do exist, by a process which I have termed "Dimensional Analogy."<ref>{{Citation|title=Dimensional Analogy|last=Coxeter|first=Donald|date=February 1923|publisher=Coxeter Fonds, University of Toronto Archives|authorlink=W:Harold Scott MacDonald Coxeter|series=|postscript=|work=}}</ref></blockquote> I believe, but I cannot prove, that we live in real space, which is Schläfli's Euclidean space of ''n'' analogous dimensions. As Grassmann showed first, space cannot be limited to any finite number of dimensions. There will always be higher dimensions to discover, first in imagination and then to explore physically, each an astonishing new enlightenment.<ref>{{Cite book|first=T.S.|last=Eliot|title=Little Gidding|volume=Four Quartets|year=1943}}<blockquote> :We shall not cease from exploration :And the end of all our exploring :Will be to arrive where we started :And know the place for the first time. :Through the unknown, remembered gate :When the last of earth left to discover :Is that which was the beginning; :At the source of the longest river :The voice of the hidden waterfall :And the children in the apple-tree :Not known, because not looked for :But heard, half-heard, in the stillness :Between two waves of the sea. </blockquote></ref> Schläfli discovered every regular convex polytope that exists in any dimension, but that was only the beginning of the story of dimensional analogy, not its end or even the end of its beginning. That project is forever beginning anew. Coxeter discovered that Schläfli's Euclidean space is an expression of intrinsic symmetries, as Noether discovered all of physics is. Kappraff and Adamson discovered that even the sequences of humble regular polygons have fractal complexity. Symmetry itself is chaotic, always reachable but forever beyond our complete grasp. We are on a Wilderness Project, and just at its beginning, but already we observe a Euclidean space of four or more orthogonal spatial dimensions in which all objects with mass move ceaselessly at the constant velocity <math>c</math>, the universal rate at which everything moves, quantum events occur, and each of our proper times evolves. I believe these facts explain the experimentally verified theories of relativity and quantum mechanics, by revealing their unified polycentric geometry, the same way the facts about Copernicus's heliocentric solar system explained the observed motions of the planets, by revealing the geometry of gravity. But others will have to do the math, work out the physics, and perform experiments to prove or disprove all of this, because I don't have the mathematics; entirely unlike Coxeter and Einstein, I am illiterate in those languages. <blockquote> ::::::BEECH :Where my imaginary line :Bends square in woods, an iron spine :And pile of real rocks have been founded. :And off this corner in the wild, :Where these are driven in and piled, :One tree, by being deeply wounded, :Has been impressed as Witness Tree :And made commit to memory :My proof of being not unbounded. :Thus truth's established and borne out, :Though circumstanced with dark and doubt— :Though by a world of doubt surrounded. :::::::—''The Moodie Forester''<ref>{{Cite book|title=A Witness Tree|last=Frost|first=Robert|year=1942|series=The Poetry of Robert Frost|publisher=Holt, Rinehart and Winston|edition=1969|}}</ref> </blockquote> == Appendix: Sequence of regular 4-polytopes == {{Regular convex 4-polytopes|wiki=W:|columns=7}} == ... == {{Efn|In a ''[[W:William Kingdon Clifford|Clifford]] displacement'', also known as an [[W:Rotations in 4-dimensional Euclidean space#Isoclinic rotations|isoclinic rotation]], all the Clifford parallel{{Efn|name=Clifford parallels}} invariant planes are displaced in four orthogonal directions (two completely orthogonal planes) at once: they are rotated by the same angle, and at the same time they are tilted ''sideways'' by that same angle. A [[W:Rotations in 4-dimensional Euclidean space#Isoclinic rotations|Clifford displacement]] is [[W:8-cell#Radial equilateral symmetry|4-dimensionally diagonal]].{{Efn|name=isoclinic 4-dimensional diagonal}} Every plane that is Clifford parallel to one of the completely orthogonal planes (including in this case an entire Clifford parallel bundle of 4 hexagons, but not all 16 hexagons) is invariant under the isoclinic rotation: all the points in the plane rotate in circles but remain in the plane, even as the whole plane tilts sideways. All 16 hexagons rotate by the same angle (though only 4 of them do so invariantly). All 16 hexagons are rotated by 60 degrees, and also displaced sideways by 60 degrees to a Clifford parallel hexagon. All of the other central polygons (e.g. squares) are also displaced to a Clifford parallel polygon 60 degrees away.|name=Clifford displacement}} {{Efn|It is not difficult to visualize four hexagonal planes intersecting at 60 degrees to each other, even in three dimensions. Four hexagonal central planes intersect at 60 degrees in the [[W:cuboctahedron|cuboctahedron]]. Four of the 24-cell's 16 hexagonal central planes (lying in the same 3-dimensional hyperplane) intersect at each of the 24-cell's vertices exactly the way they do at the center of a cuboctahedron. But the ''edges'' around the vertex do not meet as the radii do at the center of a cuboctahedron; the 24-cell has 8 edges around each vertex, not 12, so its vertex figure is the cube, not the cuboctahedron. The 8 edges meet exactly the way 8 edges do at the apex of a canonical [[W:cubic pyramid]|cubic pyramid]].{{Efn|name=24-cell vertex figure}}|name=cuboctahedral hexagons}} {{Efn|name=radially equilateral}} {{Efn|Eight {{sqrt|1}} edges converge in curved 3-dimensional space from the corners of the 24-cell's cubical vertex figure{{Efn|The [[W:vertex figure|vertex figure]] is the facet which is made by truncating a vertex; canonically, at the mid-edges incident to the vertex. But one can make similar vertex figures of different radii by truncating at any point along those edges, up to and including truncating at the adjacent vertices to make a ''full size'' vertex figure. Stillwell defines the vertex figure as "the convex hull of the neighbouring vertices of a given vertex".{{Sfn|Stillwell|2001|p=17}} That is what serves the illustrative purpose here.|name=full size vertex figure}} and meet at its center (the vertex), where they form 4 straight lines which cross there. The 8 vertices of the cube are the eight nearest other vertices of the 24-cell. The straight lines are geodesics: two {{sqrt|1}}-length segments of an apparently straight line (in the 3-space of the 24-cell's curved surface) that is bent in the 4th dimension into a great circle hexagon (in 4-space). Imagined from inside this curved 3-space, the bends in the hexagons are invisible. From outside (if we could view the 24-cell in 4-space), the straight lines would be seen to bend in the 4th dimension at the cube centers, because the center is displaced outward in the 4th dimension, out of the hyperplane defined by the cube's vertices. Thus the vertex cube is actually a [[W:cubic pyramid|cubic pyramid]]. Unlike a cube, it seems to be radially equilateral (like the tesseract and the 24-cell itself): its "radius" equals its edge length.{{Efn|The vertex cubic pyramid is not actually radially equilateral,{{Efn|name=radially equilateral}} because the edges radiating from its apex are not actually its radii: the apex of the [[W:cubic pyramid|cubic pyramid]] is not actually its center, just one of its vertices.}}|name=24-cell vertex figure}} {{Efn|The hexagons are inclined (tilted) at 60 degrees with respect to the unit radius coordinate system's orthogonal planes. Each hexagonal plane contains only ''one'' of the 4 coordinate system axes.{{Efn|Each great hexagon of the 24-cell contains one axis (one pair of antipodal vertices) belonging to each of the three inscribed 16-cells. The 24-cell contains three disjoint inscribed 16-cells, rotated 60° isoclinically{{Efn|name=isoclinic 4-dimensional diagonal}} with respect to each other (so their corresponding vertices are 120° {{=}} {{radic|3}} apart). A [[16-cell#Coordinates|16-cell is an orthonormal ''basis'']] for a 4-dimensional coordinate system, because its 8 vertices define the four orthogonal axes. In any choice of a vertex-up coordinate system (such as the unit radius coordinates used in this article), one of the three inscribed 16-cells is the basis for the coordinate system, and each hexagon has only ''one'' axis which is a coordinate system axis.|name=three basis 16-cells}} The hexagon consists of 3 pairs of opposite vertices (three 24-cell diameters): one opposite pair of ''integer'' coordinate vertices (one of the four coordinate axes), and two opposite pairs of ''half-integer'' coordinate vertices (not coordinate axes). For example: {{indent|17}}({{spaces|2}}0,{{spaces|2}}0,{{spaces|2}}1,{{spaces|2}}0) {{indent|5}}({{spaces|2}}{{sfrac|1|2}},–{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},–{{sfrac|1|2}}){{spaces|3}}({{spaces|2}}{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}}) {{indent|5}}(–{{sfrac|1|2}},–{{sfrac|1|2}},–{{sfrac|1|2}},–{{sfrac|1|2}}){{spaces|3}}(–{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},–{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}}) {{indent|17}}({{spaces|2}}0,{{spaces|2}}0,–1,{{spaces|2}}0)<br> is a hexagon on the ''y'' axis. Unlike the {{sqrt|2}} squares, the hexagons are actually made of 24-cell edges, so they are visible features of the 24-cell.|name=non-orthogonal hexagons|group=}} {{Efn|Visualize the three [[16-cell]]s inscribed in the 24-cell (left, right, and middle), and the rotation which takes them to each other. [[24-cell#Reciprocal constructions from 8-cell and 16-cell|The vertices of the middle 16-cell lie on the (w, x, y, z) coordinate axes]];{{Efn|name=six orthogonal planes of the Cartesian basis}} the other two are rotated 60° [[W:Rotations in 4-dimensional Euclidean space#Isoclinic rotations|isoclinically]] to its left and its right. The 24-vertex 24-cell is a compound of three 16-cells, whose three sets of 8 vertices are distributed around the 24-cell symmetrically; each vertex is surrounded by 8 others (in the 3-dimensional space of the 4-dimensional 24-cell's ''surface''), the way the vertices of a cube surround its center.{{Efn|name=24-cell vertex figure}} The 8 surrounding vertices (the cube corners) lie in other 16-cells: 4 in the other 16-cell to the left, and 4 in the other 16-cell to the right. They are the vertices of two tetrahedra inscribed in the cube, one belonging (as a cell) to each 16-cell. If the 16-cell edges are {{radic|2}}, each vertex of the compound of three 16-cells is {{radic|1}} away from its 8 surrounding vertices in other 16-cells. Now visualize those {{radic|1}} distances as the edges of the 24-cell (while continuing to visualize the disjoint 16-cells). The {{radic|1}} edges form great hexagons of 6 vertices which run around the 24-cell in a central plane. ''Four'' hexagons cross at each vertex (and its antipodal vertex), inclined at 60° to each other.{{Efn|name=cuboctahedral hexagons}} The [[24-cell#Hexagons|hexagons]] are not perpendicular to each other, or to the 16-cells' perpendicular [[24-cell#Squares|square central planes]].{{Efn|name=non-orthogonal hexagons}} The left and right 16-cells form a tesseract.{{Efn|Each pair of the three 16-cells inscribed in the 24-cell forms a 4-dimensional [[W:tesseract|hypercube (a tesseract or 8-cell)]], in [[24-cell#Relationships among interior polytopes|dimensional analogy]] to the way two tetrahedra form a cube: the two 8-vertex 16-cells are inscribed in the 16-vertex tesseract, occupying its alternate vertices. The third 16-cell does not lie within the tesseract; its 8 vertices protrude from the sides of the tesseract, forming a cubic pyramid on each of the tesseract's cubic cells. The three pairs of 16-cells form three tesseracts.{{Efn|name=three 8-cells}} The tesseracts share vertices, but the 16-cells are completely disjoint.{{Efn|name=completely disjoint}}|name=three 16-cells form three tesseracts}} Two 16-cells have vertex-pairs which are one {{radic|1}} edge (one hexagon edge) apart. But a [[24-cell#Simple rotations|''simple'' rotation]] of 60° will not take one whole 16-cell to another 16-cell, because their vertices are 60° apart in different directions, and a simple rotation has only one hexagonal plane of rotation. One 16-cell ''can'' be taken to another 16-cell by a 60° [[24-cell#Isoclinic rotations|''isoclinic'' rotation]], because an isoclinic rotation is [[3-sphere]] symmetric: four [[24-cell#Clifford parallel polytopes|Clifford parallel hexagonal planes]] rotate together, but in four different rotational directions,{{Efn|name=Clifford displacement}} taking each 16-cell to another 16-cell. But since an isoclinic 60° rotation is a ''diagonal'' rotation by 60° in ''two'' completely orthogonal directions at once,{{Efn|name=isoclinic geodesic}} the corresponding vertices of the 16-cell and the 16-cell it is taken to are 120° apart: ''two'' {{radic|1}} hexagon edges (or one {{radic|3}} hexagon chord) apart, not one {{radic|1}} edge (60°) apart as in a simple rotation.{{Efn|name=isoclinic 4-dimensional diagonal}} By the [[W:chiral|chiral]] diagonal nature of isoclinic rotations, the 16-cell ''cannot'' reach the adjacent 16-cell by rotating toward it; it can only reach the 16-cell ''beyond'' it. But of course, the 16-cell beyond the 16-cell to its right is the 16-cell to its left. So a 60° isoclinic rotation ''will'' take every 16-cell to another 16-cell: a 60° ''right'' isoclinic rotation will take the middle 16-cell to the 16-cell we may have originally visualized as the ''left'' 16-cell, and a 60° ''left'' isoclinic rotation will take the middle 16-cell to the 16-cell we visualized as the ''right'' 16-cell. (If so, that was our error in visualization; the 16-cell to the "left" is in fact the one reached by the left isoclinic rotation, as that is the only sense in which the two 16-cells are left or right of each other.)|name=three isoclinic 16-cells}} {{Efn|In a double rotation each vertex can be said to move along two completely orthogonal great circles at the same time, but it does not stay within the central plane of either of those original great circles; rather, it moves along a helical geodesic that traverses diagonally between great circles. The two completely orthogonal planes of rotation are said to be ''invariant'' because the points in each stay in the plane ''as the plane moves'', tilting sideways by the same angle that the other plane rotates.|name=helical geodesic}} {{Efn|A point under isoclinic rotation traverses the diagonal{{Efn|name=isoclinic 4-dimensional diagonal}} straight line of a single '''isoclinic geodesic''', reaching its destination directly, instead of the bent line of two successive '''simple geodesics'''. A '''[[W:geodesic|geodesic]]''' is the ''shortest path'' through a space (intuitively, a string pulled taught between two points). Simple geodesics are great circles lying in a central plane (the only kind of geodesics that occur in 3-space on the 2-sphere). Isoclinic geodesics are different: they do ''not'' lie in a single plane; they are 4-dimensional [[W:helix|spirals]] rather than simple 2-dimensional circles.{{Efn|name=helical geodesic}} But they are not like 3-dimensional [[W:screw threads|screw threads]] either, because they form a closed loop like any circle (after ''two'' revolutions). Isoclinic geodesics are ''4-dimensional great circles'', and they are just as circular as 2-dimensional circles: in fact, twice as circular, because they curve in a circle in two completely orthogonal directions at once.{{Efn|Isoclinic geodesics are ''4-dimensional great circles'' in the sense that they are 1-dimensional geodesic ''lines'' that curve in 4-space in two completely orthogonal planes at once. They should not be confused with ''great 2-spheres'',{{Sfn|Stillwell|2001|p=24}} which are the 4-dimensional analogues of 2-dimensional great circles (great 1-spheres).}} These '''isoclines''' are geodesic 1-dimensional lines embedded in a 4-dimensional space. On the 3-sphere{{Efn|All isoclines are geodesics, and isoclines on the 3-sphere are circles (curving equally in each dimension), but not all isoclines on 3-manifolds in 4-space are circles.}} they always occur in [[W:chiral|chiral]] pairs and form a pair of [[W:Villarceau circle|Villarceau circle]]s on the [[W:Clifford torus|Clifford torus]],{{Efn|Isoclines on the 3-sphere occur in non-intersecting chiral pairs. A left and a right isocline form a [[W:Hopf link|Hopf link]] called the {1,1} torus knot{{Sfn|Dorst|2019|loc=§1. Villarceau Circles|p=44|ps=; "In mathematics, the path that the (1, 1) knot on the torus traces is also known as a [[W:Villarceau circle|Villarceau circle]]. Villarceau circles are usually introduced as two intersecting circles that are the cross-section of a torus by a well-chosen plane cutting it. Picking one such circle and rotating it around the torus axis, the resulting family of circles can be used to rule the torus. By nesting tori smartly, the collection of all such circles then form a [[W:Hopf fibration|Hopf fibration]].... we prefer to consider the Villarceau circle as the (1, 1) torus knot [a [[W:Hopf link|Hopf link]]] rather than as a planar cut [two intersecting circles]."}} in which ''each'' of the two linked circles traverses all four dimensions.}} the paths of the left and the right [[W:Rotations in 4-dimensional Euclidean space#Double rotations|isoclinic rotation]]. They are [[W:Helix|helices]] bent into a [[W:Möbius strip|Möbius loop]] in the fourth dimension, taking a diagonal [[W:Winding number|winding route]] twice around the 3-sphere through the non-adjacent vertices of a 4-polytope's [[W:Skew polygon#Regular skew polygons in four dimensions|skew polygon]].|name=isoclinic geodesic}} {{Efn|[[File:Hopf band wikipedia.png|thumb|150px|Two [[W:Clifford parallel|Clifford parallel]] great circles spanned by a twisted [[W:Annulus (mathematics)|annulus]].]][[W:Clifford parallel|Clifford parallel]]s are non-intersecting curved lines that are parallel in the sense that the perpendicular (shortest) distance between them is the same at each point. A double helix is an example of Clifford parallelism in ordinary 3-dimensional Euclidean space. In 4-space Clifford parallels occur as geodesic great circles on the [[W:3-sphere|3-sphere]].{{Sfn|Kim|Rote|2016|pp=8-10|loc=Relations to Clifford Parallelism}} Whereas in 3-dimensional space, any two geodesic great circles on the [[W:2-sphere|2-sphere]] will always intersect at two antipodal points, in 4-dimensional space not all great circles intersect. In 4-polytopes various discrete sets of Clifford parallel non-intersecting geodesic great circles can be found on the 3-sphere. They spiral around each other in [[W:Hopf fibration|Hopf fiber bundles]] which visit all the vertices just once. The simplest example is that six mutually orthogonal great circles can be drawn on the 3-sphere, as three pairs of completely orthogonal great circles, intersecting at 8 points defining a [[16-cell]]. Each completely orthogonal pair of circles is Clifford parallel. They cannot intersect at all, because they lie in planes which intersect at only one point: the center of the 16-cell. Because they are perpendicular and share a common center, the two circles are obviously not parallel and separate in the usual way of parallel circles in 3 dimensions; rather they are connected like adjacent links in a chain, each passing through the other without intersecting at any points, forming a [[W:Hopf link|Hopf link]]|name=Clifford parallels}} {{Efn|In the 24-cell each great square plane is completely orthogonal{{Efn|name=completely orthogonal planes}} to another great square plane, and each great hexagon plane is completely orthogonal to a plane which intersects only two vertices: a great [[W:digon|digon]] plane.|name=pairs of completely orthogonal planes}} {{Efn|In an [[24-cell#Isoclinic rotations|isoclinic rotation]], each point anywhere in the 4-polytope moves an equal distance in four orthogonal directions at once, on a [[W:8-cell#Radial equilateral symmetry|4-dimensional diagonal]]. The point is displaced a total [[W:Pythagorean distance]] equal to the square root of four times the square of that distance. For example, when the unit-radius 24-cell rotates isoclinically 60° in a hexagon invariant plane and 60° in its completely orthogonal invariant plane,{{Efn|name=pairs of completely orthogonal planes}} all vertices are displaced to a vertex two edge lengths away. Each vertex is displaced to another vertex {{radic|3}} (120°) away, moving {{radic|3/4}} in four orthogonal coordinate directions.|name=isoclinic 4-dimensional diagonal}} {{Efn|Each square plane is isoclinic (Clifford parallel) to five other square planes but completely orthogonal{{Efn|name=completely orthogonal planes}} to only one of them.{{Efn|name=Clifford parallel squares in the 16-cell and 24-cell}} Every pair of completely orthogonal planes has Clifford parallel great circles, but not all Clifford parallel great circles are orthogonal (e.g., none of the hexagonal geodesics in the 24-cell are mutually orthogonal).|name=only some Clifford parallels are orthogonal}} {{Efn|In the [[16-cell#Rotations|16-cell]] the 6 orthogonal great squares form 3 pairs of completely orthogonal great circles; each pair is Clifford parallel. In the 24-cell, the 3 inscribed 16-cells lie rotated 60 degrees isoclinically{{Efn|name=isoclinic 4-dimensional diagonal}} with respect to each other; consequently their corresponding vertices are 120 degrees apart on a hexagonal great circle. Pairing their vertices which are 90 degrees apart reveals corresponding square great circles which are Clifford parallel. Each of the 18 square great circles is Clifford parallel not only to one other square great circle in the same 16-cell (the completely orthogonal one), but also to two square great circles (which are completely orthogonal to each other) in each of the other two 16-cells. (Completely orthogonal great circles are Clifford parallel, but not all Clifford parallels are orthogonal.{{Efn|name=only some Clifford parallels are orthogonal}}) A 60 degree isoclinic rotation of the 24-cell in hexagonal invariant planes takes each square great circle to a Clifford parallel (but non-orthogonal) square great circle in a different 16-cell.|name=Clifford parallel squares in the 16-cell and 24-cell}} {{Efn|In 4 dimensional space we can construct 4 perpendicular axes and 6 perpendicular planes through a point. Without loss of generality, we may take these to be the axes and orthogonal central planes of a (w, x, y, z) Cartesian coordinate system. In 4 dimensions we have the same 3 orthogonal planes (xy, xz, yz) that we have in 3 dimensions, and also 3 others (wx, wy, wz). Each of the 6 orthogonal planes shares an axis with 4 of the others, and is ''completely orthogonal'' to just one of the others: the only one with which it does not share an axis. Thus there are 3 pairs of completely orthogonal planes: xy and wz intersect only at the origin; xz and wy intersect only at the origin; yz and wx intersect only at the origin.|name=six orthogonal planes of the Cartesian basis}} {{Efn|Two planes in 4-dimensional space can have four possible reciprocal positions: (1) they can coincide (be exactly the same plane); (2) they can be parallel (the only way they can fail to intersect at all); (3) they can intersect in a single line, as two non-parallel planes do in 3-dimensional space; or (4) '''they can intersect in a single point'''{{Efn|To visualize how two planes can intersect in a single point in a four dimensional space, consider the Euclidean space (w, x, y, z) and imagine that the w dimension represents time rather than a spatial dimension. The xy central plane (where w{{=}}0, z{{=}}0) shares no axis with the wz central plane (where x{{=}}0, y{{=}}0). The xy plane exists at only a single instant in time (w{{=}}0); the wz plane (and in particular the w axis) exists all the time. Thus their only moment and place of intersection is at the origin point (0,0,0,0).|name=how planes intersect at a single point}} (and they ''must'', if they are completely orthogonal).{{Efn|Two flat planes A and B of a Euclidean space of four dimensions are called ''completely orthogonal'' if and only if every line in A is orthogonal to every line in B. In that case the planes A and B intersect at a single point O, so that if a line in A intersects with a line in B, they intersect at O.{{Efn|name=six orthogonal planes of the Cartesian basis}}|name=completely orthogonal planes}}|name=how planes intersect}} {{Efn|Polytopes are '''completely disjoint''' if all their ''element sets'' are disjoint: they do not share any vertices, edges, faces or cells. They may still overlap in space, sharing 4-content, volume, area, or lineage.|name=completely disjoint}} {{Efn|If the [[W:Euclidean distance|Pythagorean distance]] between any two vertices is {{sqrt|1}}, their geodesic distance is 1; they may be two adjacent vertices (in the curved 3-space of the surface), or a vertex and the center (in 4-space). If their Pythagorean distance is {{sqrt|2}}, their geodesic distance is 2 (whether via 3-space or 4-space, because the path along the edges is the same straight line with one 90^o bend in it as the path through the center). If their Pythagorean distance is {{sqrt|3}}, their geodesic distance is still 2 (whether on a hexagonal great circle past one 60^o bend, or as a straight line with one 60^o bend in it through the center). Finally, if their Pythagorean distance is {{sqrt|4}}, their geodesic distance is still 2 in 4-space (straight through the center), but it reaches 3 in 3-space (by going halfway around a hexagonal great circle).|name=Geodesic distance}} {{Efn|Two angles are required to fix the relative positions of two planes in 4-space.{{Sfn|Kim|Rote|2016|p=7|loc=§6 Angles between two Planes in 4-Space|ps=; "In four (and higher) dimensions, we need two angles to fix the relative position between two planes. (More generally, ''k'' angles are defined between ''k''-dimensional subspaces.)"}} Since all planes in the same [[W:hyperplane|hyperplane]] are 0 degrees apart in one of the two angles, only one angle is required in 3-space. Great hexagons in different hyperplanes are 60 degrees apart in ''both'' angles. Great squares in different hyperplanes are 90 degrees apart in ''both'' angles (completely orthogonal){{Efn|name=completely orthogonal planes}} or 60 degrees apart in ''both'' angles.{{Efn||name=Clifford parallel squares in the 16-cell and 24-cell}} Planes which are separated by two equal angles are called ''isoclinic''. Planes which are isoclinic have [[W:Clifford parallel|Clifford parallel]] great circles.{{Efn|name=Clifford parallels}} A great square and a great hexagon in different hyperplanes are neither isoclinic nor Clifford parallel; they are separated by a 90 degree angle ''and'' a 60 degree angle.|name=two angles between central planes}} {{Efn|The 24-cell contains 3 distinct 8-cells (tesseracts), rotated 60° isoclinically with respect to each other. The corresponding vertices of two 8-cells are {{radic|3}} (120°) apart. Each 8-cell contains 8 cubical cells, and each cube contains four {{radic|3}} chords (its long diagonals). The 8-cells are not completely disjoint{{Efn|name=completely disjoint}} (they share vertices), but each cube and each {{radic|3}} chord belongs to just one 8-cell. The {{radic|3}} chords joining the corresponding vertices of two 8-cells belong to the third 8-cell.|name=three 8-cells}} {{Efn|Departing from any vertex V₀ in the original great hexagon plane of isoclinic rotation P₀, the first vertex reached V₁ is 120 degrees away along a {{radic|3}} chord lying in a different hexagonal plane P₁. P₁ is inclined to P₀ at a 60° angle.{{Efn|P₀ and P₁ lie in the same hyperplane (the same central cuboctahedron) so their other angle of separation is 0.{{Efn|name=two angles between central planes}}}} The second vertex reached V₂ is 120 degrees beyond V₁ along a second {{radic|3}} chord lying in another hexagonal plane P₂ that is Clifford parallel to P₀.{{Efn|P₀ and P₂ are 60° apart in ''both'' angles of separation.{{Efn|name=two angles between central planes}} Clifford parallel planes are isoclinic (which means they are separated by two equal angles), and their corresponding vertices are all the same distance apart. Although V₀ and V₂ are ''two'' {{radic|3}} chords apart{{Efn|V₀ and V₂ are two {{radic|3}} chords apart on the geodesic path of this rotational isocline, but that is not the shortest geodesic path between them. In the 24-cell, it is impossible for two vertices to be more distant than ''one'' {{radic|3}} chord, unless they are antipodal vertices {{radic|4}} apart.{{Efn|name=Geodesic distance}} V₀ and V₂ are ''one'' {{radic|3}} chord apart on some other isocline. More generally, isoclines are geodesics because the distance between their ''adjacent'' vertices is the shortest distance between those two vertices, but a path between two vertices along a geodesic is not always the shortest distance between them (even on ordinary great circle geodesics).}}, P₀ and P₂ are just one {{radic|1}} edge apart (at every pair of ''nearest'' vertices).}} (Notice that V₁ lies in both intersecting planes P₁ and P₂, as V₀ lies in both P₀ and P₁. But P₀ and P₂ have ''no'' vertices in common; they do not intersect.) The third vertex reached V₃ is 120 degrees beyond V₂ along a third {{radic|3}} chord lying in another hexagonal plane P₃ that is Clifford parallel to P₁. The three {{radic|3}} chords lie in different 8-cells.{{Efn|name=three 8-cells}} V₀ to V₃ is a 360° isoclinic rotation.|name=360 degree geodesic path visiting 3 hexagonal planes}} {{Sfn|Mamone, Pileio & Levitt|2010|loc=§4.5 Regular Convex 4-Polytopes|pp=1438-1439|ps=; the 24-cell has 1152 symmetry operations (rotations and reflections) as enumerated in Table 2, symmetry group 𝐹₄.}} ==Notes== {{Regular convex 4-polytopes Notelist|wiki=W:}} ==Citations== {{Regular convex 4-polytopes Reflist|wiki=W:}} ==References== {{Refbegin}} * {{Cite book|title=A Week on the Concord and Merrimack Rivers|last=Thoreau|first=Henry David|author-link=W:Thoreau|publisher=James Munroe and Company|year=1849|isbn=|location=Boston|ref={{SfnRef|Thoreau|1849}}}} * {{Cite journal|title=Theoretical Evidence for Principles of Special Relativity Based on Isotropic and Uniform Four-Dimensional Space|first=Takuya|last=Yamashita|date=25 May 2023|doi= 10.20944/preprints202305.1785.v1|journal=Preprints|volume=2023|issue=2023051785|url=https://doi.org/10.20944/preprints202305.1785.v1}} * {{Cite_arXiv | arxiv=2512.02903v2 | date=2 January 2026 | title=Symmetry transformation group arising from the Laplace–Runge–Lenz vector | first1=Stephen C. | last1=Anco | first2=Mahdieh Gol Bashmani | last2=Moghadam | class=math-ph}} === [[Polyscheme|Polyschemes]] === {{Regular convex 4-polytopes Refs|wiki=W:}} {{Refend}} ezu4ge3du737j1bzfuo2q8ya1modtw5 2835261 2835260 2026-10-01T03:00:01Z Dc.samizdat 2856930 2835261 wikitext text/x-wiki {{align|center|David Brooks Christie}} {{align|center|dc@samizdat.org}} {{align|center|Draft in progress}} {{align|center|June 2023 - September 2026}} <blockquote>'''Abstract:''' The physical universe is properly visualized as real Euclidean space <math>\mathbb{R}^4</math> of four orthogonal spatial dimensions. Space itself has a fourth perpendicular dimension, of which we are unaware in ordinary life. Atoms are 4-polytopes, small round 4-dimensional objects, and stars are 4-balls of atomic plasma, large round 4-dimensional objects. We ourselves and our planet are only 3-dimensional objects, but nonetheless we can see in four dimensions of space. We have been unaware that when we look up at night we see stars and galaxies, themselves large 4-dimensional objects, distributed all around us in 4-dimensional Euclidean space, and moving through it, like us, at the constant velocity <math>c</math>. Light from them reaches us directly, on straight lines through 4-space. This view of the observed universe is compatible with special and general relativity, and with quantum mechanics. It furnishes those theories with an explanatory geometric model.</blockquote> == Summary == We observe that: * Physical space has four perpendicular dimensions, not just three. * Atoms are [[W:4-polytope|4-polytopes]]. * The sun is a [[W:4-ball|4-ball]] that is round in four dimensions. * Everything of intermediate size between an atom and a star, including us and our planet, lies in a 3-dimensional manifold of ordinary space. * Our entire 3-space manifold is moving through Euclidean 4-space at the speed of light, in a direction perpendicular to its three interior dimensions. * Special relativity describes the linear motion of objects and light signals in four-dimensional Euclidean space. == A theory of the Euclidean cosmos == The physical universe is properly visualized as [[w:Four-dimensional_space|real Euclidean space <math>\mathbb{R}^4</math>]] of four orthogonal spatial dimensions. Space itself has a fourth perpendicular dimension, of which we are unaware in ordinary life. Atoms are [[w:4-polytope|4-polytopes]], small round 4-dimensional objects, and stars are [[W:4-ball|4-balls]] of atomic plasma, large round 4-dimensional objects. Objects intermediate in size between atoms and stars, including molecules, people, and planets, are so flat as to be essentially 3-dimensional, having only the thickness of an atom in the orthogonal fourth dimension. All objects with mass move inertially through Euclidean 4-space at constant velocity <math>c</math> as long as they exist, and acceleration only varies their direction. Objects moving in the same direction are in the same inertial reference frame. Their direction of motion through 4-space at velocity <math>c</math> is their proper time dimension, simply because their direction and velocity of motion through time is the same as their direction and velocity of motion through space. A typical galaxy such as ours occupies a 4-ball of mostly empty space, with stars and other objects distributed non-uniformly within it. The galaxy's orbital center may be nothing: a smaller 4-ball of empty space they surround. The stars in our spiral galaxy appear from our accustomed point of view to occupy a disk-like region of 3-dimensional space, with a denser ball-like center, but they are not so confined: they are distributed within a region of 4-dimensional space. The disk and ball have thickness not only in the third dimension, but in the fourth spatial dimension as well. Light from stars and galaxies reaches us on straight lines through Euclidean 4-space, so from our viewpoint, in what we have always imagined to be a 3-space universe, we look into the surrounding 4-space. Although we are physically confined within a 3-dimensional hyperplane by the inertia of our motion through 4-space at constant velocity <math>c</math>, light signals are not so confined, so we observe all the cosmological objects surrounding us, both in and above or below our hyperplane, without perceiving their separation in our fourth orthogonal dimension, the direction of our motion. We may perceive a galaxy as elliptical when it is actually spherical, because that is how its image projects from its 4-ball shape into a 3-ball region in our hyperplane, where we measure it with our 3-dimensional bodies. More generally, orbits are circular in 4-space, but elliptical in the 3-space of their elliptic hyperplane. The galaxy as a whole, or more properly its orbital barycenter, is translating through 4-space at velocity <math>c</math>, in a distinct direction orthogonal to all three dimensions of our ordinary proper 3-space. Stars within the galaxy are translating with it at the same velocity <math>c</math> in the same direction, but on spiral trajectories as they pursue their various orbits within the galaxy. The galaxy as a whole occupies a 4-ball within its proper inertial reference frame (that is, in the moving frame of reference in which the galaxy considers itself to be a stationary rotating 4-ball). Over time, the galaxy 4-ball occupies a 4-dimensional cylinder and progresses along the cylinder's axis at velocity <math>c</math>. In this more universal inertial reference frame, the stars in the galaxy follow helical geodesic paths through the 4-cylinder; their trajectories are screw-translations through 4-space, the compound of a simple rotation and a completely orthogonal linear translation. The gravitational force and the inertial tendency to follow a geodesic are the same phenomenon, by the equivalence principle. That said, they can be distinguished, and the galaxy is held together primarily by gravity as inertia, not by gravity as attraction to a central mass toward which objects fall in orbit. There is not enough mass in the galaxy to hold it together by attraction, there is just enough to bend the stars' trajectories toward each other, in helical orbits around a barycentric axis of motion. It is the tremendous inertial force of stars in translational motion at velocity <math>c</math> that holds the cylinder of motion together, not some invisible dark matter. The observed universe as a whole appears to be a [[W:3-sphere|3-sphere]] expanding radially from a central origin point at velocity <math>c</math>, the invariant velocity of mass-carrying objects through 4-space, also the propagation speed of light relative to any moving 3-space manifold, as measured by all observers. A 3-sphere is a hypersphere in Euclidean 4-space, but the enclosing surface of a 3-sphere is a curved, finite 3-space, dimensionally analogous to the surface of the earth which is a curved, finite 2-space. This 3-sphere could be the domain of our visible cosmos, but of course we do not know for certain that all the cosmological objects we observe lie near the surface of our expanding 3-sphere, since it is only our assumption that they must all have originated in the same big bang long ago. Possibly some of the more distant objects we observe did not, and lie elsewhere, outside our big-bang's 3-sphere of outflying matter or even inside its 3-sphere, below its surface. We cannot assume that all objects in the 4-space universe lie near the surface of the same expanding 3-sphere. For all observers, the conjectured big-bang of their origin corresponds not only to a now-distant point in their proper time past, it also corresponds to a distinct now-distant point in 4-dimensional space: the same point in the same Euclidean 4-space for all observers with the same origin. Our big bang had a distinct origin point in real space as well as in real time. More generally, time and Euclidean 4-space can be measured independently, just as time and Euclidean 3-space were measured classically, without the necessity to combine them as spacetime. The same inertial force which holds the galactic cylinder of motion together also confines us physically to an exceedingly thin three-dimensional surface manifold moving through 4-space at velocity <math>c</math>. All objects in our solar system except the sun itself lie within this thinest three-dimensional manifold, and have only the thickness of an atom in their direction-of-motion fourth dimension. That is why we are 3-dimensional objects ourselves, and why we cannot construct more than three perpendiculars through a single point in our local 3-dimensional space. A spherical region of 4-space is called a [[W:4-ball|4-ball]]. The enclosing surface of a 4-ball of any size is a finite, curved (non-Euclidean) 3-dimensional space called a [[w:3-sphere|3-sphere]]. Our entire big-bang-origin universe appears to be the largest 3-sphere we observe, but each of the cosmological objects within it (including our galaxy and our sun) is contained in a smaller 3-sphere shell of its own, lying (we assume) on the largest 3-sphere embedded in its surface, like a soap bubble on the surface of a larger soap bubble. All the 3-dimensional surfaces are expanding, as the largest 3-sphere inflates at radial velocity <math>c</math>. We ourselves live within such an expanding 3-dimensional surface, in an infinitesimally curved 3-manifold surface embedded in Euclidean 4-space. That surface is the ordinary 3-dimensional space we experience, and it contains the earth, all the planets and the 3-dimensional space between them. Our solar system is only a small patch on the surface of a dimensionally rounder space, although that surface is not infinite. It is curved, and finite, analogous to the way the 2-dimensional surface of the earth -- once thought to be flat -- is curved and finite. Our solar system occupies a small patch on a filmy 4-dimensional soap-bubble of galactic size rounded by gravity, that is thicker-skinned than the diameter of an atom only in the interior of stars and supermassive objects. Our 3-manifold of ordinary space, as a surface within our moving 4-ball galaxy, is translating through 4-space at velocity <math>c</math> with the galaxy, in a distinct direction orthogonal to the manifold's three orthogonal dimensions of interior space. At every material point in the manifold (at every atom), the translation through 4-space is following a geometric law of motion discovered by Coxeter, that governs the propagation of individual objects through Euclidean space by the actions of their symmetry groups. The solar system's atoms of mass are 4-polytopes that are simultaneously rotating and translating, and as they advance together they define a moving 3-dimensional manifold by their own collective inertia, also called gravity, the property of matter's ceaseless propagation through 4-space at the constant velocity <math>c</math>, the universal rate of causality at which quantum events occur, all objects move, and the universe evolves. Any moving 3-dimensional manifold such as ours is an evolving surface boundary that is empty in most places, occupied by single atoms in comparatively fewer places, and occupied by bound complexes of multiple atoms (molecules) in still fewer places. In all these places it is no thicker than one atom in the dimension corresponding to its direction of translation, because molecules are 3-dimensional complexes of atoms that add no thickness to the manifold. Every object which we find occurring naturally in the solar system other than the sun itself, even the largest of 3-dimensional objects a planet, is a 3-dimensional smear of atoms no thicker than one atom in its fourth dimension, the direction of its linear translation through 4-space at velocity <math>c</math>. The moving surface manifold cannot be thicker than one atom at any point unless and until there is enough mass near that point for the force of gravity as attraction to overcome the force of gravity as inertia, allowing atoms to be "heaped up" into larger 4-dimensional objects that form a lump in its moving surface. We have little understanding of such 4-dimensional lumps thicker than one atom, since they occur naturally in our vicinity only in the interior of the sun. In fact the sun is the only such lump occurring naturally in our solar system. We refer to such 4-dimensional lumps of matter as atomic plasma, and have little experimental knowledge of their internal geometry or processes. We know that such a lump as the sun burns at its surface 3-sphere and emits radiation, and we know a good deal about those surface processes which are nuclear atomic processes, but we know almost nothing about its interior 4-ball, a dimensionally rounder enclosed space whose existence we did not suspect. Every moving surface boundary of matter in the observed universe is evolving in four dimensions at velocity <math>c</math>. The current location in 4-space of any of its material objects corresponds to the present moment in the proper time of that object's inertial reference frame. The object's direction of movement at velocity <math>c</math> corresponds to its proper time dimension, which is a spiral over time, not a Euclidean (straight-line) dimension, since its direction is changing in its orbit. Objects with mass of all sizes, from subatomic particles to the largest objects observed in the cosmos, are perpetually in inertial rotational motion in some orbit, and simultaneously in inertial translational motion propagating themselves through 4-space, in two completely orthogonal inertial motions each at the constant universal rate of transformation <math>c</math>. Every object with mass moves relative to universal 4-coordinate Euclidean space on its own distinct geodesic spiral, a screw displacement trajectory that is the compound of its two completely orthogonal inertial motions, a rotation and a translation. Objects without mass such as photons lie off such moving surface boundaries of matter from which they were emitted, and their motion is of a different nature. They are in translational motion at velocity <math>c</math> through all four dimensions concurrently, without any rotational component of motion, so they move through 4-space on straight lines at a compound velocity. The propagation speed of light measured on a straight line through Euclidean 4-space is <math>c\prime = 2c</math>, so we can see in four dimensions, even though we are physically confined to a 3-dimensional manifold that is moving at velocity <math>c</math>. For example, we can look across the center of the mostly-empty 4-ball containing our galaxy and see stars in the opposite sides of its concentric 3-sphere orbital surfaces. We have been unaware that when we look up at night we see stars and galaxies, themselves large 4-dimensional objects, distributed all around us in 4-dimensional Euclidean space, and moving through it, like us, at the constant velocity <math>c</math>. They move in the 4-space direction corresponding to their proper time, perpendicular to all three dimensions of their proper 3-space, and generally the farther they are from us the greater the divergence of their direction of motion from our direction of motion: the greater the relative motion between us and their Hubble redshift. Light from them reaches us directly, propagating on straight lines through 4-space at twice the velocity at which they, and we ourselves, are propagating through 4-space. This physical model of the observed universe is compatible with the theories of special and general relativity, and with the atomic theory of quantum mechanics. It explains those theories geometrically, as expressions of intrinsic symmetries in Euclidean space. == Symmetries == It is common to speak of nature as a web, and so it is, the great web of our physical experiences. Every web must have its root systems somewhere, and nature in this sense must be rooted in the symmetries which underlie physics and geometry, the [[W:Group (mathematics)|mathematics of groups]].{{Sfn|Conway, Burgiel & Goodman-Strauss|2008}} As I understand [[W:Noether's theorem|Noether's theorem]] (which is not mathematically), hers is the deepest meta-theory of nature yet, deeper than [[W:Theory of relativity|Einstein's relativity]] or [[W:Evolution|Darwin's evolution]] or [[W:Euclidean geometry|Euclid's geometry]]. It finds that all fundamental findings in physics are based on conservation laws which can be laid at the doors of distinct [[W:symmetry group |symmetry group]]s. Thus all fundamental systems in physics, as examples [[W:quantum chromodynamics|quantum chromodynamics]] (QCD) the theory of the strong force binding the atomic nucleus and [[W:quantum electrodynamics|quantum electrodynamics]] (QED) the theory of the electromagnetic force, each have a corresponding symmetry [[W:group theory|group theory]] of which they are an expression. [[W:Coxeter group|Coxeter's theory of symmetry groups]] generated by reflections did for geometry what Noether's theorem and Einstein's relativity did for physics. [[W:Coxeter|Coxeter]] showed that Euclidean geometry is based on conservation laws that correspond to distinct symmetry groups, and that their group actions express the principle of relativity. Here is Coxeter's formulation of the motions of objects (their congruent transformations) in an ''n''-dimensional Euclidean space, excerpted:{{Sfn|Coxeter|1973|pp=217-218|loc=§12.2 Congruent transformations}} <blockquote>Let <math>\mathrm{Q}</math> denote a rotation, <math>\mathrm{R}</math> a reflection, <math>\mathrm{T}</math> a translation, and let <math>\mathrm{Q}^q \mathrm{R}^r\mathrm{T}</math> denote a product of several such transformations, all commutative with one another. Then <math>\mathrm{RT}</math> is a glide-reflection (in two or three dimensions), <math>\mathrm{QR}</math> is a rotary-reflection, <math>\mathrm{QT}</math> is a screw-displacement, and <math>\mathrm{Q^2}</math> is a double rotation (in four dimensions).<br> Every orthogonal transformation is expressible as:<br> :<math>\mathrm{Q}^q \mathrm{R}^r</math><br> where <math>(2^q + r \le n)</math>, the number of dimensions.<br> Transformations involving a translation are also expressible as:<br> :<math>\mathrm{Q}^q \mathrm{R}^r \mathrm{T}</math><br> where <math>(2^q + r + 1 \le n)</math>.<br> For <math>(n = 4)</math> in particular, every displacement is either a double rotation <math>\mathrm{Q}^2</math>, or a screw-displacement <math>\mathrm{QT}</math> [where the rotation component <math>\mathrm{Q}</math> is a simple rotation, but the <math>\mathrm{QT}</math> is chiral like a <math>\mathrm{Q^2}</math>]. Every enantiomorphous transformation in 4-space (reversing chirality) is a <math>\mathrm{QRT}</math>.</blockquote> If we begin with this most elemental [[w:Kinematics|kinematics]] of Coxeter's, and also assume the [[W:Galilean relativity|Galilean principle of relativity]], every displacement in 4-space can be viewed as either a <math>\mathrm{Q^2}</math> or a <math>\mathrm{QT}</math>, because we can view any <math>\mathrm{QT}</math> as a <math>\mathrm{Q^2}</math> in a linearly moving (translating) reference frame. Therefore any transformation from one inertial reference frame to another is expressable as a <math>\mathrm{Q^2}</math>. By the same principle, we can view any <math>\mathrm{QT}</math> or <math>\mathrm{Q^2}</math> as an isoclinic (equi-angled) <math>\mathrm{Q^2}</math> by proper choice of reference frame.{{Efn|[[W:Arthur Cayley|Cayley]] showed that any rotation in 4-space can be decomposed into two isoclinic rotations, which intuitively we might see follows from the fact that any transformation from one inertial reference frame to another is expressable as a [[W:SO(4)|rotation in 4-dimensional Euclidean space]].|name=Cayley's rotation factorization into two isoclinic reference frame transformations}} Coxeter's relation is thus a mathematical statement of the principle of relativity, on group-theoretic grounds. It correctly captures the limits to [[W:General relativity|general relativity]], in that we can only exchange the translation (<math>\mathrm{T}</math>) for ''one'' of the two rotations (<math>\mathrm{Q}</math>). An observer in any inertial reference frame can always measure the presence, direction and velocity of ''one'' rotation (<math>\mathrm{Q}</math>) up to uncertainty, and can always distinguish the direction of their own proper time translation (<math>\mathrm{T}</math>). As I understand Coxeter theory (which is not mathematically), the symmetry groups underlying physics seem to have an expression in a [[W:Euclidean space|Euclidean space]] of four [[W:dimension|dimension]]s, that is, they are [[W:Euclidean geometry#Higher dimensions|four-dimensional Euclidean geometry]]. Therefore as I understand that geometry (which is entirely by synthetic methods rather than by Clifford's algebraic methods), the [[W:Atom|atom]] seems to have a distinct Euclidean geometry, such that atoms and their constituent particles are four-dimensional geometric objects (4-polytopes), and nature can be understood in terms of their [[W:group action|group actions]], including centrally their group <math>SO(4)</math> [[W:rotations in 4-dimensional Euclidean space|rotations in 4-dimensional Euclidean space]]. The distinct Coxeter symmetry groups have characteristic <math>SO(4)</math> rotational expressions as the [[W:Regular_4-polytope|regular 4-polytopes]]. Their discrete isoclinic rotations are distinguishing properties of fundamental objects in geometry, relativity and quantum mechanics. For example, atoms exhibit <math>SO(4)</math> symmetries of the discrete isoclinic (equi-angled) double rotations (<math>\mathrm{Q^2}</math>) of a set of regular 4-polytopes that is characteristic of their [[w:Atomic_number|atomic number]]. == Special relativity describes Euclidean 4-space == <blockquote>Our entire model of the universe is built on symmetries. Some, like isotropy (the laws are the same in all directions), homogeneity (same in all places), and time invariance (same at all times) seem natural enough. Even relativity, the Lorentz Invariance that allows everyone to observe a constant speed of light, has an elegance to it that makes it seem natural.<ref>{{Cite book|first=Dave|last=Goldberg|title=The Universe in the Rearview Mirror: How Hidden Symmetries Shape Reality|chapter=§10. Hidden Symmetries: Why some symmetries but not others?|year=2013|publisher=Dutton Penguin Group|isbn=978-0-525-95366-1|ref={{SfnRef|Goldberg|2013}}}}</ref></blockquote> Although the Minkowski spacetime of relativity is a non-Euclidean 4-dimensional space,{{Efn|Spacetime is a non-Euclidean (curved) 4-dimensional space because it consists of three orthogonal space dimensions and a time dimension. The time dimension is not orthogonal to the three spatial dimensions; the time coordinate has the opposite sign to the three space coordinates so spacetime is hyperbolic, not a flat Euclidean 4-space at all.}} it has been noticed that its 3-dimensional space component could be modeled as a [[W:3-sphere|3-sphere]] embedded in 4-dimensional Euclidean (flat) space. That is, we could imagine that the ordinary 3-dimensional space we perceive is the curved 3-dimensional surface of a 4-dimensional ball (since the surface of a 4-ball is a curved 3-dimensional space called a 3-sphere, just as the surface of a 3-ball like the earth is a curved 2-dimensional space called a 2-sphere). This was [[#Origins of the theory|imagined by Einstein]] himself in 1921, as a thought experiment in which he carefully described his fourth orthogonal spatial dimension as merely a mathematical abstraction. Subsequently it was noticed by others (not mainstream physicists) that if physical space were really embedded in Euclidean 4-dimensional space (with our 3-dimensional space embedded in 4-space as some non-Euclidean 3-manifold, not necessarily a 3-sphere), then the Lorentz transformation effects of special relativity (spatial forshortenings and time dilations and so forth) could all be explained by ordinary perspective geometry in 4-dimensional Euclidean space. Special relativity reduces to classical vector space geometry (based on the 4-dimensional version of the Pythagorean theorem), but if and only if every observer is moving through 4-space at a universal constant velocity <math>c</math>, in some 4-space direction.{{Sfn|Yamashita|2023}} This counter-intuitive alternative geometric model of relativity, which has usually been called [[W:Formulations of special relativity#Euclidean relativity|Euclidean relativity]], is motivated by the fact that in every kind of relativity, but originally in Einstein's special relativity, each observer moves on a vector through a Euclidean four-dimensional space consisting of their three proper spatial dimensions and their proper time dimension, and the Pythagorean vector-sum of their motion through this kind of proper 4-space is always <math>c</math>, as measured by all observers from any inertial reference frame.{{Efn|Each observer is stationary in space in their own proper reference frame, while they move at maximum velocity {{Math|c}} through their own proper time. Observed from another reference frame in relative motion, they appear foreshortened in space in their direction of motion, and their clocks appear to be slowed to less than the maximum velocity {{Math|c}}.}} This is the Lorentz invariant, that allows everyone to observe a constant speed of light, regardless of their motion relative to the light source.{{Efn| ...cite Lewis Epstein's elegant explanation of the Lorentz Invariance as observers moving at constant velocity {{Math|c}} through space and proper time.}} But no physicists have taken the leap of claiming that therefore, our universe is physically [[W:Euclidean geometry#Higher dimensions|this kind of Euclidean 4-space]], and that observers are actually moving through it at velocity <math>c</math>. In physics as it has been universally understood, observers are not supposed to be able to move at velocity <math>c</math>. Their motion takes place in 3-space and in universal coordinate time (in Minkowski spacetime), and the cosmos is considered to be a non-Euclidean 3-space, generally a closed (finite) expanding 3-space, but with only three spatial dimensions, not four. In the Euclidean relativity alternative view, however, every observer is always moving at velocity <math>c</math> through the universe, which is real Euclidean 4-dimensional space <math>\mathbb{R}^4</math>. The direction in which they are moving is called their proper time axis.{{Efn|Time in spacetime is universal coordinate time, but there is another kind of time in relativity, the proper time in each inertial reference frame. Your proper time is the time you experience, and every observer has his own proper time; proper time runs at different rates in different inertial reference frames. It runs slower (compared to universal coordinate time) in a gravitational field (according to general relativity), and observers in motion with respect to each other view each other's clocks as running slower than their own clocks (according to special relativity).}} Their movement in time is not just modelled as movement in an abstract fourth dimension (as it is in Minkowski spacetime), their movement in time is isomorphic to their movement through physical space in a distinct direction at velocity <math>c</math>. Two observers' directions of movement through space may be different (or not, if they happen to be going in the same direction). Your proper time dimension is whichever direction you are moving. The other three directions perpendicular to your proper time axis are the three dimensions of your ordinary proper space, which again, will be different directions for you than for other observers moving in a different direction. There are four orthogonal spatial dimensions which we all share, but we share the same orthogonal proper time axis and ordinary proper 3-space axes only if we are at rest with respect to each other, actually moving in the same direction at velocity <math>c</math>, in the same inertial reference frame. Your proper 4-space coordinate system is rotated with respect to another observer's proper 4-space coordinate system, precisely as your vectors (directions of motion) are rotated in Euclidean 4-space with respect to each other, but there are no metric distortions (no Lorentz transformations) between your proper Euclidean 4-space coordinate systems; you are both embedded in the same Euclidean 4-dimensional space <math>\mathbb{R}^4</math>. Lorentz transformations are required only to convert between your respective proper Minkowski spacetime coordinate systems. So in this novel alternate view of relativity, every mass in the universe must be perpetually in motion at velocity <math>c</math> through Euclidean 4-space, along with all the masses in its vicinity that are going in (nearly) the same direction. The entire solar system, for example, must be translating in the fourth dimension at the "speed of light" <math>c</math>, although we do not notice it, since we are all moving in that same direction together. Acceleration of an object varies its direction of motion through 4-space, but never its velocity, which is invariant for all objects with mass. Two objects which are in motion relative to each other are both actually in motion at the same velocity <math>c</math>, but in at least slightly different directions.{{Efn|The angular divergence between two observer's motion vectors is proportional to their relative velocity: the more they diverge, the greater their relative velocity, up to the maximum divergence possible in the space. In Euclidean relativity all observers are in motion at velocity {{Math|c}} relative to universal Cartesian 4-coordinate space, so the maximum relative velocity between two observers is {{Math|2c}} when they are moving in exactly opposite directions in 4-space. This is not a contradiction of special relativity, which limits the maximum relative velocity between two observers to {{Math|c}}, it is the same measurement in different units. Special relativity measures all velocities in Minkowski spacetime (in a non-Euclidean 3-space). Euclidean relativity measures all velocities in Euclidean 4-space.}} In Einstein's relativity, the invariant <math>c</math> is the speed of light through 3-space. In Euclidean relativity, the invariant <math>c</math> is the speed of matter through 4-space! The speed of light through 3-space is also perceived as <math>c</math> by all observers, because they are each living in a moving 3-manifold that is translating through 4-space at velocity <math>c</math>. Despite their extreme differences in viewpoint, Einstein's relativity and Euclidean relativity are equivalent theories in complete agreement with each other, by definition. The two theories make exactly the same special relativity predictions of how observers in different inertial reference frames will perceive each other's motions in time and space. It is beyond the scope of this present paper to show how they also agree on the predictions of general relativity, but it is important to understand that our formulation of Euclidean relativity requires our acceptance of the experimentally verified findings of special relativity, general relativity and quantum mechanics. Our model and the standard model both describe the same geometric relations of space and time based on the same evidence, but as embedded in two very different universal host spaces: Euclidean 4-space versus Minkowski spacetime. In some instances our model provides a geometric explanation for physical phenomena where the standard model has none, as yet. An example is the two models' differing explanations for the gravitational coherence of galaxies: either their inertial motion at velocity <math>c</math>, or their possession of experimentally undetected dark matter. A more central example is our use of Coxeter's kinematics to explain the laws of relativistic motion geometrically. More generally, our model is related to deep geometric properties of number elucidated by Coxeter and other geometers.{{Efn| ...cite Kappraff & Adamson's 2003 paper on The Relationship of the Cotangent Function to Special Relativity Theory, geometry and properties of number,{{Sfn|Kappraff & Adamson|2003|loc=Special Relativity Theory, Geometry and properties of number}} which shows how the Lorentz coefficient is a function of a deep geometric property of number{{Sfn|Kappraff & Adamson|2000|loc=A Fresh Look at Number}} discovered by Steinbach,{{Sfn|Steinbach|1997|loc=Golden Fields: A Case for the Heptagon}} by means of which the root formula of geometry in any Euclidean dimension, the Pythagorean theorem, may be derived solely in terms of the addition of polygon side lengths, without recourse to their products or squares. More generally, Steinbach found that in the relations among regular polytope chords, to add is to multiply; every chord is both the product (quotient) of a pair of chords and the sum (difference) of another pair of chords.}} Euclidean relativity is not even a fringe theory; no physicists or astronomers have adopted it. There are many good reasons why the revolutionary leap to a four orthogonal spatial dimensions viewpoint has not been taken, beginning with the universally observed fact that we can only construct three perpendiculars through a point in our immediate space, which appears to be resolutely 3-dimensional, not 4-dimensional. Euclidean relativity offers a nice geometric explanation of the reasons for the Lorentz transformations, but only at the cost of raising other mysteries, which have been difficult for its aficionados to explain. Another mystery is how light signals between observers in relative motion could "catch up" with the receiver moving on a diverging path through 4-space from the emitter. If both observers are already moving at <math>c</math> (on diverging paths), the propagation speed of light through 4-space between them would have to be greater than <math>c</math>. Euclidean relativity is a revolutionary theory indeed, in which <math>c</math> cannot possibly be the speed of light! We conclude that, for a theory of Euclidean 4-space to be physically viable (that is, for <math>\mathbb{R}^4</math> to be our real space and not merely an abstract mathematical space), the speed of light through Euclidean 4-space must be <math>c\prime = 2c</math>, with massless photons translating through 4-space at twice the speed of mass-carrying objects. Photons must translate the diagonal distance through 4-space along the long diameter of a unit 4-hypercube, in the same time that massive particles translate inertially along the edge (or the radius) of a unit 4-hypercube. This is conceivable in Euclidean 4-space (and in no other Euclidean space of any dimensionality) because the long diagonal of the unit 4-hypercube is the natural number <math>\sqrt{4}</math>. == An object's motion in space is the product of its discrete self-reflections == Coxeter theory describes all the possible motions of an object in space as local functions of the object's discrete geometry (its shape). Coxeter observed that in a Euclidean space of any number of dimensions, any displacement of a geometric object from one place to another, and any rotation of the object from one orientation to another, can be broken down into the product of a number of discrete self-reflections. Any action of a polytope that transforms its position and orientation in space may be measured as a distinct sequence of self-reflections of the object in its own surfaces. Any motion of the object whatsoever may be precisely described as the object propagating itself through space by a discrete sequence of local self-reflections. This is a purely kinematic description of motion which does not give any account of forces acting on the object that cause it to move. Coxeter found that both changes in position (translations) and changes in orientation (rotations) can be broken down into the simplest of all displacements (self-reflections). A translation occurs when an object self-reflects twice, in two distinct surfaces which are parallel to each other. A rotation also occurs when an object self-reflects twice, but in two distinct surfaces which intersect each other. When a object self-reflects once, it turns itself inside out (it reverses its chirality), but in translations and rotations it self-reflects twice, preserving its chirality. Coxeter's laws of kinematics are a geometric counterpart to Newton's algebraic laws of motion in three dimensional Euclidean space. They are helpful because they can be understood as geometric pictures, which may help us to visualize the relationships between translation and rotation in classic Newtonian physics problems, such as the Kepler problem of the motion of the planets.<ref>{{Cite book|last=Feynman|first=Richard|title=Feynman's Lost Lecture: The Motion of Planets Around the Sun|date=1996|publisher=W. W. Norton & Company|isbn=978-0393039184}}</ref> But they are also a revolutionary advance beyond Newton's laws, because Coxeter formulated them in Euclidean spaces of any number of dimensions. In particular, they give us geometric pictures of all the possible motions of objects in 4-dimensional Euclidean space: <blockquote>Every orthogonal transformation in 4-space is expressible as:<br> :<math>\mathrm{Q}^q \mathrm{R}^r \mathrm{T}^t</math><br> where <math>(2^q + r + t \le 4)</math>. Every displacement is either a double rotation <math>\mathrm{Q}^2</math>, or a screw-displacement <math>\mathrm{QT}</math> [where the rotation component <math>\mathrm{Q}</math> is a simple rotation, but the <math>\mathrm{QT}</math> is chiral like a <math>\mathrm{Q^2}</math>]. Every enantiomorphous transformation in 4-space (reversing chirality) is a <math>\mathrm{QRT}</math>.</blockquote> While this description should be understood as geometric pictures, some of the pictures may not be easy for us to visualize, since we have no physical experience in 4-dimensional space. Rotation (<math>\mathrm{Q}</math>), reflection (<math>\mathrm{R}</math>) and translation (<math>\mathrm{T}</math>) are obvious analogues of what they are in three-dimensional space, but double rotation (<math>\mathrm{Q}^2</math>) is something new and unprecedented in our physical experience, because double rotations cannot occur until there are four or more dimensions of space in which to rotate. A point in 4-space may be in motion on two circles in two completely orthogonal rotation planes simultaneously. Nothing constrains the two circles to be of the same radius, or constrains either circle from being of infinite radius such that the point moves in a straight line within its rotation plane: a translation <math>\mathrm{T}</math> rather than a rotation <math>\mathrm{Q}</math>. The motion of a rigid object defined by multiple points is constrained by its rigidity, such that the radii of both circles may approach infinity, but only one of the two radii may actually reach infinity. Only one of the two rotations may actually be a translation. Four dimensional Euclidean space can contain no such thing as a <math>\mathrm{Q}^2\mathrm{T}</math>. A translating double rotation <math>\mathrm{Q}^2</math>, like a translating simple rotation <math>\mathrm{Q}</math>, is simply a screw translation <math>\mathrm{QT}</math>. That is the essence of the way the principle of relativity operates in Euclidean 4-space. An object which is double-rotating in its own proper inertial reference frame may be seen to be performing nothing more mysterious than a screw translation, when observed from an inertial reference frame from which the object is in relative translational motion. In a universe which is real Euclidean four-dimensional space <math>\mathbb{R}^4</math>, wherein these motions occur only at the constant velocity <math>c</math>, there is a universal Cartesian 4-coordinate reference frame in which every rigid object is translating on a <math>\mathrm{QT}</math> at velocity <math>c</math>. That universal inertial reference frame is not the proper reference frame of any object or observer, wherein the object or observer is stationary, but it is the common reference frame of all observers. == Light propagates through 4-space at twice its apparent velocity <math>c</math>== Coxeter's laws of kinematics in 4-dimensional Euclidean space apply to all objects with mass, but we find there is an additional kind of displacement which applies only to massless particles such as photons. Light quanta (photons) translate through 4-space by 4-dimensional reflection <math>\mathrm{R}^4</math>, which may be termed a double translation <math>\mathrm{T}^2</math>, a pure translation via two pairs of parallel reflections without any rotation component <math>\mathrm{Q}</math>. Matter (atoms and all particles with mass) are perpetually rotating and translating through 4-space by <math>\mathrm{QT}</math>, a screw translation of a rotating object, which is relativistically equivalent to a stationary isoclinic <math>\mathrm{Q^2}</math>, an isoclinically rotating object such as an atom. A simple rotation <math>\mathrm{Q}</math> or simple translation <math>\mathrm{T}</math> is a double reflection <math>\mathrm{R^2}</math>, so a <math>\mathrm{QT}</math> or <math>\mathrm{Q^2}</math> is an <math>\mathrm{R^4}</math>, but not with the same group of reflection angles as a light signal <math>\mathrm{R^4}</math>. A translation <math>\mathrm{T = R^2}</math> is a double reflection in two parallel planes, and a rotation <math>\mathrm{Q = R^2}</math> is a double reflection in two intersecting planes, as in a <math>\mathrm{QT = R^4}</math> which is both at once. A double translation <math>\mathrm{T^2 = R^4}</math> is two double reflections in pairs of parallel planes at once, a reflection in four non-intersecting parallel planes; it is all translation and no rotation. In a <math>\mathrm{T^2}</math> all the motion goes to translation, so the translation goes twice as far as the simple translation <math>\mathrm{T}</math> in a <math>\mathrm{QT}</math>. A double translation <math>\mathrm{T^2 = R^4}</math> is the opposite of a double rotation <math>\mathrm{Q^2 = R^4}</math>, which is stationary but rotates twice as far as the simple rotation <math>\mathrm{Q}</math> in a <math>\mathrm{QT}</math>. The product of the two translations in a <math>\mathrm{T^2}</math> is a diagonal 4-space translation over the long diameter of the unit 4-hypercube, exactly twice the distance of a simple <math>\mathrm{T}</math> over the edge length (or radius) of the unit 4-hypercube. The [[w:Tesseract|4-hypercube (also known as the 8-cell or tesseract)]] is ''radially equilateral'', which means its edge length is equal to its radius, like the hexagon, so its long diameter (twice its radius) is exactly twice its edge length. The photon moves an equal distance in four orthogonal directions. By the four-dimensional Pythagorean theorem, each of those four distances is half the total distance the photon moves: one edge length (one radius) is half the total diagonal distance moved (the long diameter). That total movement is a double-the-distance translation, but without any rotation component, so it cannot carry any mass with it. A <math>\mathrm{T^2}</math> cannot reposition a 4-polytope the way a <math>\mathrm{QT}</math> does, it can only reposition a quantum of energy that has no distinguishing rotational symmetry, such as a photon. That is the price light pays to move exactly twice as fast as matter.{{Efn| ...lensing of double translations <math>\mathrm{T^2 = R^4}</math> in more than two pairs of parallel planes at once...relationship to the frequency of light emitted and the coherence length of the wave packet...}} == Special relativity is Galilean relativity in a Euclidean space of four orthogonal dimensions == {{Efn|...TAC suggests this section is needed sooner, i.e. in the preceding Special Relativity section, as it explains how Euclidean relativity reduces special relativity to 4D perspective geometry...it's misplaced (too late) here...}} Perspective effects known as the Lorentz transformations occur because each observer's proper 3-dimensional space is a moving curved manifold embedded in flat 4-dimensional Euclidean space. The curvature of their 3-space complicates sightline calculations for observers; they sometimes require Lorentz transformations to produce the actual 4-space Cartesian coordinates of objects in the scene being observed. But if all four spatial dimensions are considered, no Lorentz transformations are required (or permitted) in correct scene construction, except when an observer wants to calculate a projection, that is, the shadow of how things will appear to them from a three-dimensional viewpoint (not how they really are).{{Sfn|Yamashita|2023}} Space really has four orthogonal dimensions, and space and time behave there just as they do in a classical vector space, only bigger by one dimension. It is not necessary to combine 4-space with time in a unified spacetime to explain 4-dimensional perspective effects at high relative velocities, because Euclidean 4-space is already 4-dimensional, and those effects fall out naturally from the 4-dimensional Pythagorean theorem, exactly as ordinary visual perspective does in three dimensions from the 3-dimensional Pythagorean theorem. Because one of the four spatial dimensions corresponds to an observer's direction of motion (in both space and proper time), and all observers and all scenes being observed are in motion (at constant velocity) in their respective proper time directions, we observe perspective foreshortenings in time as well as in a spatial dimension. In special relativity these perspective effects are reciprocal, precisely because they are only apparent, not actual, changes in size and duration. (In general relativity the actual rate of physical processes varies from place to place, and reference frame differences are neither reciprocal nor illusory.) None of these Lorentz effects are beyond geometric explanation or paradoxical. The universe is unexpectedly strange to us in precisely the ways the Euclidean fourth dimension is strange to us; but that does hold many surprises. Euclidean 4-space is much more interesting than Euclidean 3-space, analogous to the way 3-space is much more interesting and deeply explanatory to us than it would be if we experienced it only as a 2-space with many folds and curves, as perhaps an ant does. The emergent properties of 4-space are hard for us to visualize because they lie so wholly beyond our physical experience, just as it was hard for our ancestors to imagine the earth as round like a ball. However, Euclidean spaces of successive dimensions are analogous, and so higher dimensional spaces can be anticipated and explored: that is Schläfli's great discovery. Moreover dimensional analogy itself, like everything else in nature, is an exact expression of intrinsic group-theoretic symmetries: that is Nother's great discovery. == Dimensional relativity == Coxeter's kinetic law of <math>n</math>-dimensional congruent Euclidean transformations may be called ''dimensional relativity'', since it captures the theories of special and general relativity, and has its roots in dimensional analogy. Dimensional analogy is the exploration of [[w:Hermann_Grassmann#Mathematician|Hermann Grassmann's vector space principle]], in which space cannot be limited to any finite number of dimensions. The geometry of higher-dimensional space is accessable by reason of direct analogy, as [[w:Ludwig Schläfli|Ludwig Schläfli]] subsequently demonstrated. By analogy to the surface of the earth, the bounding surface of a spherical region of <math>n</math>-dimensional Euclidean space is an <math>(n-1)</math>-sphere, a spherical space of one fewer dimensions than the <math>n</math>-ball of Euclidean space it surrounds. In dimensional relativity the sky is not a ceiling, but an infinite regress of alternating spherical and Euclidean <math>n</math>-spaces of increasing <math>n</math>, accessible from each observer's point of view. By dimensional analogy, each observer looks up into their own reference frame's regress of concentric alternating <math>n</math>-spaces. By the capacity for dimensional analogy which they possess, some observers see deeper into <math>n</math>-dimensional space than others. == Polycentric spherical relativity == An intelligent observer equipped with the principle of relativity may perceive the universe from any inertial reference frame, not only from their own proper stationary reference frame in the <math>n</math>-space universe in which they physically locate themself. We see that every observer may also properly view themself as stationary and the universe as an <math>(n+1)</math>-sphere with themself at the center observing it, perceptually equidistant from all points on its <math>n</math>-space surface, including their own physical location which is one of those surface points, distinguished to them but moving on the surface, and not the center of anything. This ''polycentric model'' of the universe is a further restatement of the principle of relativity. It is compatible with Galileo's relativity of uniformly moving objects in ordinary space, Einstein's special relativity of inertial reference frames in 4-dimensional spacetime, Einstein's general relativity of all reference frames in non-Euclidean spacetime, and Coxeter's dimensional relativity of orthogonal group actions in Euclidean and spherical spaces of any number of dimensions. It should be known as Thoreau's principle of ''spherical relativity'', since the first precise written statement of it appears in 1849: "The universe is a sphere whose center is wherever there is intelligence."{{Sfn|Thoreau|1849|p=349|ps=; "The universe is a sphere whose center is wherever there is intelligence." [Contemporaneous and independent of [[W:Ludwig Schlafli|Ludwig Schlafli]]'s pioneering work enumerating the complete set of regular polyschemes in any number of dimensions.]}} == Revolutions == The original Copernican revolution in 1543 displaced the center of the universe from the center of the earth to a point farther away, the center of the sun, with the earth performing a ''revolution'' around the sun, and the stars remaining on a fixed 2-sphere around the sun instead of around the earth. But this led inevitably to the recognition that the sun must be a star itself, not equidistant from all the stars, and the center of but one of many spheres, no monotheistic center at all. In such fashion the Euclidean four-dimensional revolution, emerging three to five centuries later, initially lends itself to the big bang theory of a single origin of the whole universe, but leads inevitably to the recognition that all the galaxies need not be equidistant from a single origin in time, any more than all the stars lie in the same galaxy, equidistant from a single center in space. The expanding sphere of matter on the surface of which we find ourselves living is likely to be one of many 3-spheres expanding at velocity <math>c</math>, with their big bang origins occurring at distinct times and places in the ''n''-dimensional universe. The most distant objects we see when we look up at night may not all have the same origin in space and time. As recently as Copernicus we believed all the stars lay on a single 2-sphere embedded in Euclidean 3-space, with our sun at its center. During the enlightenment we dispersed those stars into an infinite Euclidean 3-space, and relinquished our privileged position at the center. Then Einstein showed that our 3-space could not be Euclidean, that it must be a 3-manifold curved in every place in obedience to Newton's inverse-square law of gravity; and in a geometry related to time, at least, it must be 4-dimensional. In this work we suggest a theory of ''n''-dimensional real space and how light travels in it, a theory which says we can see into four orthogonal dimensions of Euclidean space, and so when we look up at night we see cosmological objects distributed in at least four dimensions of space around us, rather than all located in our own local 3-space. Looking still deeper and farther out, the universe viewed as a 4-sphere might, or might not, be expanding, and the most distant objects we see when we look up at night may, or may not, lie in our 4-dimensional hyperplane. Real space has ''n'' dimensions as [[w:Hermann_Grassmann|Grassmann]] and [[w:Schläfli|Schläfli]] showed, and we do not know how many dimensions the most distant objects we see may be distributed in. They need not all lie within the four spatial dimensions in which we have now learned to observe them, any more than they lie in the three dimensional hyperplane of local space in which we find everything residing in our solar system. When we look up at the objects that surround us, we have no way of discerning how many dimensions beyond three the space we are looking into has. We know their distance from us primarily by virtue of how long it takes their light to reach us. We can measure their distribution around us in 3-space or 4-space, but that is simply how we choose to measure their positions, not an actual finding of how they are distributed. Even if it is now evident that they do not all lie in the same 3-space, how many more dimensions than three are needed to contain them? We observe that our 4-ball galaxy is embedded in Euclidean ''n''-space as one of many 4-ball galaxies, each translating in a distinct direction through 4-space at velocity <math>c</math>, on more or less divergent paths from each other. But only much closer observation will reveal evidence of whether everything we see lies in the same Euclidean 4-space, or if it is distributed in five or more dimensions, and how it is moving there. To remain in agreement with the theory of relativity, the Euclidean four-dimensional viewpoint requires that all mass-carrying objects be in motion in some distinct direction through 4-space at the constant velocity <math>c</math>, although the relative velocity between nearby objects is much smaller since they move on similar vectors, aimed away from a common origin point in the past. It is natural to expect that objects moving at constant velocity away from a common origin will be distributed roughly on the surface of an expanding 3-sphere. Although their paths away from their origin are not straight lines but various helical isoclines (screw translations), nearby objects must be translating radially at the same velocity, since the objects in a system (such as our solar system or galaxy) do not separate rapidly over time but remain in orbital formation. Each system's screw translation has ''two'' [[w:Completely_orthogonal|completely orthogonal]] components of motion in 4-space, an orbital rotation (such as the earth's around our sun) and a linear translation of the entire system at velocity <math>c</math> in the direction of the original 3-sphere's radial expansion (along the system's proper time vector). Of course the view from our solar system does not suggest that each galaxy's own distinct 3-sphere is expanding at this great rate from its galactic center. The standard theory has been that the entire observable universe is expanding from a single big bang origin in time, with galaxies forming later. While the Euclidean four-dimensional viewpoint lends itself to that standard theory, it also supports theories which require no single origin point in space and time. These are the voyages of starship Earth, to boldly go where no one has gone before. We made the jump to lightspeed long ago, in whatever big bang our atoms emerged from, and have never slowed down since. == Origins of the theory == Einstein himself may have been the first to imagine the universe as the three-dimensional surface of a four-dimensional Euclidean 3-sphere, in what was narrowly the first written articulation of the geometry of Euclidean 4-space relativity, contemporaneous with the teen-aged Coxeter's (quoted below).{{Efn|[[W:William Rowan Hamilton|Hamilton]]'s algebra '''H''' of [[W:Quaternions|quaternions]] contains the notion of a [[W:Three-dimensional sphere|three-dimensional sphere]] embedded in a four-dimensional space, but Hamilton did not conceive of the quaternions as the Cartesian 4-coordinates of a Euclidean 4-space, and did not describe our ordinary 3-space as embedded in Euclidean 4-space.}} Einstein did this as a [[W:Gedankenexperiment|gedankenexperiment]] in the context of investigating whether his equations of general relativity predicted an infinite or a finite universe, in his 1921 Princeton lecture.<ref>{{Cite book|url=http://www.gutenberg.org/ebooks/36276|title=The Meaning of Relativity|last=Einstein|first=Albert|publisher=Princeton University Press|year=1923|isbn=|location=|pages=110-111}}</ref> He invited us to imagine "A spherical manifold of three dimensions, embedded in a Euclidean continuum of four dimensions", but he was careful to disclaim parenthetically that "The aid of a fourth space dimension has naturally no significance except that of a mathematical artifice." Informally, the Euclidean 4-dimensional theory of relativity may be given as a sort of reciprocal to that disclaimer of Einstein's: ''The Minkowski spacetime has naturally no significance except that of a mathematical artifice, as an aid to understanding how things will appear to an observer from their perspective; the foreshortenings, clock desynchronizations and other Lorentz transformations it predicts are proper calculations of actual perspective effects; but real space is a flat, Euclidean continuum of four orthogonal spatial dimensions, and in it the ordinary laws of a flat vector space hold (such as the Pythagorean theorem), and all sightline calculations work classically, so long as you consider all four spatial dimensions.'' The Euclidean theory of relativity differs from the special theory of relativity in ascribing to the physical universe a geometry of four or more orthogonal spatial dimensions, rather than the special theory's [[w:Minkowski spacetime|Minkowski spacetime]] geometry, in which three spatial dimensions and a time dimension comprise a unified spacetime of four dimensions. Anco and Maghadam found that <math>SO(4)</math> breaks to <math>\mathbb{S}^3</math> (the 3-sphere) if the energy in the Kepler orbit is negative (an elliptical orbit), and to <math>H^3</math> (Minkowski spacetime) if the energy is positive (a hyperbolic orbit). Therefore the fact that the planets orbit on ellipses in our 3-space suggests that they orbit on a 3-sphere embedded in Euclidean 4-space which is the actual geometry of our physical universe, and Minkowski spacetime is an abstraction; the reciprocal of Einstein's disclaimer is the direct model. Of course spacetime remains a true and useful abstraction, although it must relinquish its privileged position as our exclusive conception of our place in space.{{Efn| ...origins of the Euclidean 4-space insight in the observations of Fock, Atkinson, Moser and others.}} The invention of Euclidean geometry of more than three spatial dimensions preceded Einstein's theories by more than fifty years, when it was worked out originally by the Swiss mathematician [[w:Ludwig Schläfli|Ludwig Schläfli]] before 1853.{{Sfn|Coxeter|1973|loc=§7. Ordinary Polytopes in Higher Space; §7.x. Historical remarks|pp=141-144|ps=; "Practically all the ideas in this chapter ... are due to Schläfli, who discovered them before 1853 — a time when Cayley, Grassmann and Möbius were the only other people who had ever conceived the possibility of geometry in more than three dimensions."}} Schläfli extended Euclid's geometry of one, two, and three dimensions in a direct way to four or more dimensions, generalizing the rules and terms of [[w:Euclidean geometry|Euclidean geometry]] to spaces of any number of dimensions. He coined the general term ''[[polyscheme]]'' to mean geometric forms of any number of dimensions, including two-dimensional [[w:polygon|polygons]], three-dimensional [[w:polyhedron|polyhedra]], four dimensional [[w:polychoron|polychora]], and so on, and in the process he found all of the [[w:Regular polytope|regular polyschemes]] that are possible in every dimension, including in particular the [[User:Dc.samizdat/Rotations#Sequence of regular 4-polytopes|six convex regular polychora]] which can be constructed in a Euclidean space of four dimensions (the set analogous to the five [[w:Platonic solid|Platonic solids]] the ancients found in three dimensional space). Thus Schläfli was the first to explore the fourth dimension, reveal its emergent geometric properties, and discover its astonishing regular objects. Because his work was only published posthumously in 1901, and remained almost completely unknown until Coxeter published [[w:Regular_Polytopes_(book)|Regular Polytopes]] in 1947, other researchers had more than fifty years to rediscover the regular polychora, and competing terms were coined; today [[w:Reinhold_Hoppe|Reinhold Hoppe]]'s word ''[[w:Polytope|polytope]]'' is the commonly used term for ''polyscheme.''{{Efn|[[w:Reinhold_Hoppe|Reinhold Hoppe]]'s German word ''polytop'' was introduced into English by [[W:Alicia Boole Stott|Alicia Boole Stott]], who like Hoppe and [[W:Thorold Gosset|Thorold Gosset]] rediscovered Schlafli's six regular convex 4-polytopes, with no knowledge of their prior discovery. Today Schläfli's original ''polyschem'', with its echo of ''schema'' as in the configurations of information structures, seems even more fitting in its generality than ''polytope'' -- perhaps analogously as information software (programming) is even more general than information hardware (computers).}} Because of this century-long lag in the dissemination of a scientific discovery, the regular 4-polytopes appear to have played no role at all, by any name, in the twentieth century discovery and evolution of the theories of relativity and quantum mechanics.{{Efn|One could argue that the higher-dimensional polytopes have barely influenced science or culture at all thus far. The physicist John Edward Huth's comprehensive deep dive through the history of cultural and scientific concepts of physical space, from ancient flatland models of the world through general relativity and quantum mechancs, shows exactly how we got to our present standard model of the universe, although it includes no mention of higher-dimensional Euclidean space.<ref>{{Cite book|last=Huth|first=John Edward|title=A Sense of Space: A local's guide to a flat earth, the edge of the cosmos, and other curious places|year=2025|publisher=University of Chicago Press}}</ref>}} == Boundaries == <blockquote>Ever since we discovered that Earth is round and turns like a mad-spinning top, we have understood that reality is not as it appears to us: every time we glimpse a new aspect of it, it is a deeply emotional experience. Another veil has fallen.<ref>{{Cite book|author=Carlo Rovelli|author-link=W:Carlo Rovelli|title=Seven Brief Lessons on Physics|publisher=Riverhead|year=2016|isbn=978-0399184413}}</ref></blockquote> Of course it is strange to consciously contemplate this world we inhabit, our planet, our solar system, our 3-sphere surface in our vast galaxy, as the merest film, a boundary no thicker in the places we inhabit than the diameter of an electron (though much thicker in some places we cannot inhabit, such as the interior of stars). But is not our unconscious traditional concept of the boundary of our world even stranger? Since the enlightenment we are accustomed to thinking that there is nothing beyond three dimensional space: no boundary, because there is nothing else to separate us from. But anyone who knows the [[polyscheme]]s Schläfli discovered knows that space can have any number of dimensions, and that there are fundamental objects and motions to be discovered in four dimensions that are even more various and interesting than those we can discover in three. The strange thing, when we think about it that way, is that there ''is'' a boundary between three and four dimensional space. ''Why'' can't we move (or apparently, see) in more than three dimensions? Why is our physical world apparently only three dimensional? Why would it have just ''three'' dimensions, and not four, or five, or the ''n'' dimensions that Schläfli mapped? What is the nature of the boundary which confines us to just three dimensions? We know that in Euclidean geometry the boundary between three and four dimensions is itself a spherical three dimensional space, so we should suspect that we are materially confined within such a curved boundary surface. Light need not be confined with us within our three dimensional boundary space. We would look directly through four dimensional space in our natural way, by receiving light signals that travelled through it to us on straight lines. In that case the reason we do not observe a fourth spatial dimension in our vicinity is that there are no nearby objects in it, just off our hyperplane in the wild. The nearest four-dimensional object we can see with our eyes is our sun, which lies equatorially in our own hyperplane, though it bulges out of it above and below. But when we look up at the heavens, every pinprick of light we observe is itself a four-dimensional object off our hyperplane, and they are distributed all around us in four-dimensional space through which we gaze. We are four-dimensionally sighted creatures, even though our bodies are three-dimensional objects, thin as an atom in the fourth dimension. But that should not perplex us: we can see into three dimensional space even though our retinas are two dimensional objects, thin as a photoreceptor cell. Our unconscious provincial concept is that there is nothing else outside our three dimensional world: no boundary, because there is nothing else to separate us from. But Schläfli discovered something else: all the astonishing regular objects that exist in higher dimensions, which vastly extend our notions of the beauty and mystery of space itself, and the intrinsic spatial symmetries of our universe which geometry reveals. Space is more commodious than we thought it was, and permits previously unimagined objects and motions. So our provincial conception of our place in it now has the same kind of status as our idea that the sun rises in the east and passes overhead: it is mere appearance, not a true model and no longer a proper explanation. An inertial boundary is an explanation, be it ever so thin. And would a boundary of ''no'' thickness, a mere abstraction with no physical power to separate, be a more suitable explanation? We must look for a physically powerful explanation in the geometry of space itself, which general relativity properly associates with the gravitational or inertial force. <blockquote>The number of dimensions possessed by a figure is the number of straight lines each perpendicular to all the others which can be drawn on it. Thus a point has no dimensions, a straight line one, a plane surface two, and a solid three .... In space as we now know it only three lines can be imagined perpendicular to each other. A fourth line, perpendicular to all the other three would be quite invisible and unimaginable to us. We ourselves and all the material things around us probably possess a fourth dimension, of which we are quite unaware. If not, from a four-dimensional point of view we are mere geometrical abstractions, like geometrical surfaces, lines, and points are to us. But this thickness in the fourth dimension must be exceedingly minute, if it exists at all. That is, we could only draw an exceedingly small line perpendicular to our three perpendicular lines, length, breadth and thickness, so small that no microscope could ever perceive it. We can find out something about the conditions of the fourth and higher dimensions if they exist, without being certain that they do exist, by a process which I have termed "Dimensional Analogy."<ref>{{Citation|title=Dimensional Analogy|last=Coxeter|first=Donald|date=February 1923|publisher=Coxeter Fonds, University of Toronto Archives|authorlink=W:Harold Scott MacDonald Coxeter|series=|postscript=|work=}}</ref></blockquote> I believe, but I cannot prove, that we live in real space, which is Schläfli's Euclidean space of ''n'' analogous dimensions. As Grassmann showed first, space cannot be limited to any finite number of dimensions. There will always be higher dimensions to discover, first in imagination and then to explore physically, each an astonishing new enlightenment.<ref>{{Cite book|first=T.S.|last=Eliot|title=Little Gidding|volume=Four Quartets|year=1943}}<blockquote> :We shall not cease from exploration :And the end of all our exploring :Will be to arrive where we started :And know the place for the first time. :Through the unknown, remembered gate :When the last of earth left to discover :Is that which was the beginning; :At the source of the longest river :The voice of the hidden waterfall :And the children in the apple-tree :Not known, because not looked for :But heard, half-heard, in the stillness :Between two waves of the sea. </blockquote></ref> Schläfli discovered every regular convex polytope that exists in any dimension, but that was only the beginning of the story of dimensional analogy, not its end or even the end of its beginning. That project is forever beginning anew. Coxeter discovered that Schläfli's Euclidean space is an expression of intrinsic symmetries, as Noether discovered all of physics is. Kappraff and Adamson discovered that even the sequences of humble regular polygons have fractal complexity. Symmetry itself is chaotic, always reachable but forever beyond our complete grasp. We are on a Wilderness Project, and just at its beginning, but already we observe a Euclidean space of four or more orthogonal spatial dimensions in which all objects with mass move ceaselessly at the constant velocity <math>c</math>, the universal rate at which everything moves, quantum events occur, and each of our proper times evolves. I believe these facts explain the experimentally verified theories of relativity and quantum mechanics, by revealing their unified polycentric geometry, the same way the facts about Copernicus's heliocentric solar system explained the observed motions of the planets, by revealing the geometry of gravity. But others will have to do the math, work out the physics, and perform experiments to prove or disprove all of this, because I don't have the mathematics; entirely unlike Coxeter and Einstein, I am illiterate in those languages. <blockquote> ::::::BEECH :Where my imaginary line :Bends square in woods, an iron spine :And pile of real rocks have been founded. :And off this corner in the wild, :Where these are driven in and piled, :One tree, by being deeply wounded, :Has been impressed as Witness Tree :And made commit to memory :My proof of being not unbounded. :Thus truth's established and borne out, :Though circumstanced with dark and doubt— :Though by a world of doubt surrounded. :::::::—''The Moodie Forester''<ref>{{Cite book|title=A Witness Tree|last=Frost|first=Robert|year=1942|series=The Poetry of Robert Frost|publisher=Holt, Rinehart and Winston|edition=1969|}}</ref> </blockquote> == Appendix: Sequence of regular 4-polytopes == {{Regular convex 4-polytopes|wiki=W:|columns=7}} == ... == {{Efn|In a ''[[W:William Kingdon Clifford|Clifford]] displacement'', also known as an [[W:Rotations in 4-dimensional Euclidean space#Isoclinic rotations|isoclinic rotation]], all the Clifford parallel{{Efn|name=Clifford parallels}} invariant planes are displaced in four orthogonal directions (two completely orthogonal planes) at once: they are rotated by the same angle, and at the same time they are tilted ''sideways'' by that same angle. A [[W:Rotations in 4-dimensional Euclidean space#Isoclinic rotations|Clifford displacement]] is [[W:8-cell#Radial equilateral symmetry|4-dimensionally diagonal]].{{Efn|name=isoclinic 4-dimensional diagonal}} Every plane that is Clifford parallel to one of the completely orthogonal planes (including in this case an entire Clifford parallel bundle of 4 hexagons, but not all 16 hexagons) is invariant under the isoclinic rotation: all the points in the plane rotate in circles but remain in the plane, even as the whole plane tilts sideways. All 16 hexagons rotate by the same angle (though only 4 of them do so invariantly). All 16 hexagons are rotated by 60 degrees, and also displaced sideways by 60 degrees to a Clifford parallel hexagon. All of the other central polygons (e.g. squares) are also displaced to a Clifford parallel polygon 60 degrees away.|name=Clifford displacement}} {{Efn|It is not difficult to visualize four hexagonal planes intersecting at 60 degrees to each other, even in three dimensions. Four hexagonal central planes intersect at 60 degrees in the [[W:cuboctahedron|cuboctahedron]]. Four of the 24-cell's 16 hexagonal central planes (lying in the same 3-dimensional hyperplane) intersect at each of the 24-cell's vertices exactly the way they do at the center of a cuboctahedron. But the ''edges'' around the vertex do not meet as the radii do at the center of a cuboctahedron; the 24-cell has 8 edges around each vertex, not 12, so its vertex figure is the cube, not the cuboctahedron. The 8 edges meet exactly the way 8 edges do at the apex of a canonical [[W:cubic pyramid]|cubic pyramid]].{{Efn|name=24-cell vertex figure}}|name=cuboctahedral hexagons}} {{Efn|name=radially equilateral}} {{Efn|Eight {{sqrt|1}} edges converge in curved 3-dimensional space from the corners of the 24-cell's cubical vertex figure{{Efn|The [[W:vertex figure|vertex figure]] is the facet which is made by truncating a vertex; canonically, at the mid-edges incident to the vertex. But one can make similar vertex figures of different radii by truncating at any point along those edges, up to and including truncating at the adjacent vertices to make a ''full size'' vertex figure. Stillwell defines the vertex figure as "the convex hull of the neighbouring vertices of a given vertex".{{Sfn|Stillwell|2001|p=17}} That is what serves the illustrative purpose here.|name=full size vertex figure}} and meet at its center (the vertex), where they form 4 straight lines which cross there. The 8 vertices of the cube are the eight nearest other vertices of the 24-cell. The straight lines are geodesics: two {{sqrt|1}}-length segments of an apparently straight line (in the 3-space of the 24-cell's curved surface) that is bent in the 4th dimension into a great circle hexagon (in 4-space). Imagined from inside this curved 3-space, the bends in the hexagons are invisible. From outside (if we could view the 24-cell in 4-space), the straight lines would be seen to bend in the 4th dimension at the cube centers, because the center is displaced outward in the 4th dimension, out of the hyperplane defined by the cube's vertices. Thus the vertex cube is actually a [[W:cubic pyramid|cubic pyramid]]. Unlike a cube, it seems to be radially equilateral (like the tesseract and the 24-cell itself): its "radius" equals its edge length.{{Efn|The vertex cubic pyramid is not actually radially equilateral,{{Efn|name=radially equilateral}} because the edges radiating from its apex are not actually its radii: the apex of the [[W:cubic pyramid|cubic pyramid]] is not actually its center, just one of its vertices.}}|name=24-cell vertex figure}} {{Efn|The hexagons are inclined (tilted) at 60 degrees with respect to the unit radius coordinate system's orthogonal planes. Each hexagonal plane contains only ''one'' of the 4 coordinate system axes.{{Efn|Each great hexagon of the 24-cell contains one axis (one pair of antipodal vertices) belonging to each of the three inscribed 16-cells. The 24-cell contains three disjoint inscribed 16-cells, rotated 60° isoclinically{{Efn|name=isoclinic 4-dimensional diagonal}} with respect to each other (so their corresponding vertices are 120° {{=}} {{radic|3}} apart). A [[16-cell#Coordinates|16-cell is an orthonormal ''basis'']] for a 4-dimensional coordinate system, because its 8 vertices define the four orthogonal axes. In any choice of a vertex-up coordinate system (such as the unit radius coordinates used in this article), one of the three inscribed 16-cells is the basis for the coordinate system, and each hexagon has only ''one'' axis which is a coordinate system axis.|name=three basis 16-cells}} The hexagon consists of 3 pairs of opposite vertices (three 24-cell diameters): one opposite pair of ''integer'' coordinate vertices (one of the four coordinate axes), and two opposite pairs of ''half-integer'' coordinate vertices (not coordinate axes). For example: {{indent|17}}({{spaces|2}}0,{{spaces|2}}0,{{spaces|2}}1,{{spaces|2}}0) {{indent|5}}({{spaces|2}}{{sfrac|1|2}},–{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},–{{sfrac|1|2}}){{spaces|3}}({{spaces|2}}{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}}) {{indent|5}}(–{{sfrac|1|2}},–{{sfrac|1|2}},–{{sfrac|1|2}},–{{sfrac|1|2}}){{spaces|3}}(–{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},–{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}}) {{indent|17}}({{spaces|2}}0,{{spaces|2}}0,–1,{{spaces|2}}0)<br> is a hexagon on the ''y'' axis. Unlike the {{sqrt|2}} squares, the hexagons are actually made of 24-cell edges, so they are visible features of the 24-cell.|name=non-orthogonal hexagons|group=}} {{Efn|Visualize the three [[16-cell]]s inscribed in the 24-cell (left, right, and middle), and the rotation which takes them to each other. [[24-cell#Reciprocal constructions from 8-cell and 16-cell|The vertices of the middle 16-cell lie on the (w, x, y, z) coordinate axes]];{{Efn|name=six orthogonal planes of the Cartesian basis}} the other two are rotated 60° [[W:Rotations in 4-dimensional Euclidean space#Isoclinic rotations|isoclinically]] to its left and its right. The 24-vertex 24-cell is a compound of three 16-cells, whose three sets of 8 vertices are distributed around the 24-cell symmetrically; each vertex is surrounded by 8 others (in the 3-dimensional space of the 4-dimensional 24-cell's ''surface''), the way the vertices of a cube surround its center.{{Efn|name=24-cell vertex figure}} The 8 surrounding vertices (the cube corners) lie in other 16-cells: 4 in the other 16-cell to the left, and 4 in the other 16-cell to the right. They are the vertices of two tetrahedra inscribed in the cube, one belonging (as a cell) to each 16-cell. If the 16-cell edges are {{radic|2}}, each vertex of the compound of three 16-cells is {{radic|1}} away from its 8 surrounding vertices in other 16-cells. Now visualize those {{radic|1}} distances as the edges of the 24-cell (while continuing to visualize the disjoint 16-cells). The {{radic|1}} edges form great hexagons of 6 vertices which run around the 24-cell in a central plane. ''Four'' hexagons cross at each vertex (and its antipodal vertex), inclined at 60° to each other.{{Efn|name=cuboctahedral hexagons}} The [[24-cell#Hexagons|hexagons]] are not perpendicular to each other, or to the 16-cells' perpendicular [[24-cell#Squares|square central planes]].{{Efn|name=non-orthogonal hexagons}} The left and right 16-cells form a tesseract.{{Efn|Each pair of the three 16-cells inscribed in the 24-cell forms a 4-dimensional [[W:tesseract|hypercube (a tesseract or 8-cell)]], in [[24-cell#Relationships among interior polytopes|dimensional analogy]] to the way two tetrahedra form a cube: the two 8-vertex 16-cells are inscribed in the 16-vertex tesseract, occupying its alternate vertices. The third 16-cell does not lie within the tesseract; its 8 vertices protrude from the sides of the tesseract, forming a cubic pyramid on each of the tesseract's cubic cells. The three pairs of 16-cells form three tesseracts.{{Efn|name=three 8-cells}} The tesseracts share vertices, but the 16-cells are completely disjoint.{{Efn|name=completely disjoint}}|name=three 16-cells form three tesseracts}} Two 16-cells have vertex-pairs which are one {{radic|1}} edge (one hexagon edge) apart. But a [[24-cell#Simple rotations|''simple'' rotation]] of 60° will not take one whole 16-cell to another 16-cell, because their vertices are 60° apart in different directions, and a simple rotation has only one hexagonal plane of rotation. One 16-cell ''can'' be taken to another 16-cell by a 60° [[24-cell#Isoclinic rotations|''isoclinic'' rotation]], because an isoclinic rotation is [[3-sphere]] symmetric: four [[24-cell#Clifford parallel polytopes|Clifford parallel hexagonal planes]] rotate together, but in four different rotational directions,{{Efn|name=Clifford displacement}} taking each 16-cell to another 16-cell. But since an isoclinic 60° rotation is a ''diagonal'' rotation by 60° in ''two'' completely orthogonal directions at once,{{Efn|name=isoclinic geodesic}} the corresponding vertices of the 16-cell and the 16-cell it is taken to are 120° apart: ''two'' {{radic|1}} hexagon edges (or one {{radic|3}} hexagon chord) apart, not one {{radic|1}} edge (60°) apart as in a simple rotation.{{Efn|name=isoclinic 4-dimensional diagonal}} By the [[W:chiral|chiral]] diagonal nature of isoclinic rotations, the 16-cell ''cannot'' reach the adjacent 16-cell by rotating toward it; it can only reach the 16-cell ''beyond'' it. But of course, the 16-cell beyond the 16-cell to its right is the 16-cell to its left. So a 60° isoclinic rotation ''will'' take every 16-cell to another 16-cell: a 60° ''right'' isoclinic rotation will take the middle 16-cell to the 16-cell we may have originally visualized as the ''left'' 16-cell, and a 60° ''left'' isoclinic rotation will take the middle 16-cell to the 16-cell we visualized as the ''right'' 16-cell. (If so, that was our error in visualization; the 16-cell to the "left" is in fact the one reached by the left isoclinic rotation, as that is the only sense in which the two 16-cells are left or right of each other.)|name=three isoclinic 16-cells}} {{Efn|In a double rotation each vertex can be said to move along two completely orthogonal great circles at the same time, but it does not stay within the central plane of either of those original great circles; rather, it moves along a helical geodesic that traverses diagonally between great circles. The two completely orthogonal planes of rotation are said to be ''invariant'' because the points in each stay in the plane ''as the plane moves'', tilting sideways by the same angle that the other plane rotates.|name=helical geodesic}} {{Efn|A point under isoclinic rotation traverses the diagonal{{Efn|name=isoclinic 4-dimensional diagonal}} straight line of a single '''isoclinic geodesic''', reaching its destination directly, instead of the bent line of two successive '''simple geodesics'''. A '''[[W:geodesic|geodesic]]''' is the ''shortest path'' through a space (intuitively, a string pulled taught between two points). Simple geodesics are great circles lying in a central plane (the only kind of geodesics that occur in 3-space on the 2-sphere). Isoclinic geodesics are different: they do ''not'' lie in a single plane; they are 4-dimensional [[W:helix|spirals]] rather than simple 2-dimensional circles.{{Efn|name=helical geodesic}} But they are not like 3-dimensional [[W:screw threads|screw threads]] either, because they form a closed loop like any circle (after ''two'' revolutions). Isoclinic geodesics are ''4-dimensional great circles'', and they are just as circular as 2-dimensional circles: in fact, twice as circular, because they curve in a circle in two completely orthogonal directions at once.{{Efn|Isoclinic geodesics are ''4-dimensional great circles'' in the sense that they are 1-dimensional geodesic ''lines'' that curve in 4-space in two completely orthogonal planes at once. They should not be confused with ''great 2-spheres'',{{Sfn|Stillwell|2001|p=24}} which are the 4-dimensional analogues of 2-dimensional great circles (great 1-spheres).}} These '''isoclines''' are geodesic 1-dimensional lines embedded in a 4-dimensional space. On the 3-sphere{{Efn|All isoclines are geodesics, and isoclines on the 3-sphere are circles (curving equally in each dimension), but not all isoclines on 3-manifolds in 4-space are circles.}} they always occur in [[W:chiral|chiral]] pairs and form a pair of [[W:Villarceau circle|Villarceau circle]]s on the [[W:Clifford torus|Clifford torus]],{{Efn|Isoclines on the 3-sphere occur in non-intersecting chiral pairs. A left and a right isocline form a [[W:Hopf link|Hopf link]] called the {1,1} torus knot{{Sfn|Dorst|2019|loc=§1. Villarceau Circles|p=44|ps=; "In mathematics, the path that the (1, 1) knot on the torus traces is also known as a [[W:Villarceau circle|Villarceau circle]]. Villarceau circles are usually introduced as two intersecting circles that are the cross-section of a torus by a well-chosen plane cutting it. Picking one such circle and rotating it around the torus axis, the resulting family of circles can be used to rule the torus. By nesting tori smartly, the collection of all such circles then form a [[W:Hopf fibration|Hopf fibration]].... we prefer to consider the Villarceau circle as the (1, 1) torus knot [a [[W:Hopf link|Hopf link]]] rather than as a planar cut [two intersecting circles]."}} in which ''each'' of the two linked circles traverses all four dimensions.}} the paths of the left and the right [[W:Rotations in 4-dimensional Euclidean space#Double rotations|isoclinic rotation]]. They are [[W:Helix|helices]] bent into a [[W:Möbius strip|Möbius loop]] in the fourth dimension, taking a diagonal [[W:Winding number|winding route]] twice around the 3-sphere through the non-adjacent vertices of a 4-polytope's [[W:Skew polygon#Regular skew polygons in four dimensions|skew polygon]].|name=isoclinic geodesic}} {{Efn|[[File:Hopf band wikipedia.png|thumb|150px|Two [[W:Clifford parallel|Clifford parallel]] great circles spanned by a twisted [[W:Annulus (mathematics)|annulus]].]][[W:Clifford parallel|Clifford parallel]]s are non-intersecting curved lines that are parallel in the sense that the perpendicular (shortest) distance between them is the same at each point. A double helix is an example of Clifford parallelism in ordinary 3-dimensional Euclidean space. In 4-space Clifford parallels occur as geodesic great circles on the [[W:3-sphere|3-sphere]].{{Sfn|Kim|Rote|2016|pp=8-10|loc=Relations to Clifford Parallelism}} Whereas in 3-dimensional space, any two geodesic great circles on the [[W:2-sphere|2-sphere]] will always intersect at two antipodal points, in 4-dimensional space not all great circles intersect. In 4-polytopes various discrete sets of Clifford parallel non-intersecting geodesic great circles can be found on the 3-sphere. They spiral around each other in [[W:Hopf fibration|Hopf fiber bundles]] which visit all the vertices just once. The simplest example is that six mutually orthogonal great circles can be drawn on the 3-sphere, as three pairs of completely orthogonal great circles, intersecting at 8 points defining a [[16-cell]]. Each completely orthogonal pair of circles is Clifford parallel. They cannot intersect at all, because they lie in planes which intersect at only one point: the center of the 16-cell. Because they are perpendicular and share a common center, the two circles are obviously not parallel and separate in the usual way of parallel circles in 3 dimensions; rather they are connected like adjacent links in a chain, each passing through the other without intersecting at any points, forming a [[W:Hopf link|Hopf link]]|name=Clifford parallels}} {{Efn|In the 24-cell each great square plane is completely orthogonal{{Efn|name=completely orthogonal planes}} to another great square plane, and each great hexagon plane is completely orthogonal to a plane which intersects only two vertices: a great [[W:digon|digon]] plane.|name=pairs of completely orthogonal planes}} {{Efn|In an [[24-cell#Isoclinic rotations|isoclinic rotation]], each point anywhere in the 4-polytope moves an equal distance in four orthogonal directions at once, on a [[W:8-cell#Radial equilateral symmetry|4-dimensional diagonal]]. The point is displaced a total [[W:Pythagorean distance]] equal to the square root of four times the square of that distance. For example, when the unit-radius 24-cell rotates isoclinically 60° in a hexagon invariant plane and 60° in its completely orthogonal invariant plane,{{Efn|name=pairs of completely orthogonal planes}} all vertices are displaced to a vertex two edge lengths away. Each vertex is displaced to another vertex {{radic|3}} (120°) away, moving {{radic|3/4}} in four orthogonal coordinate directions.|name=isoclinic 4-dimensional diagonal}} {{Efn|Each square plane is isoclinic (Clifford parallel) to five other square planes but completely orthogonal{{Efn|name=completely orthogonal planes}} to only one of them.{{Efn|name=Clifford parallel squares in the 16-cell and 24-cell}} Every pair of completely orthogonal planes has Clifford parallel great circles, but not all Clifford parallel great circles are orthogonal (e.g., none of the hexagonal geodesics in the 24-cell are mutually orthogonal).|name=only some Clifford parallels are orthogonal}} {{Efn|In the [[16-cell#Rotations|16-cell]] the 6 orthogonal great squares form 3 pairs of completely orthogonal great circles; each pair is Clifford parallel. In the 24-cell, the 3 inscribed 16-cells lie rotated 60 degrees isoclinically{{Efn|name=isoclinic 4-dimensional diagonal}} with respect to each other; consequently their corresponding vertices are 120 degrees apart on a hexagonal great circle. Pairing their vertices which are 90 degrees apart reveals corresponding square great circles which are Clifford parallel. Each of the 18 square great circles is Clifford parallel not only to one other square great circle in the same 16-cell (the completely orthogonal one), but also to two square great circles (which are completely orthogonal to each other) in each of the other two 16-cells. (Completely orthogonal great circles are Clifford parallel, but not all Clifford parallels are orthogonal.{{Efn|name=only some Clifford parallels are orthogonal}}) A 60 degree isoclinic rotation of the 24-cell in hexagonal invariant planes takes each square great circle to a Clifford parallel (but non-orthogonal) square great circle in a different 16-cell.|name=Clifford parallel squares in the 16-cell and 24-cell}} {{Efn|In 4 dimensional space we can construct 4 perpendicular axes and 6 perpendicular planes through a point. Without loss of generality, we may take these to be the axes and orthogonal central planes of a (w, x, y, z) Cartesian coordinate system. In 4 dimensions we have the same 3 orthogonal planes (xy, xz, yz) that we have in 3 dimensions, and also 3 others (wx, wy, wz). Each of the 6 orthogonal planes shares an axis with 4 of the others, and is ''completely orthogonal'' to just one of the others: the only one with which it does not share an axis. Thus there are 3 pairs of completely orthogonal planes: xy and wz intersect only at the origin; xz and wy intersect only at the origin; yz and wx intersect only at the origin.|name=six orthogonal planes of the Cartesian basis}} {{Efn|Two planes in 4-dimensional space can have four possible reciprocal positions: (1) they can coincide (be exactly the same plane); (2) they can be parallel (the only way they can fail to intersect at all); (3) they can intersect in a single line, as two non-parallel planes do in 3-dimensional space; or (4) '''they can intersect in a single point'''{{Efn|To visualize how two planes can intersect in a single point in a four dimensional space, consider the Euclidean space (w, x, y, z) and imagine that the w dimension represents time rather than a spatial dimension. The xy central plane (where w{{=}}0, z{{=}}0) shares no axis with the wz central plane (where x{{=}}0, y{{=}}0). The xy plane exists at only a single instant in time (w{{=}}0); the wz plane (and in particular the w axis) exists all the time. Thus their only moment and place of intersection is at the origin point (0,0,0,0).|name=how planes intersect at a single point}} (and they ''must'', if they are completely orthogonal).{{Efn|Two flat planes A and B of a Euclidean space of four dimensions are called ''completely orthogonal'' if and only if every line in A is orthogonal to every line in B. In that case the planes A and B intersect at a single point O, so that if a line in A intersects with a line in B, they intersect at O.{{Efn|name=six orthogonal planes of the Cartesian basis}}|name=completely orthogonal planes}}|name=how planes intersect}} {{Efn|Polytopes are '''completely disjoint''' if all their ''element sets'' are disjoint: they do not share any vertices, edges, faces or cells. They may still overlap in space, sharing 4-content, volume, area, or lineage.|name=completely disjoint}} {{Efn|If the [[W:Euclidean distance|Pythagorean distance]] between any two vertices is {{sqrt|1}}, their geodesic distance is 1; they may be two adjacent vertices (in the curved 3-space of the surface), or a vertex and the center (in 4-space). If their Pythagorean distance is {{sqrt|2}}, their geodesic distance is 2 (whether via 3-space or 4-space, because the path along the edges is the same straight line with one 90^o bend in it as the path through the center). If their Pythagorean distance is {{sqrt|3}}, their geodesic distance is still 2 (whether on a hexagonal great circle past one 60^o bend, or as a straight line with one 60^o bend in it through the center). Finally, if their Pythagorean distance is {{sqrt|4}}, their geodesic distance is still 2 in 4-space (straight through the center), but it reaches 3 in 3-space (by going halfway around a hexagonal great circle).|name=Geodesic distance}} {{Efn|Two angles are required to fix the relative positions of two planes in 4-space.{{Sfn|Kim|Rote|2016|p=7|loc=§6 Angles between two Planes in 4-Space|ps=; "In four (and higher) dimensions, we need two angles to fix the relative position between two planes. (More generally, ''k'' angles are defined between ''k''-dimensional subspaces.)"}} Since all planes in the same [[W:hyperplane|hyperplane]] are 0 degrees apart in one of the two angles, only one angle is required in 3-space. Great hexagons in different hyperplanes are 60 degrees apart in ''both'' angles. Great squares in different hyperplanes are 90 degrees apart in ''both'' angles (completely orthogonal){{Efn|name=completely orthogonal planes}} or 60 degrees apart in ''both'' angles.{{Efn||name=Clifford parallel squares in the 16-cell and 24-cell}} Planes which are separated by two equal angles are called ''isoclinic''. Planes which are isoclinic have [[W:Clifford parallel|Clifford parallel]] great circles.{{Efn|name=Clifford parallels}} A great square and a great hexagon in different hyperplanes are neither isoclinic nor Clifford parallel; they are separated by a 90 degree angle ''and'' a 60 degree angle.|name=two angles between central planes}} {{Efn|The 24-cell contains 3 distinct 8-cells (tesseracts), rotated 60° isoclinically with respect to each other. The corresponding vertices of two 8-cells are {{radic|3}} (120°) apart. Each 8-cell contains 8 cubical cells, and each cube contains four {{radic|3}} chords (its long diagonals). The 8-cells are not completely disjoint{{Efn|name=completely disjoint}} (they share vertices), but each cube and each {{radic|3}} chord belongs to just one 8-cell. The {{radic|3}} chords joining the corresponding vertices of two 8-cells belong to the third 8-cell.|name=three 8-cells}} {{Efn|Departing from any vertex V₀ in the original great hexagon plane of isoclinic rotation P₀, the first vertex reached V₁ is 120 degrees away along a {{radic|3}} chord lying in a different hexagonal plane P₁. P₁ is inclined to P₀ at a 60° angle.{{Efn|P₀ and P₁ lie in the same hyperplane (the same central cuboctahedron) so their other angle of separation is 0.{{Efn|name=two angles between central planes}}}} The second vertex reached V₂ is 120 degrees beyond V₁ along a second {{radic|3}} chord lying in another hexagonal plane P₂ that is Clifford parallel to P₀.{{Efn|P₀ and P₂ are 60° apart in ''both'' angles of separation.{{Efn|name=two angles between central planes}} Clifford parallel planes are isoclinic (which means they are separated by two equal angles), and their corresponding vertices are all the same distance apart. Although V₀ and V₂ are ''two'' {{radic|3}} chords apart{{Efn|V₀ and V₂ are two {{radic|3}} chords apart on the geodesic path of this rotational isocline, but that is not the shortest geodesic path between them. In the 24-cell, it is impossible for two vertices to be more distant than ''one'' {{radic|3}} chord, unless they are antipodal vertices {{radic|4}} apart.{{Efn|name=Geodesic distance}} V₀ and V₂ are ''one'' {{radic|3}} chord apart on some other isocline. More generally, isoclines are geodesics because the distance between their ''adjacent'' vertices is the shortest distance between those two vertices, but a path between two vertices along a geodesic is not always the shortest distance between them (even on ordinary great circle geodesics).}}, P₀ and P₂ are just one {{radic|1}} edge apart (at every pair of ''nearest'' vertices).}} (Notice that V₁ lies in both intersecting planes P₁ and P₂, as V₀ lies in both P₀ and P₁. But P₀ and P₂ have ''no'' vertices in common; they do not intersect.) The third vertex reached V₃ is 120 degrees beyond V₂ along a third {{radic|3}} chord lying in another hexagonal plane P₃ that is Clifford parallel to P₁. The three {{radic|3}} chords lie in different 8-cells.{{Efn|name=three 8-cells}} V₀ to V₃ is a 360° isoclinic rotation.|name=360 degree geodesic path visiting 3 hexagonal planes}} {{Sfn|Mamone, Pileio & Levitt|2010|loc=§4.5 Regular Convex 4-Polytopes|pp=1438-1439|ps=; the 24-cell has 1152 symmetry operations (rotations and reflections) as enumerated in Table 2, symmetry group 𝐹₄.}} ==Notes== {{Regular convex 4-polytopes Notelist|wiki=W:}} ==Citations== {{Regular convex 4-polytopes Reflist|wiki=W:}} ==References== {{Refbegin}} * {{Cite book|title=A Week on the Concord and Merrimack Rivers|last=Thoreau|first=Henry David|author-link=W:Thoreau|publisher=James Munroe and Company|year=1849|isbn=|location=Boston|ref={{SfnRef|Thoreau|1849}}}} * {{Cite journal|title=Theoretical Evidence for Principles of Special Relativity Based on Isotropic and Uniform Four-Dimensional Space|first=Takuya|last=Yamashita|date=25 May 2023|doi= 10.20944/preprints202305.1785.v1|journal=Preprints|volume=2023|issue=2023051785|url=https://doi.org/10.20944/preprints202305.1785.v1}} * {{Cite_arXiv | arxiv=2512.02903v2 | date=2 January 2026 | title=Symmetry transformation group arising from the Laplace–Runge–Lenz vector | first1=Stephen C. | last1=Anco | first2=Mahdieh Gol Bashmani | last2=Moghadam | class=math-ph}} === [[Polyscheme|Polyschemes]] === {{Regular convex 4-polytopes Refs|wiki=W:}} {{Refend}} 3efdrczu26j5ite26jwtlb8zyhrbdw3 2835267 2835261 2026-10-01T03:50:56Z Dc.samizdat 2856930 /* Special relativity describes Euclidean 4-space */ 2835267 wikitext text/x-wiki {{align|center|David Brooks Christie}} {{align|center|dc@samizdat.org}} {{align|center|Draft in progress}} {{align|center|June 2023 - September 2026}} <blockquote>'''Abstract:''' The physical universe is properly visualized as real Euclidean space <math>\mathbb{R}^4</math> of four orthogonal spatial dimensions. Space itself has a fourth perpendicular dimension, of which we are unaware in ordinary life. Atoms are 4-polytopes, small round 4-dimensional objects, and stars are 4-balls of atomic plasma, large round 4-dimensional objects. We ourselves and our planet are only 3-dimensional objects, but nonetheless we can see in four dimensions of space. We have been unaware that when we look up at night we see stars and galaxies, themselves large 4-dimensional objects, distributed all around us in 4-dimensional Euclidean space, and moving through it, like us, at the constant velocity <math>c</math>. Light from them reaches us directly, on straight lines through 4-space. This view of the observed universe is compatible with special and general relativity, and with quantum mechanics. It furnishes those theories with an explanatory geometric model.</blockquote> == Summary == We observe that: * Physical space has four perpendicular dimensions, not just three. * Atoms are [[W:4-polytope|4-polytopes]]. * The sun is a [[W:4-ball|4-ball]] that is round in four dimensions. * Everything of intermediate size between an atom and a star, including us and our planet, lies in a 3-dimensional manifold of ordinary space. * Our entire 3-space manifold is moving through Euclidean 4-space at the speed of light, in a direction perpendicular to its three interior dimensions. * Special relativity describes the linear motion of objects and light signals in four-dimensional Euclidean space. == A theory of the Euclidean cosmos == The physical universe is properly visualized as [[w:Four-dimensional_space|real Euclidean space <math>\mathbb{R}^4</math>]] of four orthogonal spatial dimensions. Space itself has a fourth perpendicular dimension, of which we are unaware in ordinary life. Atoms are [[w:4-polytope|4-polytopes]], small round 4-dimensional objects, and stars are [[W:4-ball|4-balls]] of atomic plasma, large round 4-dimensional objects. Objects intermediate in size between atoms and stars, including molecules, people, and planets, are so flat as to be essentially 3-dimensional, having only the thickness of an atom in the orthogonal fourth dimension. All objects with mass move inertially through Euclidean 4-space at constant velocity <math>c</math> as long as they exist, and acceleration only varies their direction. Objects moving in the same direction are in the same inertial reference frame. Their direction of motion through 4-space at velocity <math>c</math> is their proper time dimension, simply because their direction and velocity of motion through time is the same as their direction and velocity of motion through space. A typical galaxy such as ours occupies a 4-ball of mostly empty space, with stars and other objects distributed non-uniformly within it. The galaxy's orbital center may be nothing: a smaller 4-ball of empty space they surround. The stars in our spiral galaxy appear from our accustomed point of view to occupy a disk-like region of 3-dimensional space, with a denser ball-like center, but they are not so confined: they are distributed within a region of 4-dimensional space. The disk and ball have thickness not only in the third dimension, but in the fourth spatial dimension as well. Light from stars and galaxies reaches us on straight lines through Euclidean 4-space, so from our viewpoint, in what we have always imagined to be a 3-space universe, we look into the surrounding 4-space. Although we are physically confined within a 3-dimensional hyperplane by the inertia of our motion through 4-space at constant velocity <math>c</math>, light signals are not so confined, so we observe all the cosmological objects surrounding us, both in and above or below our hyperplane, without perceiving their separation in our fourth orthogonal dimension, the direction of our motion. We may perceive a galaxy as elliptical when it is actually spherical, because that is how its image projects from its 4-ball shape into a 3-ball region in our hyperplane, where we measure it with our 3-dimensional bodies. More generally, orbits are circular in 4-space, but elliptical in the 3-space of their elliptic hyperplane. The galaxy as a whole, or more properly its orbital barycenter, is translating through 4-space at velocity <math>c</math>, in a distinct direction orthogonal to all three dimensions of our ordinary proper 3-space. Stars within the galaxy are translating with it at the same velocity <math>c</math> in the same direction, but on spiral trajectories as they pursue their various orbits within the galaxy. The galaxy as a whole occupies a 4-ball within its proper inertial reference frame (that is, in the moving frame of reference in which the galaxy considers itself to be a stationary rotating 4-ball). Over time, the galaxy 4-ball occupies a 4-dimensional cylinder and progresses along the cylinder's axis at velocity <math>c</math>. In this more universal inertial reference frame, the stars in the galaxy follow helical geodesic paths through the 4-cylinder; their trajectories are screw-translations through 4-space, the compound of a simple rotation and a completely orthogonal linear translation. The gravitational force and the inertial tendency to follow a geodesic are the same phenomenon, by the equivalence principle. That said, they can be distinguished, and the galaxy is held together primarily by gravity as inertia, not by gravity as attraction to a central mass toward which objects fall in orbit. There is not enough mass in the galaxy to hold it together by attraction, there is just enough to bend the stars' trajectories toward each other, in helical orbits around a barycentric axis of motion. It is the tremendous inertial force of stars in translational motion at velocity <math>c</math> that holds the cylinder of motion together, not some invisible dark matter. The observed universe as a whole appears to be a [[W:3-sphere|3-sphere]] expanding radially from a central origin point at velocity <math>c</math>, the invariant velocity of mass-carrying objects through 4-space, also the propagation speed of light relative to any moving 3-space manifold, as measured by all observers. A 3-sphere is a hypersphere in Euclidean 4-space, but the enclosing surface of a 3-sphere is a curved, finite 3-space, dimensionally analogous to the surface of the earth which is a curved, finite 2-space. This 3-sphere could be the domain of our visible cosmos, but of course we do not know for certain that all the cosmological objects we observe lie near the surface of our expanding 3-sphere, since it is only our assumption that they must all have originated in the same big bang long ago. Possibly some of the more distant objects we observe did not, and lie elsewhere, outside our big-bang's 3-sphere of outflying matter or even inside its 3-sphere, below its surface. We cannot assume that all objects in the 4-space universe lie near the surface of the same expanding 3-sphere. For all observers, the conjectured big-bang of their origin corresponds not only to a now-distant point in their proper time past, it also corresponds to a distinct now-distant point in 4-dimensional space: the same point in the same Euclidean 4-space for all observers with the same origin. Our big bang had a distinct origin point in real space as well as in real time. More generally, time and Euclidean 4-space can be measured independently, just as time and Euclidean 3-space were measured classically, without the necessity to combine them as spacetime. The same inertial force which holds the galactic cylinder of motion together also confines us physically to an exceedingly thin three-dimensional surface manifold moving through 4-space at velocity <math>c</math>. All objects in our solar system except the sun itself lie within this thinest three-dimensional manifold, and have only the thickness of an atom in their direction-of-motion fourth dimension. That is why we are 3-dimensional objects ourselves, and why we cannot construct more than three perpendiculars through a single point in our local 3-dimensional space. A spherical region of 4-space is called a [[W:4-ball|4-ball]]. The enclosing surface of a 4-ball of any size is a finite, curved (non-Euclidean) 3-dimensional space called a [[w:3-sphere|3-sphere]]. Our entire big-bang-origin universe appears to be the largest 3-sphere we observe, but each of the cosmological objects within it (including our galaxy and our sun) is contained in a smaller 3-sphere shell of its own, lying (we assume) on the largest 3-sphere embedded in its surface, like a soap bubble on the surface of a larger soap bubble. All the 3-dimensional surfaces are expanding, as the largest 3-sphere inflates at radial velocity <math>c</math>. We ourselves live within such an expanding 3-dimensional surface, in an infinitesimally curved 3-manifold surface embedded in Euclidean 4-space. That surface is the ordinary 3-dimensional space we experience, and it contains the earth, all the planets and the 3-dimensional space between them. Our solar system is only a small patch on the surface of a dimensionally rounder space, although that surface is not infinite. It is curved, and finite, analogous to the way the 2-dimensional surface of the earth -- once thought to be flat -- is curved and finite. Our solar system occupies a small patch on a filmy 4-dimensional soap-bubble of galactic size rounded by gravity, that is thicker-skinned than the diameter of an atom only in the interior of stars and supermassive objects. Our 3-manifold of ordinary space, as a surface within our moving 4-ball galaxy, is translating through 4-space at velocity <math>c</math> with the galaxy, in a distinct direction orthogonal to the manifold's three orthogonal dimensions of interior space. At every material point in the manifold (at every atom), the translation through 4-space is following a geometric law of motion discovered by Coxeter, that governs the propagation of individual objects through Euclidean space by the actions of their symmetry groups. The solar system's atoms of mass are 4-polytopes that are simultaneously rotating and translating, and as they advance together they define a moving 3-dimensional manifold by their own collective inertia, also called gravity, the property of matter's ceaseless propagation through 4-space at the constant velocity <math>c</math>, the universal rate of causality at which quantum events occur, all objects move, and the universe evolves. Any moving 3-dimensional manifold such as ours is an evolving surface boundary that is empty in most places, occupied by single atoms in comparatively fewer places, and occupied by bound complexes of multiple atoms (molecules) in still fewer places. In all these places it is no thicker than one atom in the dimension corresponding to its direction of translation, because molecules are 3-dimensional complexes of atoms that add no thickness to the manifold. Every object which we find occurring naturally in the solar system other than the sun itself, even the largest of 3-dimensional objects a planet, is a 3-dimensional smear of atoms no thicker than one atom in its fourth dimension, the direction of its linear translation through 4-space at velocity <math>c</math>. The moving surface manifold cannot be thicker than one atom at any point unless and until there is enough mass near that point for the force of gravity as attraction to overcome the force of gravity as inertia, allowing atoms to be "heaped up" into larger 4-dimensional objects that form a lump in its moving surface. We have little understanding of such 4-dimensional lumps thicker than one atom, since they occur naturally in our vicinity only in the interior of the sun. In fact the sun is the only such lump occurring naturally in our solar system. We refer to such 4-dimensional lumps of matter as atomic plasma, and have little experimental knowledge of their internal geometry or processes. We know that such a lump as the sun burns at its surface 3-sphere and emits radiation, and we know a good deal about those surface processes which are nuclear atomic processes, but we know almost nothing about its interior 4-ball, a dimensionally rounder enclosed space whose existence we did not suspect. Every moving surface boundary of matter in the observed universe is evolving in four dimensions at velocity <math>c</math>. The current location in 4-space of any of its material objects corresponds to the present moment in the proper time of that object's inertial reference frame. The object's direction of movement at velocity <math>c</math> corresponds to its proper time dimension, which is a spiral over time, not a Euclidean (straight-line) dimension, since its direction is changing in its orbit. Objects with mass of all sizes, from subatomic particles to the largest objects observed in the cosmos, are perpetually in inertial rotational motion in some orbit, and simultaneously in inertial translational motion propagating themselves through 4-space, in two completely orthogonal inertial motions each at the constant universal rate of transformation <math>c</math>. Every object with mass moves relative to universal 4-coordinate Euclidean space on its own distinct geodesic spiral, a screw displacement trajectory that is the compound of its two completely orthogonal inertial motions, a rotation and a translation. Objects without mass such as photons lie off such moving surface boundaries of matter from which they were emitted, and their motion is of a different nature. They are in translational motion at velocity <math>c</math> through all four dimensions concurrently, without any rotational component of motion, so they move through 4-space on straight lines at a compound velocity. The propagation speed of light measured on a straight line through Euclidean 4-space is <math>c\prime = 2c</math>, so we can see in four dimensions, even though we are physically confined to a 3-dimensional manifold that is moving at velocity <math>c</math>. For example, we can look across the center of the mostly-empty 4-ball containing our galaxy and see stars in the opposite sides of its concentric 3-sphere orbital surfaces. We have been unaware that when we look up at night we see stars and galaxies, themselves large 4-dimensional objects, distributed all around us in 4-dimensional Euclidean space, and moving through it, like us, at the constant velocity <math>c</math>. They move in the 4-space direction corresponding to their proper time, perpendicular to all three dimensions of their proper 3-space, and generally the farther they are from us the greater the divergence of their direction of motion from our direction of motion: the greater the relative motion between us and their Hubble redshift. Light from them reaches us directly, propagating on straight lines through 4-space at twice the velocity at which they, and we ourselves, are propagating through 4-space. This physical model of the observed universe is compatible with the theories of special and general relativity, and with the atomic theory of quantum mechanics. It explains those theories geometrically, as expressions of intrinsic symmetries in Euclidean space. == Symmetries == It is common to speak of nature as a web, and so it is, the great web of our physical experiences. Every web must have its root systems somewhere, and nature in this sense must be rooted in the symmetries which underlie physics and geometry, the [[W:Group (mathematics)|mathematics of groups]].{{Sfn|Conway, Burgiel & Goodman-Strauss|2008}} As I understand [[W:Noether's theorem|Noether's theorem]] (which is not mathematically), hers is the deepest meta-theory of nature yet, deeper than [[W:Theory of relativity|Einstein's relativity]] or [[W:Evolution|Darwin's evolution]] or [[W:Euclidean geometry|Euclid's geometry]]. It finds that all fundamental findings in physics are based on conservation laws which can be laid at the doors of distinct [[W:symmetry group |symmetry group]]s. Thus all fundamental systems in physics, as examples [[W:quantum chromodynamics|quantum chromodynamics]] (QCD) the theory of the strong force binding the atomic nucleus and [[W:quantum electrodynamics|quantum electrodynamics]] (QED) the theory of the electromagnetic force, each have a corresponding symmetry [[W:group theory|group theory]] of which they are an expression. [[W:Coxeter group|Coxeter's theory of symmetry groups]] generated by reflections did for geometry what Noether's theorem and Einstein's relativity did for physics. [[W:Coxeter|Coxeter]] showed that Euclidean geometry is based on conservation laws that correspond to distinct symmetry groups, and that their group actions express the principle of relativity. Here is Coxeter's formulation of the motions of objects (their congruent transformations) in an ''n''-dimensional Euclidean space, excerpted:{{Sfn|Coxeter|1973|pp=217-218|loc=§12.2 Congruent transformations}} <blockquote>Let <math>\mathrm{Q}</math> denote a rotation, <math>\mathrm{R}</math> a reflection, <math>\mathrm{T}</math> a translation, and let <math>\mathrm{Q}^q \mathrm{R}^r\mathrm{T}</math> denote a product of several such transformations, all commutative with one another. Then <math>\mathrm{RT}</math> is a glide-reflection (in two or three dimensions), <math>\mathrm{QR}</math> is a rotary-reflection, <math>\mathrm{QT}</math> is a screw-displacement, and <math>\mathrm{Q^2}</math> is a double rotation (in four dimensions).<br> Every orthogonal transformation is expressible as:<br> :<math>\mathrm{Q}^q \mathrm{R}^r</math><br> where <math>(2^q + r \le n)</math>, the number of dimensions.<br> Transformations involving a translation are also expressible as:<br> :<math>\mathrm{Q}^q \mathrm{R}^r \mathrm{T}</math><br> where <math>(2^q + r + 1 \le n)</math>.<br> For <math>(n = 4)</math> in particular, every displacement is either a double rotation <math>\mathrm{Q}^2</math>, or a screw-displacement <math>\mathrm{QT}</math> [where the rotation component <math>\mathrm{Q}</math> is a simple rotation, but the <math>\mathrm{QT}</math> is chiral like a <math>\mathrm{Q^2}</math>]. Every enantiomorphous transformation in 4-space (reversing chirality) is a <math>\mathrm{QRT}</math>.</blockquote> If we begin with this most elemental [[w:Kinematics|kinematics]] of Coxeter's, and also assume the [[W:Galilean relativity|Galilean principle of relativity]], every displacement in 4-space can be viewed as either a <math>\mathrm{Q^2}</math> or a <math>\mathrm{QT}</math>, because we can view any <math>\mathrm{QT}</math> as a <math>\mathrm{Q^2}</math> in a linearly moving (translating) reference frame. Therefore any transformation from one inertial reference frame to another is expressable as a <math>\mathrm{Q^2}</math>. By the same principle, we can view any <math>\mathrm{QT}</math> or <math>\mathrm{Q^2}</math> as an isoclinic (equi-angled) <math>\mathrm{Q^2}</math> by proper choice of reference frame.{{Efn|[[W:Arthur Cayley|Cayley]] showed that any rotation in 4-space can be decomposed into two isoclinic rotations, which intuitively we might see follows from the fact that any transformation from one inertial reference frame to another is expressable as a [[W:SO(4)|rotation in 4-dimensional Euclidean space]].|name=Cayley's rotation factorization into two isoclinic reference frame transformations}} Coxeter's relation is thus a mathematical statement of the principle of relativity, on group-theoretic grounds. It correctly captures the limits to [[W:General relativity|general relativity]], in that we can only exchange the translation (<math>\mathrm{T}</math>) for ''one'' of the two rotations (<math>\mathrm{Q}</math>). An observer in any inertial reference frame can always measure the presence, direction and velocity of ''one'' rotation (<math>\mathrm{Q}</math>) up to uncertainty, and can always distinguish the direction of their own proper time translation (<math>\mathrm{T}</math>). As I understand Coxeter theory (which is not mathematically), the symmetry groups underlying physics seem to have an expression in a [[W:Euclidean space|Euclidean space]] of four [[W:dimension|dimension]]s, that is, they are [[W:Euclidean geometry#Higher dimensions|four-dimensional Euclidean geometry]]. Therefore as I understand that geometry (which is entirely by synthetic methods rather than by Clifford's algebraic methods), the [[W:Atom|atom]] seems to have a distinct Euclidean geometry, such that atoms and their constituent particles are four-dimensional geometric objects (4-polytopes), and nature can be understood in terms of their [[W:group action|group actions]], including centrally their group <math>SO(4)</math> [[W:rotations in 4-dimensional Euclidean space|rotations in 4-dimensional Euclidean space]]. The distinct Coxeter symmetry groups have characteristic <math>SO(4)</math> rotational expressions as the [[W:Regular_4-polytope|regular 4-polytopes]]. Their discrete isoclinic rotations are distinguishing properties of fundamental objects in geometry, relativity and quantum mechanics. For example, atoms exhibit <math>SO(4)</math> symmetries of the discrete isoclinic (equi-angled) double rotations (<math>\mathrm{Q^2}</math>) of a set of regular 4-polytopes that is characteristic of their [[w:Atomic_number|atomic number]]. == Special relativity describes Euclidean 4-space == <blockquote>Our entire model of the universe is built on symmetries. Some, like isotropy (the laws are the same in all directions), homogeneity (same in all places), and time invariance (same at all times) seem natural enough. Even relativity, the Lorentz Invariance that allows everyone to observe a constant speed of light, has an elegance to it that makes it seem natural.<ref>{{Cite book|first=Dave|last=Goldberg|title=The Universe in the Rearview Mirror: How Hidden Symmetries Shape Reality|chapter=§10. Hidden Symmetries: Why some symmetries but not others?|year=2013|publisher=Dutton Penguin Group|isbn=978-0-525-95366-1|ref={{SfnRef|Goldberg|2013}}}}</ref></blockquote> Although the Minkowski spacetime of relativity is a non-Euclidean 4-dimensional space,{{Efn|Spacetime is a non-Euclidean (curved) 4-dimensional space because it consists of three orthogonal space dimensions and a time dimension. The time dimension is not orthogonal to the three spatial dimensions; the time coordinate has the opposite sign to the three space coordinates so spacetime is hyperbolic, not a flat Euclidean 4-space at all.}} it has been noticed that its 3-dimensional space component could be modeled as a [[W:3-sphere|3-sphere]] embedded in 4-dimensional Euclidean (flat) space. That is, we could imagine that the ordinary 3-dimensional space we perceive is the curved 3-dimensional surface of a 4-dimensional ball (since the surface of a 4-ball is a curved 3-dimensional space called a 3-sphere, just as the surface of a 3-ball like the earth is a curved 2-dimensional space called a 2-sphere). This was [[#Origins of the theory|imagined by Einstein]] himself in 1921, as a thought experiment in which he carefully described his fourth orthogonal spatial dimension as merely a mathematical abstraction. Subsequently it was noticed by others (not mainstream physicists) that if physical space were really embedded in Euclidean 4-dimensional space (with our 3-dimensional space embedded in 4-space as some non-Euclidean 3-manifold, not necessarily a 3-sphere), then the Lorentz transformation effects of special relativity (spatial forshortenings and time dilations and so forth) could all be explained by ordinary perspective geometry in 4-dimensional Euclidean space. Special relativity reduces to classical vector space geometry (based on the 4-dimensional version of the Pythagorean theorem), but if and only if every observer is moving through 4-space at a universal constant velocity <math>c</math>, in some 4-space direction.{{Sfn|Yamashita|2023}} This counter-intuitive alternative geometric model of relativity, which has usually been called [[W:Formulations of special relativity#Euclidean relativity|Euclidean relativity]], is motivated by the fact that in every kind of relativity, but originally in Einstein's special relativity, each observer moves on a vector through a Euclidean four-dimensional space consisting of their three proper spatial dimensions and their proper time dimension, and the Pythagorean vector-sum of their motion through this kind of proper 4-space is always <math>c</math>, as measured by all observers from any inertial reference frame.{{Efn|Each observer is stationary in space in their own proper reference frame, while they move at maximum velocity {{Math|c}} through their own proper time. Observed from another reference frame in relative motion, they appear foreshortened in space in their direction of motion, and their clocks appear to be slowed to less than the maximum velocity {{Math|c}}.}} This is the Lorentz invariant, that allows everyone to observe a constant speed of light, regardless of their motion relative to the light source.{{Efn| ...cite Lewis Epstein's elegant explanation of the Lorentz Invariance as observers moving at constant velocity {{Math|c}} through space and proper time.}} But no physicists have taken the leap of claiming that therefore, our universe is physically [[W:Euclidean geometry#Higher dimensions|this kind of Euclidean 4-space]], and that observers are actually moving through it at velocity <math>c</math>. In physics as it has been universally understood, observers are not supposed to be able to move at velocity <math>c</math>. Their motion takes place in 3-space and in universal coordinate time (in Minkowski spacetime), and the cosmos is considered to be a non-Euclidean 3-space, generally a closed (finite) expanding 3-space, but with only three spatial dimensions, not four. In the Euclidean relativity alternative view, however, every observer is always moving at velocity <math>c</math> through the universe, which is real Euclidean 4-dimensional space <math>\mathbb{R}^4</math>. The direction in which they are moving is called their proper time axis.{{Efn|Time in spacetime is universal coordinate time, but there is another kind of time in relativity, the proper time in each inertial reference frame. Your proper time is the time you experience, and every observer has his own proper time; proper time runs at different rates in different inertial reference frames. It runs slower (compared to universal coordinate time) in a gravitational field (according to general relativity), and observers in motion with respect to each other view each other's clocks as running slower than their own clocks (according to special relativity).}} Their movement in time is not just modelled as movement in an abstract fourth dimension (as it is in Minkowski spacetime), their movement in time is isomorphic to their movement through physical space in a distinct direction at velocity <math>c</math>. Two observers' directions of movement through space may be different (or not, if they happen to be going in the same direction). Your proper time dimension is whichever direction you are moving. The other three directions perpendicular to your proper time axis are the three dimensions of your ordinary proper space, which again, will be different directions for you than for other observers moving in a different direction. There are four orthogonal spatial dimensions which we all share, but we share the same orthogonal proper time axis and ordinary proper 3-space axes only if we are at rest with respect to each other, actually moving in the same direction at velocity <math>c</math>, in the same inertial reference frame. Your proper 4-space coordinate system is rotated with respect to another observer's proper 4-space coordinate system, precisely as your vectors (directions of motion) are rotated in Euclidean 4-space with respect to each other, but there are no metric distortions (no Lorentz transformations) between your proper Euclidean 4-space coordinate systems; you are both embedded in the same Euclidean 4-dimensional space <math>\mathbb{R}^4</math>. Lorentz transformations are required only to convert between your respective proper Minkowski spacetime coordinate systems. So in this novel alternate view of relativity, every mass in the universe must be perpetually in motion at velocity <math>c</math> through Euclidean 4-space, along with all the masses in its vicinity that are going in (nearly) the same direction. The entire solar system, for example, must be translating in the fourth dimension at the "speed of light" <math>c</math>, although we do not notice it, since we are all moving in that same direction together. Acceleration of an object varies its direction of motion through 4-space, but never its velocity, which is invariant for all objects with mass. Two objects which are in motion relative to each other are both actually in motion at the same velocity <math>c</math>, but in at least slightly different directions.{{Efn|The angular divergence between two observer's motion vectors is proportional to their relative velocity: the more they diverge, the greater their relative velocity, up to the maximum divergence possible in the space. In Euclidean relativity all observers are in motion at velocity {{Math|c}} relative to universal Cartesian 4-coordinate space, so the maximum relative velocity between two observers is {{Math|2c}} when they are moving in exactly opposite directions in 4-space. This is not a contradiction of special relativity, which limits the maximum relative velocity between two observers to {{Math|c}}, it is the same measurement in different units. Special relativity measures all velocities in Minkowski spacetime (in a non-Euclidean 3-space). Euclidean relativity measures all velocities in Euclidean 4-space.}} In Einstein's relativity, the invariant <math>c</math> is the speed of light through 3-space. In Euclidean relativity, the invariant <math>c</math> is the speed of matter through 4-space! The speed of light through 3-space is also perceived as <math>c</math> by all observers, because they are each living in a moving 3-manifold that is translating through 4-space at velocity <math>c</math>. Despite their extreme differences in viewpoint, Einstein's relativity and Euclidean relativity are equivalent theories in complete agreement with each other, by definition. The two theories make exactly the same special relativity predictions of how observers in different inertial reference frames will perceive each other's motions in time and space. It is beyond the scope of this present paper to show how they also agree on the predictions of general relativity, but it is important to understand that our formulation of Euclidean relativity requires our acceptance of the experimentally verified findings of special relativity, general relativity and quantum mechanics. Our model and the standard model both describe the same geometric relations of space and time based on the same evidence, but as embedded in two very different universal host spaces: Euclidean 4-space versus Minkowski spacetime. In some instances our model provides a geometric explanation for physical phenomena where the standard model has none, as yet. An example is the two models' differing explanations for the gravitational coherence of galaxies: either their inertial motion at velocity <math>c</math>, or their possession of experimentally undetected dark matter. A more central example is our use of Coxeter's kinematics to explain the laws of relativistic motion geometrically. {{Efn|More generally, our model is concerned with group-theoretic properties of number elucidated by Coxeter and other geometers. ...cite Kappraff & Adamson's 2003 paper on The Relationship of the Cotangent Function to Special Relativity Theory, geometry and properties of number,{{Sfn|Kappraff & Adamson|2003|loc=Special Relativity Theory, Geometry and properties of number}} which shows how the Lorentz coefficient is a function of a deep geometric property of number{{Sfn|Kappraff & Adamson|2000|loc=A Fresh Look at Number}} discovered by Steinbach,{{Sfn|Steinbach|1997|loc=Golden Fields: A Case for the Heptagon}} by means of which the root formula of geometry in any Euclidean dimension, the Pythagorean theorem, may be derived solely in terms of the addition of polygon side lengths, without recourse to their products or squares. More generally, Steinbach found that in the relations among regular polytope chords, to add is to multiply; every chord is both the product (quotient) of a pair of chords and the sum (difference) of another pair of chords.}} Euclidean relativity is not even a fringe theory; no physicists or astronomers have adopted it. There are many good reasons why the revolutionary leap to a four orthogonal spatial dimensions viewpoint has not been taken, beginning with the universally observed fact that we can only construct three perpendiculars through a point in our immediate space, which appears to be resolutely 3-dimensional, not 4-dimensional. Euclidean relativity offers a nice geometric explanation of the reasons for the Lorentz transformations, but only at the cost of raising other mysteries, which have been difficult for its aficionados to explain. Another mystery is how light signals between observers in relative motion could "catch up" with the receiver moving on a diverging path through 4-space from the emitter. If both observers are already moving at <math>c</math> (on diverging paths), the propagation speed of light through 4-space between them would have to be greater than <math>c</math>. Euclidean relativity is a revolutionary theory indeed, in which <math>c</math> cannot possibly be the speed of light! We conclude that, for a theory of Euclidean 4-space to be physically viable (that is, for <math>\mathbb{R}^4</math> to be our real space and not merely an abstract mathematical space), the speed of light through Euclidean 4-space must be <math>c\prime = 2c</math>, with massless photons translating through 4-space at twice the speed of mass-carrying objects. Photons must translate the diagonal distance through 4-space along the long diameter of a unit 4-hypercube, in the same time that massive particles translate inertially along the edge (or the radius) of a unit 4-hypercube. This is conceivable in Euclidean 4-space (and in no other Euclidean space of any dimensionality) because the long diagonal of the unit 4-hypercube is the natural number <math>\sqrt{4}</math>. == An object's motion in space is the product of its discrete self-reflections == Coxeter theory describes all the possible motions of an object in space as local functions of the object's discrete geometry (its shape). Coxeter observed that in a Euclidean space of any number of dimensions, any displacement of a geometric object from one place to another, and any rotation of the object from one orientation to another, can be broken down into the product of a number of discrete self-reflections. Any action of a polytope that transforms its position and orientation in space may be measured as a distinct sequence of self-reflections of the object in its own surfaces. Any motion of the object whatsoever may be precisely described as the object propagating itself through space by a discrete sequence of local self-reflections. This is a purely kinematic description of motion which does not give any account of forces acting on the object that cause it to move. Coxeter found that both changes in position (translations) and changes in orientation (rotations) can be broken down into the simplest of all displacements (self-reflections). A translation occurs when an object self-reflects twice, in two distinct surfaces which are parallel to each other. A rotation also occurs when an object self-reflects twice, but in two distinct surfaces which intersect each other. When a object self-reflects once, it turns itself inside out (it reverses its chirality), but in translations and rotations it self-reflects twice, preserving its chirality. Coxeter's laws of kinematics are a geometric counterpart to Newton's algebraic laws of motion in three dimensional Euclidean space. They are helpful because they can be understood as geometric pictures, which may help us to visualize the relationships between translation and rotation in classic Newtonian physics problems, such as the Kepler problem of the motion of the planets.<ref>{{Cite book|last=Feynman|first=Richard|title=Feynman's Lost Lecture: The Motion of Planets Around the Sun|date=1996|publisher=W. W. Norton & Company|isbn=978-0393039184}}</ref> But they are also a revolutionary advance beyond Newton's laws, because Coxeter formulated them in Euclidean spaces of any number of dimensions. In particular, they give us geometric pictures of all the possible motions of objects in 4-dimensional Euclidean space: <blockquote>Every orthogonal transformation in 4-space is expressible as:<br> :<math>\mathrm{Q}^q \mathrm{R}^r \mathrm{T}^t</math><br> where <math>(2^q + r + t \le 4)</math>. Every displacement is either a double rotation <math>\mathrm{Q}^2</math>, or a screw-displacement <math>\mathrm{QT}</math> [where the rotation component <math>\mathrm{Q}</math> is a simple rotation, but the <math>\mathrm{QT}</math> is chiral like a <math>\mathrm{Q^2}</math>]. Every enantiomorphous transformation in 4-space (reversing chirality) is a <math>\mathrm{QRT}</math>.</blockquote> While this description should be understood as geometric pictures, some of the pictures may not be easy for us to visualize, since we have no physical experience in 4-dimensional space. Rotation (<math>\mathrm{Q}</math>), reflection (<math>\mathrm{R}</math>) and translation (<math>\mathrm{T}</math>) are obvious analogues of what they are in three-dimensional space, but double rotation (<math>\mathrm{Q}^2</math>) is something new and unprecedented in our physical experience, because double rotations cannot occur until there are four or more dimensions of space in which to rotate. A point in 4-space may be in motion on two circles in two completely orthogonal rotation planes simultaneously. Nothing constrains the two circles to be of the same radius, or constrains either circle from being of infinite radius such that the point moves in a straight line within its rotation plane: a translation <math>\mathrm{T}</math> rather than a rotation <math>\mathrm{Q}</math>. The motion of a rigid object defined by multiple points is constrained by its rigidity, such that the radii of both circles may approach infinity, but only one of the two radii may actually reach infinity. Only one of the two rotations may actually be a translation. Four dimensional Euclidean space can contain no such thing as a <math>\mathrm{Q}^2\mathrm{T}</math>. A translating double rotation <math>\mathrm{Q}^2</math>, like a translating simple rotation <math>\mathrm{Q}</math>, is simply a screw translation <math>\mathrm{QT}</math>. That is the essence of the way the principle of relativity operates in Euclidean 4-space. An object which is double-rotating in its own proper inertial reference frame may be seen to be performing nothing more mysterious than a screw translation, when observed from an inertial reference frame from which the object is in relative translational motion. In a universe which is real Euclidean four-dimensional space <math>\mathbb{R}^4</math>, wherein these motions occur only at the constant velocity <math>c</math>, there is a universal Cartesian 4-coordinate reference frame in which every rigid object is translating on a <math>\mathrm{QT}</math> at velocity <math>c</math>. That universal inertial reference frame is not the proper reference frame of any object or observer, wherein the object or observer is stationary, but it is the common reference frame of all observers. == Light propagates through 4-space at twice its apparent velocity <math>c</math>== Coxeter's laws of kinematics in 4-dimensional Euclidean space apply to all objects with mass, but we find there is an additional kind of displacement which applies only to massless particles such as photons. Light quanta (photons) translate through 4-space by 4-dimensional reflection <math>\mathrm{R}^4</math>, which may be termed a double translation <math>\mathrm{T}^2</math>, a pure translation via two pairs of parallel reflections without any rotation component <math>\mathrm{Q}</math>. Matter (atoms and all particles with mass) are perpetually rotating and translating through 4-space by <math>\mathrm{QT}</math>, a screw translation of a rotating object, which is relativistically equivalent to a stationary isoclinic <math>\mathrm{Q^2}</math>, an isoclinically rotating object such as an atom. A simple rotation <math>\mathrm{Q}</math> or simple translation <math>\mathrm{T}</math> is a double reflection <math>\mathrm{R^2}</math>, so a <math>\mathrm{QT}</math> or <math>\mathrm{Q^2}</math> is an <math>\mathrm{R^4}</math>, but not with the same group of reflection angles as a light signal <math>\mathrm{R^4}</math>. A translation <math>\mathrm{T = R^2}</math> is a double reflection in two parallel planes, and a rotation <math>\mathrm{Q = R^2}</math> is a double reflection in two intersecting planes, as in a <math>\mathrm{QT = R^4}</math> which is both at once. A double translation <math>\mathrm{T^2 = R^4}</math> is two double reflections in pairs of parallel planes at once, a reflection in four non-intersecting parallel planes; it is all translation and no rotation. In a <math>\mathrm{T^2}</math> all the motion goes to translation, so the translation goes twice as far as the simple translation <math>\mathrm{T}</math> in a <math>\mathrm{QT}</math>. A double translation <math>\mathrm{T^2 = R^4}</math> is the opposite of a double rotation <math>\mathrm{Q^2 = R^4}</math>, which is stationary but rotates twice as far as the simple rotation <math>\mathrm{Q}</math> in a <math>\mathrm{QT}</math>. The product of the two translations in a <math>\mathrm{T^2}</math> is a diagonal 4-space translation over the long diameter of the unit 4-hypercube, exactly twice the distance of a simple <math>\mathrm{T}</math> over the edge length (or radius) of the unit 4-hypercube. The [[w:Tesseract|4-hypercube (also known as the 8-cell or tesseract)]] is ''radially equilateral'', which means its edge length is equal to its radius, like the hexagon, so its long diameter (twice its radius) is exactly twice its edge length. The photon moves an equal distance in four orthogonal directions. By the four-dimensional Pythagorean theorem, each of those four distances is half the total distance the photon moves: one edge length (one radius) is half the total diagonal distance moved (the long diameter). That total movement is a double-the-distance translation, but without any rotation component, so it cannot carry any mass with it. A <math>\mathrm{T^2}</math> cannot reposition a 4-polytope the way a <math>\mathrm{QT}</math> does, it can only reposition a quantum of energy that has no distinguishing rotational symmetry, such as a photon. That is the price light pays to move exactly twice as fast as matter.{{Efn| ...lensing of double translations <math>\mathrm{T^2 = R^4}</math> in more than two pairs of parallel planes at once...relationship to the frequency of light emitted and the coherence length of the wave packet...}} == Special relativity is Galilean relativity in a Euclidean space of four orthogonal dimensions == {{Efn|...TAC suggests this section is needed sooner, i.e. in the preceding Special Relativity section, as it explains how Euclidean relativity reduces special relativity to 4D perspective geometry...it's misplaced (too late) here...}} Perspective effects known as the Lorentz transformations occur because each observer's proper 3-dimensional space is a moving curved manifold embedded in flat 4-dimensional Euclidean space. The curvature of their 3-space complicates sightline calculations for observers; they sometimes require Lorentz transformations to produce the actual 4-space Cartesian coordinates of objects in the scene being observed. But if all four spatial dimensions are considered, no Lorentz transformations are required (or permitted) in correct scene construction, except when an observer wants to calculate a projection, that is, the shadow of how things will appear to them from a three-dimensional viewpoint (not how they really are).{{Sfn|Yamashita|2023}} Space really has four orthogonal dimensions, and space and time behave there just as they do in a classical vector space, only bigger by one dimension. It is not necessary to combine 4-space with time in a unified spacetime to explain 4-dimensional perspective effects at high relative velocities, because Euclidean 4-space is already 4-dimensional, and those effects fall out naturally from the 4-dimensional Pythagorean theorem, exactly as ordinary visual perspective does in three dimensions from the 3-dimensional Pythagorean theorem. Because one of the four spatial dimensions corresponds to an observer's direction of motion (in both space and proper time), and all observers and all scenes being observed are in motion (at constant velocity) in their respective proper time directions, we observe perspective foreshortenings in time as well as in a spatial dimension. In special relativity these perspective effects are reciprocal, precisely because they are only apparent, not actual, changes in size and duration. (In general relativity the actual rate of physical processes varies from place to place, and reference frame differences are neither reciprocal nor illusory.) None of these Lorentz effects are beyond geometric explanation or paradoxical. The universe is unexpectedly strange to us in precisely the ways the Euclidean fourth dimension is strange to us; but that does hold many surprises. Euclidean 4-space is much more interesting than Euclidean 3-space, analogous to the way 3-space is much more interesting and deeply explanatory to us than it would be if we experienced it only as a 2-space with many folds and curves, as perhaps an ant does. The emergent properties of 4-space are hard for us to visualize because they lie so wholly beyond our physical experience, just as it was hard for our ancestors to imagine the earth as round like a ball. However, Euclidean spaces of successive dimensions are analogous, and so higher dimensional spaces can be anticipated and explored: that is Schläfli's great discovery. Moreover dimensional analogy itself, like everything else in nature, is an exact expression of intrinsic group-theoretic symmetries: that is Nother's great discovery. == Dimensional relativity == Coxeter's kinetic law of <math>n</math>-dimensional congruent Euclidean transformations may be called ''dimensional relativity'', since it captures the theories of special and general relativity, and has its roots in dimensional analogy. Dimensional analogy is the exploration of [[w:Hermann_Grassmann#Mathematician|Hermann Grassmann's vector space principle]], in which space cannot be limited to any finite number of dimensions. The geometry of higher-dimensional space is accessable by reason of direct analogy, as [[w:Ludwig Schläfli|Ludwig Schläfli]] subsequently demonstrated. By analogy to the surface of the earth, the bounding surface of a spherical region of <math>n</math>-dimensional Euclidean space is an <math>(n-1)</math>-sphere, a spherical space of one fewer dimensions than the <math>n</math>-ball of Euclidean space it surrounds. In dimensional relativity the sky is not a ceiling, but an infinite regress of alternating spherical and Euclidean <math>n</math>-spaces of increasing <math>n</math>, accessible from each observer's point of view. By dimensional analogy, each observer looks up into their own reference frame's regress of concentric alternating <math>n</math>-spaces. By the capacity for dimensional analogy which they possess, some observers see deeper into <math>n</math>-dimensional space than others. == Polycentric spherical relativity == An intelligent observer equipped with the principle of relativity may perceive the universe from any inertial reference frame, not only from their own proper stationary reference frame in the <math>n</math>-space universe in which they physically locate themself. We see that every observer may also properly view themself as stationary and the universe as an <math>(n+1)</math>-sphere with themself at the center observing it, perceptually equidistant from all points on its <math>n</math>-space surface, including their own physical location which is one of those surface points, distinguished to them but moving on the surface, and not the center of anything. This ''polycentric model'' of the universe is a further restatement of the principle of relativity. It is compatible with Galileo's relativity of uniformly moving objects in ordinary space, Einstein's special relativity of inertial reference frames in 4-dimensional spacetime, Einstein's general relativity of all reference frames in non-Euclidean spacetime, and Coxeter's dimensional relativity of orthogonal group actions in Euclidean and spherical spaces of any number of dimensions. It should be known as Thoreau's principle of ''spherical relativity'', since the first precise written statement of it appears in 1849: "The universe is a sphere whose center is wherever there is intelligence."{{Sfn|Thoreau|1849|p=349|ps=; "The universe is a sphere whose center is wherever there is intelligence." [Contemporaneous and independent of [[W:Ludwig Schlafli|Ludwig Schlafli]]'s pioneering work enumerating the complete set of regular polyschemes in any number of dimensions.]}} == Revolutions == The original Copernican revolution in 1543 displaced the center of the universe from the center of the earth to a point farther away, the center of the sun, with the earth performing a ''revolution'' around the sun, and the stars remaining on a fixed 2-sphere around the sun instead of around the earth. But this led inevitably to the recognition that the sun must be a star itself, not equidistant from all the stars, and the center of but one of many spheres, no monotheistic center at all. In such fashion the Euclidean four-dimensional revolution, emerging three to five centuries later, initially lends itself to the big bang theory of a single origin of the whole universe, but leads inevitably to the recognition that all the galaxies need not be equidistant from a single origin in time, any more than all the stars lie in the same galaxy, equidistant from a single center in space. The expanding sphere of matter on the surface of which we find ourselves living is likely to be one of many 3-spheres expanding at velocity <math>c</math>, with their big bang origins occurring at distinct times and places in the ''n''-dimensional universe. The most distant objects we see when we look up at night may not all have the same origin in space and time. As recently as Copernicus we believed all the stars lay on a single 2-sphere embedded in Euclidean 3-space, with our sun at its center. During the enlightenment we dispersed those stars into an infinite Euclidean 3-space, and relinquished our privileged position at the center. Then Einstein showed that our 3-space could not be Euclidean, that it must be a 3-manifold curved in every place in obedience to Newton's inverse-square law of gravity; and in a geometry related to time, at least, it must be 4-dimensional. In this work we suggest a theory of ''n''-dimensional real space and how light travels in it, a theory which says we can see into four orthogonal dimensions of Euclidean space, and so when we look up at night we see cosmological objects distributed in at least four dimensions of space around us, rather than all located in our own local 3-space. Looking still deeper and farther out, the universe viewed as a 4-sphere might, or might not, be expanding, and the most distant objects we see when we look up at night may, or may not, lie in our 4-dimensional hyperplane. Real space has ''n'' dimensions as [[w:Hermann_Grassmann|Grassmann]] and [[w:Schläfli|Schläfli]] showed, and we do not know how many dimensions the most distant objects we see may be distributed in. They need not all lie within the four spatial dimensions in which we have now learned to observe them, any more than they lie in the three dimensional hyperplane of local space in which we find everything residing in our solar system. When we look up at the objects that surround us, we have no way of discerning how many dimensions beyond three the space we are looking into has. We know their distance from us primarily by virtue of how long it takes their light to reach us. We can measure their distribution around us in 3-space or 4-space, but that is simply how we choose to measure their positions, not an actual finding of how they are distributed. Even if it is now evident that they do not all lie in the same 3-space, how many more dimensions than three are needed to contain them? We observe that our 4-ball galaxy is embedded in Euclidean ''n''-space as one of many 4-ball galaxies, each translating in a distinct direction through 4-space at velocity <math>c</math>, on more or less divergent paths from each other. But only much closer observation will reveal evidence of whether everything we see lies in the same Euclidean 4-space, or if it is distributed in five or more dimensions, and how it is moving there. To remain in agreement with the theory of relativity, the Euclidean four-dimensional viewpoint requires that all mass-carrying objects be in motion in some distinct direction through 4-space at the constant velocity <math>c</math>, although the relative velocity between nearby objects is much smaller since they move on similar vectors, aimed away from a common origin point in the past. It is natural to expect that objects moving at constant velocity away from a common origin will be distributed roughly on the surface of an expanding 3-sphere. Although their paths away from their origin are not straight lines but various helical isoclines (screw translations), nearby objects must be translating radially at the same velocity, since the objects in a system (such as our solar system or galaxy) do not separate rapidly over time but remain in orbital formation. Each system's screw translation has ''two'' [[w:Completely_orthogonal|completely orthogonal]] components of motion in 4-space, an orbital rotation (such as the earth's around our sun) and a linear translation of the entire system at velocity <math>c</math> in the direction of the original 3-sphere's radial expansion (along the system's proper time vector). Of course the view from our solar system does not suggest that each galaxy's own distinct 3-sphere is expanding at this great rate from its galactic center. The standard theory has been that the entire observable universe is expanding from a single big bang origin in time, with galaxies forming later. While the Euclidean four-dimensional viewpoint lends itself to that standard theory, it also supports theories which require no single origin point in space and time. These are the voyages of starship Earth, to boldly go where no one has gone before. We made the jump to lightspeed long ago, in whatever big bang our atoms emerged from, and have never slowed down since. == Origins of the theory == Einstein himself may have been the first to imagine the universe as the three-dimensional surface of a four-dimensional Euclidean 3-sphere, in what was narrowly the first written articulation of the geometry of Euclidean 4-space relativity, contemporaneous with the teen-aged Coxeter's (quoted below).{{Efn|[[W:William Rowan Hamilton|Hamilton]]'s algebra '''H''' of [[W:Quaternions|quaternions]] contains the notion of a [[W:Three-dimensional sphere|three-dimensional sphere]] embedded in a four-dimensional space, but Hamilton did not conceive of the quaternions as the Cartesian 4-coordinates of a Euclidean 4-space, and did not describe our ordinary 3-space as embedded in Euclidean 4-space.}} Einstein did this as a [[W:Gedankenexperiment|gedankenexperiment]] in the context of investigating whether his equations of general relativity predicted an infinite or a finite universe, in his 1921 Princeton lecture.<ref>{{Cite book|url=http://www.gutenberg.org/ebooks/36276|title=The Meaning of Relativity|last=Einstein|first=Albert|publisher=Princeton University Press|year=1923|isbn=|location=|pages=110-111}}</ref> He invited us to imagine "A spherical manifold of three dimensions, embedded in a Euclidean continuum of four dimensions", but he was careful to disclaim parenthetically that "The aid of a fourth space dimension has naturally no significance except that of a mathematical artifice." Informally, the Euclidean 4-dimensional theory of relativity may be given as a sort of reciprocal to that disclaimer of Einstein's: ''The Minkowski spacetime has naturally no significance except that of a mathematical artifice, as an aid to understanding how things will appear to an observer from their perspective; the foreshortenings, clock desynchronizations and other Lorentz transformations it predicts are proper calculations of actual perspective effects; but real space is a flat, Euclidean continuum of four orthogonal spatial dimensions, and in it the ordinary laws of a flat vector space hold (such as the Pythagorean theorem), and all sightline calculations work classically, so long as you consider all four spatial dimensions.'' The Euclidean theory of relativity differs from the special theory of relativity in ascribing to the physical universe a geometry of four or more orthogonal spatial dimensions, rather than the special theory's [[w:Minkowski spacetime|Minkowski spacetime]] geometry, in which three spatial dimensions and a time dimension comprise a unified spacetime of four dimensions. Anco and Maghadam found that <math>SO(4)</math> breaks to <math>\mathbb{S}^3</math> (the 3-sphere) if the energy in the Kepler orbit is negative (an elliptical orbit), and to <math>H^3</math> (Minkowski spacetime) if the energy is positive (a hyperbolic orbit). Therefore the fact that the planets orbit on ellipses in our 3-space suggests that they orbit on a 3-sphere embedded in Euclidean 4-space which is the actual geometry of our physical universe, and Minkowski spacetime is an abstraction; the reciprocal of Einstein's disclaimer is the direct model. Of course spacetime remains a true and useful abstraction, although it must relinquish its privileged position as our exclusive conception of our place in space.{{Efn| ...origins of the Euclidean 4-space insight in the observations of Fock, Atkinson, Moser and others.}} The invention of Euclidean geometry of more than three spatial dimensions preceded Einstein's theories by more than fifty years, when it was worked out originally by the Swiss mathematician [[w:Ludwig Schläfli|Ludwig Schläfli]] before 1853.{{Sfn|Coxeter|1973|loc=§7. Ordinary Polytopes in Higher Space; §7.x. Historical remarks|pp=141-144|ps=; "Practically all the ideas in this chapter ... are due to Schläfli, who discovered them before 1853 — a time when Cayley, Grassmann and Möbius were the only other people who had ever conceived the possibility of geometry in more than three dimensions."}} Schläfli extended Euclid's geometry of one, two, and three dimensions in a direct way to four or more dimensions, generalizing the rules and terms of [[w:Euclidean geometry|Euclidean geometry]] to spaces of any number of dimensions. He coined the general term ''[[polyscheme]]'' to mean geometric forms of any number of dimensions, including two-dimensional [[w:polygon|polygons]], three-dimensional [[w:polyhedron|polyhedra]], four dimensional [[w:polychoron|polychora]], and so on, and in the process he found all of the [[w:Regular polytope|regular polyschemes]] that are possible in every dimension, including in particular the [[User:Dc.samizdat/Rotations#Sequence of regular 4-polytopes|six convex regular polychora]] which can be constructed in a Euclidean space of four dimensions (the set analogous to the five [[w:Platonic solid|Platonic solids]] the ancients found in three dimensional space). Thus Schläfli was the first to explore the fourth dimension, reveal its emergent geometric properties, and discover its astonishing regular objects. Because his work was only published posthumously in 1901, and remained almost completely unknown until Coxeter published [[w:Regular_Polytopes_(book)|Regular Polytopes]] in 1947, other researchers had more than fifty years to rediscover the regular polychora, and competing terms were coined; today [[w:Reinhold_Hoppe|Reinhold Hoppe]]'s word ''[[w:Polytope|polytope]]'' is the commonly used term for ''polyscheme.''{{Efn|[[w:Reinhold_Hoppe|Reinhold Hoppe]]'s German word ''polytop'' was introduced into English by [[W:Alicia Boole Stott|Alicia Boole Stott]], who like Hoppe and [[W:Thorold Gosset|Thorold Gosset]] rediscovered Schlafli's six regular convex 4-polytopes, with no knowledge of their prior discovery. Today Schläfli's original ''polyschem'', with its echo of ''schema'' as in the configurations of information structures, seems even more fitting in its generality than ''polytope'' -- perhaps analogously as information software (programming) is even more general than information hardware (computers).}} Because of this century-long lag in the dissemination of a scientific discovery, the regular 4-polytopes appear to have played no role at all, by any name, in the twentieth century discovery and evolution of the theories of relativity and quantum mechanics.{{Efn|One could argue that the higher-dimensional polytopes have barely influenced science or culture at all thus far. The physicist John Edward Huth's comprehensive deep dive through the history of cultural and scientific concepts of physical space, from ancient flatland models of the world through general relativity and quantum mechancs, shows exactly how we got to our present standard model of the universe, although it includes no mention of higher-dimensional Euclidean space.<ref>{{Cite book|last=Huth|first=John Edward|title=A Sense of Space: A local's guide to a flat earth, the edge of the cosmos, and other curious places|year=2025|publisher=University of Chicago Press}}</ref>}} == Boundaries == <blockquote>Ever since we discovered that Earth is round and turns like a mad-spinning top, we have understood that reality is not as it appears to us: every time we glimpse a new aspect of it, it is a deeply emotional experience. Another veil has fallen.<ref>{{Cite book|author=Carlo Rovelli|author-link=W:Carlo Rovelli|title=Seven Brief Lessons on Physics|publisher=Riverhead|year=2016|isbn=978-0399184413}}</ref></blockquote> Of course it is strange to consciously contemplate this world we inhabit, our planet, our solar system, our 3-sphere surface in our vast galaxy, as the merest film, a boundary no thicker in the places we inhabit than the diameter of an electron (though much thicker in some places we cannot inhabit, such as the interior of stars). But is not our unconscious traditional concept of the boundary of our world even stranger? Since the enlightenment we are accustomed to thinking that there is nothing beyond three dimensional space: no boundary, because there is nothing else to separate us from. But anyone who knows the [[polyscheme]]s Schläfli discovered knows that space can have any number of dimensions, and that there are fundamental objects and motions to be discovered in four dimensions that are even more various and interesting than those we can discover in three. The strange thing, when we think about it that way, is that there ''is'' a boundary between three and four dimensional space. ''Why'' can't we move (or apparently, see) in more than three dimensions? Why is our physical world apparently only three dimensional? Why would it have just ''three'' dimensions, and not four, or five, or the ''n'' dimensions that Schläfli mapped? What is the nature of the boundary which confines us to just three dimensions? We know that in Euclidean geometry the boundary between three and four dimensions is itself a spherical three dimensional space, so we should suspect that we are materially confined within such a curved boundary surface. Light need not be confined with us within our three dimensional boundary space. We would look directly through four dimensional space in our natural way, by receiving light signals that travelled through it to us on straight lines. In that case the reason we do not observe a fourth spatial dimension in our vicinity is that there are no nearby objects in it, just off our hyperplane in the wild. The nearest four-dimensional object we can see with our eyes is our sun, which lies equatorially in our own hyperplane, though it bulges out of it above and below. But when we look up at the heavens, every pinprick of light we observe is itself a four-dimensional object off our hyperplane, and they are distributed all around us in four-dimensional space through which we gaze. We are four-dimensionally sighted creatures, even though our bodies are three-dimensional objects, thin as an atom in the fourth dimension. But that should not perplex us: we can see into three dimensional space even though our retinas are two dimensional objects, thin as a photoreceptor cell. Our unconscious provincial concept is that there is nothing else outside our three dimensional world: no boundary, because there is nothing else to separate us from. But Schläfli discovered something else: all the astonishing regular objects that exist in higher dimensions, which vastly extend our notions of the beauty and mystery of space itself, and the intrinsic spatial symmetries of our universe which geometry reveals. Space is more commodious than we thought it was, and permits previously unimagined objects and motions. So our provincial conception of our place in it now has the same kind of status as our idea that the sun rises in the east and passes overhead: it is mere appearance, not a true model and no longer a proper explanation. An inertial boundary is an explanation, be it ever so thin. And would a boundary of ''no'' thickness, a mere abstraction with no physical power to separate, be a more suitable explanation? We must look for a physically powerful explanation in the geometry of space itself, which general relativity properly associates with the gravitational or inertial force. <blockquote>The number of dimensions possessed by a figure is the number of straight lines each perpendicular to all the others which can be drawn on it. Thus a point has no dimensions, a straight line one, a plane surface two, and a solid three .... In space as we now know it only three lines can be imagined perpendicular to each other. A fourth line, perpendicular to all the other three would be quite invisible and unimaginable to us. We ourselves and all the material things around us probably possess a fourth dimension, of which we are quite unaware. If not, from a four-dimensional point of view we are mere geometrical abstractions, like geometrical surfaces, lines, and points are to us. But this thickness in the fourth dimension must be exceedingly minute, if it exists at all. That is, we could only draw an exceedingly small line perpendicular to our three perpendicular lines, length, breadth and thickness, so small that no microscope could ever perceive it. We can find out something about the conditions of the fourth and higher dimensions if they exist, without being certain that they do exist, by a process which I have termed "Dimensional Analogy."<ref>{{Citation|title=Dimensional Analogy|last=Coxeter|first=Donald|date=February 1923|publisher=Coxeter Fonds, University of Toronto Archives|authorlink=W:Harold Scott MacDonald Coxeter|series=|postscript=|work=}}</ref></blockquote> I believe, but I cannot prove, that we live in real space, which is Schläfli's Euclidean space of ''n'' analogous dimensions. As Grassmann showed first, space cannot be limited to any finite number of dimensions. There will always be higher dimensions to discover, first in imagination and then to explore physically, each an astonishing new enlightenment.<ref>{{Cite book|first=T.S.|last=Eliot|title=Little Gidding|volume=Four Quartets|year=1943}}<blockquote> :We shall not cease from exploration :And the end of all our exploring :Will be to arrive where we started :And know the place for the first time. :Through the unknown, remembered gate :When the last of earth left to discover :Is that which was the beginning; :At the source of the longest river :The voice of the hidden waterfall :And the children in the apple-tree :Not known, because not looked for :But heard, half-heard, in the stillness :Between two waves of the sea. </blockquote></ref> Schläfli discovered every regular convex polytope that exists in any dimension, but that was only the beginning of the story of dimensional analogy, not its end or even the end of its beginning. That project is forever beginning anew. Coxeter discovered that Schläfli's Euclidean space is an expression of intrinsic symmetries, as Noether discovered all of physics is. Kappraff and Adamson discovered that even the sequences of humble regular polygons have fractal complexity. Symmetry itself is chaotic, always reachable but forever beyond our complete grasp. We are on a Wilderness Project, and just at its beginning, but already we observe a Euclidean space of four or more orthogonal spatial dimensions in which all objects with mass move ceaselessly at the constant velocity <math>c</math>, the universal rate at which everything moves, quantum events occur, and each of our proper times evolves. I believe these facts explain the experimentally verified theories of relativity and quantum mechanics, by revealing their unified polycentric geometry, the same way the facts about Copernicus's heliocentric solar system explained the observed motions of the planets, by revealing the geometry of gravity. But others will have to do the math, work out the physics, and perform experiments to prove or disprove all of this, because I don't have the mathematics; entirely unlike Coxeter and Einstein, I am illiterate in those languages. <blockquote> ::::::BEECH :Where my imaginary line :Bends square in woods, an iron spine :And pile of real rocks have been founded. :And off this corner in the wild, :Where these are driven in and piled, :One tree, by being deeply wounded, :Has been impressed as Witness Tree :And made commit to memory :My proof of being not unbounded. :Thus truth's established and borne out, :Though circumstanced with dark and doubt— :Though by a world of doubt surrounded. :::::::—''The Moodie Forester''<ref>{{Cite book|title=A Witness Tree|last=Frost|first=Robert|year=1942|series=The Poetry of Robert Frost|publisher=Holt, Rinehart and Winston|edition=1969|}}</ref> </blockquote> == Appendix: Sequence of regular 4-polytopes == {{Regular convex 4-polytopes|wiki=W:|columns=7}} == ... == {{Efn|In a ''[[W:William Kingdon Clifford|Clifford]] displacement'', also known as an [[W:Rotations in 4-dimensional Euclidean space#Isoclinic rotations|isoclinic rotation]], all the Clifford parallel{{Efn|name=Clifford parallels}} invariant planes are displaced in four orthogonal directions (two completely orthogonal planes) at once: they are rotated by the same angle, and at the same time they are tilted ''sideways'' by that same angle. A [[W:Rotations in 4-dimensional Euclidean space#Isoclinic rotations|Clifford displacement]] is [[W:8-cell#Radial equilateral symmetry|4-dimensionally diagonal]].{{Efn|name=isoclinic 4-dimensional diagonal}} Every plane that is Clifford parallel to one of the completely orthogonal planes (including in this case an entire Clifford parallel bundle of 4 hexagons, but not all 16 hexagons) is invariant under the isoclinic rotation: all the points in the plane rotate in circles but remain in the plane, even as the whole plane tilts sideways. All 16 hexagons rotate by the same angle (though only 4 of them do so invariantly). All 16 hexagons are rotated by 60 degrees, and also displaced sideways by 60 degrees to a Clifford parallel hexagon. All of the other central polygons (e.g. squares) are also displaced to a Clifford parallel polygon 60 degrees away.|name=Clifford displacement}} {{Efn|It is not difficult to visualize four hexagonal planes intersecting at 60 degrees to each other, even in three dimensions. Four hexagonal central planes intersect at 60 degrees in the [[W:cuboctahedron|cuboctahedron]]. Four of the 24-cell's 16 hexagonal central planes (lying in the same 3-dimensional hyperplane) intersect at each of the 24-cell's vertices exactly the way they do at the center of a cuboctahedron. But the ''edges'' around the vertex do not meet as the radii do at the center of a cuboctahedron; the 24-cell has 8 edges around each vertex, not 12, so its vertex figure is the cube, not the cuboctahedron. The 8 edges meet exactly the way 8 edges do at the apex of a canonical [[W:cubic pyramid]|cubic pyramid]].{{Efn|name=24-cell vertex figure}}|name=cuboctahedral hexagons}} {{Efn|name=radially equilateral}} {{Efn|Eight {{sqrt|1}} edges converge in curved 3-dimensional space from the corners of the 24-cell's cubical vertex figure{{Efn|The [[W:vertex figure|vertex figure]] is the facet which is made by truncating a vertex; canonically, at the mid-edges incident to the vertex. But one can make similar vertex figures of different radii by truncating at any point along those edges, up to and including truncating at the adjacent vertices to make a ''full size'' vertex figure. Stillwell defines the vertex figure as "the convex hull of the neighbouring vertices of a given vertex".{{Sfn|Stillwell|2001|p=17}} That is what serves the illustrative purpose here.|name=full size vertex figure}} and meet at its center (the vertex), where they form 4 straight lines which cross there. The 8 vertices of the cube are the eight nearest other vertices of the 24-cell. The straight lines are geodesics: two {{sqrt|1}}-length segments of an apparently straight line (in the 3-space of the 24-cell's curved surface) that is bent in the 4th dimension into a great circle hexagon (in 4-space). Imagined from inside this curved 3-space, the bends in the hexagons are invisible. From outside (if we could view the 24-cell in 4-space), the straight lines would be seen to bend in the 4th dimension at the cube centers, because the center is displaced outward in the 4th dimension, out of the hyperplane defined by the cube's vertices. Thus the vertex cube is actually a [[W:cubic pyramid|cubic pyramid]]. Unlike a cube, it seems to be radially equilateral (like the tesseract and the 24-cell itself): its "radius" equals its edge length.{{Efn|The vertex cubic pyramid is not actually radially equilateral,{{Efn|name=radially equilateral}} because the edges radiating from its apex are not actually its radii: the apex of the [[W:cubic pyramid|cubic pyramid]] is not actually its center, just one of its vertices.}}|name=24-cell vertex figure}} {{Efn|The hexagons are inclined (tilted) at 60 degrees with respect to the unit radius coordinate system's orthogonal planes. Each hexagonal plane contains only ''one'' of the 4 coordinate system axes.{{Efn|Each great hexagon of the 24-cell contains one axis (one pair of antipodal vertices) belonging to each of the three inscribed 16-cells. The 24-cell contains three disjoint inscribed 16-cells, rotated 60° isoclinically{{Efn|name=isoclinic 4-dimensional diagonal}} with respect to each other (so their corresponding vertices are 120° {{=}} {{radic|3}} apart). A [[16-cell#Coordinates|16-cell is an orthonormal ''basis'']] for a 4-dimensional coordinate system, because its 8 vertices define the four orthogonal axes. In any choice of a vertex-up coordinate system (such as the unit radius coordinates used in this article), one of the three inscribed 16-cells is the basis for the coordinate system, and each hexagon has only ''one'' axis which is a coordinate system axis.|name=three basis 16-cells}} The hexagon consists of 3 pairs of opposite vertices (three 24-cell diameters): one opposite pair of ''integer'' coordinate vertices (one of the four coordinate axes), and two opposite pairs of ''half-integer'' coordinate vertices (not coordinate axes). For example: {{indent|17}}({{spaces|2}}0,{{spaces|2}}0,{{spaces|2}}1,{{spaces|2}}0) {{indent|5}}({{spaces|2}}{{sfrac|1|2}},–{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},–{{sfrac|1|2}}){{spaces|3}}({{spaces|2}}{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}}) {{indent|5}}(–{{sfrac|1|2}},–{{sfrac|1|2}},–{{sfrac|1|2}},–{{sfrac|1|2}}){{spaces|3}}(–{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}},–{{sfrac|1|2}},{{spaces|2}}{{sfrac|1|2}}) {{indent|17}}({{spaces|2}}0,{{spaces|2}}0,–1,{{spaces|2}}0)<br> is a hexagon on the ''y'' axis. Unlike the {{sqrt|2}} squares, the hexagons are actually made of 24-cell edges, so they are visible features of the 24-cell.|name=non-orthogonal hexagons|group=}} {{Efn|Visualize the three [[16-cell]]s inscribed in the 24-cell (left, right, and middle), and the rotation which takes them to each other. [[24-cell#Reciprocal constructions from 8-cell and 16-cell|The vertices of the middle 16-cell lie on the (w, x, y, z) coordinate axes]];{{Efn|name=six orthogonal planes of the Cartesian basis}} the other two are rotated 60° [[W:Rotations in 4-dimensional Euclidean space#Isoclinic rotations|isoclinically]] to its left and its right. The 24-vertex 24-cell is a compound of three 16-cells, whose three sets of 8 vertices are distributed around the 24-cell symmetrically; each vertex is surrounded by 8 others (in the 3-dimensional space of the 4-dimensional 24-cell's ''surface''), the way the vertices of a cube surround its center.{{Efn|name=24-cell vertex figure}} The 8 surrounding vertices (the cube corners) lie in other 16-cells: 4 in the other 16-cell to the left, and 4 in the other 16-cell to the right. They are the vertices of two tetrahedra inscribed in the cube, one belonging (as a cell) to each 16-cell. If the 16-cell edges are {{radic|2}}, each vertex of the compound of three 16-cells is {{radic|1}} away from its 8 surrounding vertices in other 16-cells. Now visualize those {{radic|1}} distances as the edges of the 24-cell (while continuing to visualize the disjoint 16-cells). The {{radic|1}} edges form great hexagons of 6 vertices which run around the 24-cell in a central plane. ''Four'' hexagons cross at each vertex (and its antipodal vertex), inclined at 60° to each other.{{Efn|name=cuboctahedral hexagons}} The [[24-cell#Hexagons|hexagons]] are not perpendicular to each other, or to the 16-cells' perpendicular [[24-cell#Squares|square central planes]].{{Efn|name=non-orthogonal hexagons}} The left and right 16-cells form a tesseract.{{Efn|Each pair of the three 16-cells inscribed in the 24-cell forms a 4-dimensional [[W:tesseract|hypercube (a tesseract or 8-cell)]], in [[24-cell#Relationships among interior polytopes|dimensional analogy]] to the way two tetrahedra form a cube: the two 8-vertex 16-cells are inscribed in the 16-vertex tesseract, occupying its alternate vertices. The third 16-cell does not lie within the tesseract; its 8 vertices protrude from the sides of the tesseract, forming a cubic pyramid on each of the tesseract's cubic cells. The three pairs of 16-cells form three tesseracts.{{Efn|name=three 8-cells}} The tesseracts share vertices, but the 16-cells are completely disjoint.{{Efn|name=completely disjoint}}|name=three 16-cells form three tesseracts}} Two 16-cells have vertex-pairs which are one {{radic|1}} edge (one hexagon edge) apart. But a [[24-cell#Simple rotations|''simple'' rotation]] of 60° will not take one whole 16-cell to another 16-cell, because their vertices are 60° apart in different directions, and a simple rotation has only one hexagonal plane of rotation. One 16-cell ''can'' be taken to another 16-cell by a 60° [[24-cell#Isoclinic rotations|''isoclinic'' rotation]], because an isoclinic rotation is [[3-sphere]] symmetric: four [[24-cell#Clifford parallel polytopes|Clifford parallel hexagonal planes]] rotate together, but in four different rotational directions,{{Efn|name=Clifford displacement}} taking each 16-cell to another 16-cell. But since an isoclinic 60° rotation is a ''diagonal'' rotation by 60° in ''two'' completely orthogonal directions at once,{{Efn|name=isoclinic geodesic}} the corresponding vertices of the 16-cell and the 16-cell it is taken to are 120° apart: ''two'' {{radic|1}} hexagon edges (or one {{radic|3}} hexagon chord) apart, not one {{radic|1}} edge (60°) apart as in a simple rotation.{{Efn|name=isoclinic 4-dimensional diagonal}} By the [[W:chiral|chiral]] diagonal nature of isoclinic rotations, the 16-cell ''cannot'' reach the adjacent 16-cell by rotating toward it; it can only reach the 16-cell ''beyond'' it. But of course, the 16-cell beyond the 16-cell to its right is the 16-cell to its left. So a 60° isoclinic rotation ''will'' take every 16-cell to another 16-cell: a 60° ''right'' isoclinic rotation will take the middle 16-cell to the 16-cell we may have originally visualized as the ''left'' 16-cell, and a 60° ''left'' isoclinic rotation will take the middle 16-cell to the 16-cell we visualized as the ''right'' 16-cell. (If so, that was our error in visualization; the 16-cell to the "left" is in fact the one reached by the left isoclinic rotation, as that is the only sense in which the two 16-cells are left or right of each other.)|name=three isoclinic 16-cells}} {{Efn|In a double rotation each vertex can be said to move along two completely orthogonal great circles at the same time, but it does not stay within the central plane of either of those original great circles; rather, it moves along a helical geodesic that traverses diagonally between great circles. The two completely orthogonal planes of rotation are said to be ''invariant'' because the points in each stay in the plane ''as the plane moves'', tilting sideways by the same angle that the other plane rotates.|name=helical geodesic}} {{Efn|A point under isoclinic rotation traverses the diagonal{{Efn|name=isoclinic 4-dimensional diagonal}} straight line of a single '''isoclinic geodesic''', reaching its destination directly, instead of the bent line of two successive '''simple geodesics'''. A '''[[W:geodesic|geodesic]]''' is the ''shortest path'' through a space (intuitively, a string pulled taught between two points). Simple geodesics are great circles lying in a central plane (the only kind of geodesics that occur in 3-space on the 2-sphere). Isoclinic geodesics are different: they do ''not'' lie in a single plane; they are 4-dimensional [[W:helix|spirals]] rather than simple 2-dimensional circles.{{Efn|name=helical geodesic}} But they are not like 3-dimensional [[W:screw threads|screw threads]] either, because they form a closed loop like any circle (after ''two'' revolutions). Isoclinic geodesics are ''4-dimensional great circles'', and they are just as circular as 2-dimensional circles: in fact, twice as circular, because they curve in a circle in two completely orthogonal directions at once.{{Efn|Isoclinic geodesics are ''4-dimensional great circles'' in the sense that they are 1-dimensional geodesic ''lines'' that curve in 4-space in two completely orthogonal planes at once. They should not be confused with ''great 2-spheres'',{{Sfn|Stillwell|2001|p=24}} which are the 4-dimensional analogues of 2-dimensional great circles (great 1-spheres).}} These '''isoclines''' are geodesic 1-dimensional lines embedded in a 4-dimensional space. On the 3-sphere{{Efn|All isoclines are geodesics, and isoclines on the 3-sphere are circles (curving equally in each dimension), but not all isoclines on 3-manifolds in 4-space are circles.}} they always occur in [[W:chiral|chiral]] pairs and form a pair of [[W:Villarceau circle|Villarceau circle]]s on the [[W:Clifford torus|Clifford torus]],{{Efn|Isoclines on the 3-sphere occur in non-intersecting chiral pairs. A left and a right isocline form a [[W:Hopf link|Hopf link]] called the {1,1} torus knot{{Sfn|Dorst|2019|loc=§1. Villarceau Circles|p=44|ps=; "In mathematics, the path that the (1, 1) knot on the torus traces is also known as a [[W:Villarceau circle|Villarceau circle]]. Villarceau circles are usually introduced as two intersecting circles that are the cross-section of a torus by a well-chosen plane cutting it. Picking one such circle and rotating it around the torus axis, the resulting family of circles can be used to rule the torus. By nesting tori smartly, the collection of all such circles then form a [[W:Hopf fibration|Hopf fibration]].... we prefer to consider the Villarceau circle as the (1, 1) torus knot [a [[W:Hopf link|Hopf link]]] rather than as a planar cut [two intersecting circles]."}} in which ''each'' of the two linked circles traverses all four dimensions.}} the paths of the left and the right [[W:Rotations in 4-dimensional Euclidean space#Double rotations|isoclinic rotation]]. They are [[W:Helix|helices]] bent into a [[W:Möbius strip|Möbius loop]] in the fourth dimension, taking a diagonal [[W:Winding number|winding route]] twice around the 3-sphere through the non-adjacent vertices of a 4-polytope's [[W:Skew polygon#Regular skew polygons in four dimensions|skew polygon]].|name=isoclinic geodesic}} {{Efn|[[File:Hopf band wikipedia.png|thumb|150px|Two [[W:Clifford parallel|Clifford parallel]] great circles spanned by a twisted [[W:Annulus (mathematics)|annulus]].]][[W:Clifford parallel|Clifford parallel]]s are non-intersecting curved lines that are parallel in the sense that the perpendicular (shortest) distance between them is the same at each point. A double helix is an example of Clifford parallelism in ordinary 3-dimensional Euclidean space. In 4-space Clifford parallels occur as geodesic great circles on the [[W:3-sphere|3-sphere]].{{Sfn|Kim|Rote|2016|pp=8-10|loc=Relations to Clifford Parallelism}} Whereas in 3-dimensional space, any two geodesic great circles on the [[W:2-sphere|2-sphere]] will always intersect at two antipodal points, in 4-dimensional space not all great circles intersect. In 4-polytopes various discrete sets of Clifford parallel non-intersecting geodesic great circles can be found on the 3-sphere. They spiral around each other in [[W:Hopf fibration|Hopf fiber bundles]] which visit all the vertices just once. The simplest example is that six mutually orthogonal great circles can be drawn on the 3-sphere, as three pairs of completely orthogonal great circles, intersecting at 8 points defining a [[16-cell]]. Each completely orthogonal pair of circles is Clifford parallel. They cannot intersect at all, because they lie in planes which intersect at only one point: the center of the 16-cell. Because they are perpendicular and share a common center, the two circles are obviously not parallel and separate in the usual way of parallel circles in 3 dimensions; rather they are connected like adjacent links in a chain, each passing through the other without intersecting at any points, forming a [[W:Hopf link|Hopf link]]|name=Clifford parallels}} {{Efn|In the 24-cell each great square plane is completely orthogonal{{Efn|name=completely orthogonal planes}} to another great square plane, and each great hexagon plane is completely orthogonal to a plane which intersects only two vertices: a great [[W:digon|digon]] plane.|name=pairs of completely orthogonal planes}} {{Efn|In an [[24-cell#Isoclinic rotations|isoclinic rotation]], each point anywhere in the 4-polytope moves an equal distance in four orthogonal directions at once, on a [[W:8-cell#Radial equilateral symmetry|4-dimensional diagonal]]. The point is displaced a total [[W:Pythagorean distance]] equal to the square root of four times the square of that distance. For example, when the unit-radius 24-cell rotates isoclinically 60° in a hexagon invariant plane and 60° in its completely orthogonal invariant plane,{{Efn|name=pairs of completely orthogonal planes}} all vertices are displaced to a vertex two edge lengths away. Each vertex is displaced to another vertex {{radic|3}} (120°) away, moving {{radic|3/4}} in four orthogonal coordinate directions.|name=isoclinic 4-dimensional diagonal}} {{Efn|Each square plane is isoclinic (Clifford parallel) to five other square planes but completely orthogonal{{Efn|name=completely orthogonal planes}} to only one of them.{{Efn|name=Clifford parallel squares in the 16-cell and 24-cell}} Every pair of completely orthogonal planes has Clifford parallel great circles, but not all Clifford parallel great circles are orthogonal (e.g., none of the hexagonal geodesics in the 24-cell are mutually orthogonal).|name=only some Clifford parallels are orthogonal}} {{Efn|In the [[16-cell#Rotations|16-cell]] the 6 orthogonal great squares form 3 pairs of completely orthogonal great circles; each pair is Clifford parallel. In the 24-cell, the 3 inscribed 16-cells lie rotated 60 degrees isoclinically{{Efn|name=isoclinic 4-dimensional diagonal}} with respect to each other; consequently their corresponding vertices are 120 degrees apart on a hexagonal great circle. Pairing their vertices which are 90 degrees apart reveals corresponding square great circles which are Clifford parallel. Each of the 18 square great circles is Clifford parallel not only to one other square great circle in the same 16-cell (the completely orthogonal one), but also to two square great circles (which are completely orthogonal to each other) in each of the other two 16-cells. (Completely orthogonal great circles are Clifford parallel, but not all Clifford parallels are orthogonal.{{Efn|name=only some Clifford parallels are orthogonal}}) A 60 degree isoclinic rotation of the 24-cell in hexagonal invariant planes takes each square great circle to a Clifford parallel (but non-orthogonal) square great circle in a different 16-cell.|name=Clifford parallel squares in the 16-cell and 24-cell}} {{Efn|In 4 dimensional space we can construct 4 perpendicular axes and 6 perpendicular planes through a point. Without loss of generality, we may take these to be the axes and orthogonal central planes of a (w, x, y, z) Cartesian coordinate system. In 4 dimensions we have the same 3 orthogonal planes (xy, xz, yz) that we have in 3 dimensions, and also 3 others (wx, wy, wz). Each of the 6 orthogonal planes shares an axis with 4 of the others, and is ''completely orthogonal'' to just one of the others: the only one with which it does not share an axis. Thus there are 3 pairs of completely orthogonal planes: xy and wz intersect only at the origin; xz and wy intersect only at the origin; yz and wx intersect only at the origin.|name=six orthogonal planes of the Cartesian basis}} {{Efn|Two planes in 4-dimensional space can have four possible reciprocal positions: (1) they can coincide (be exactly the same plane); (2) they can be parallel (the only way they can fail to intersect at all); (3) they can intersect in a single line, as two non-parallel planes do in 3-dimensional space; or (4) '''they can intersect in a single point'''{{Efn|To visualize how two planes can intersect in a single point in a four dimensional space, consider the Euclidean space (w, x, y, z) and imagine that the w dimension represents time rather than a spatial dimension. The xy central plane (where w{{=}}0, z{{=}}0) shares no axis with the wz central plane (where x{{=}}0, y{{=}}0). The xy plane exists at only a single instant in time (w{{=}}0); the wz plane (and in particular the w axis) exists all the time. Thus their only moment and place of intersection is at the origin point (0,0,0,0).|name=how planes intersect at a single point}} (and they ''must'', if they are completely orthogonal).{{Efn|Two flat planes A and B of a Euclidean space of four dimensions are called ''completely orthogonal'' if and only if every line in A is orthogonal to every line in B. In that case the planes A and B intersect at a single point O, so that if a line in A intersects with a line in B, they intersect at O.{{Efn|name=six orthogonal planes of the Cartesian basis}}|name=completely orthogonal planes}}|name=how planes intersect}} {{Efn|Polytopes are '''completely disjoint''' if all their ''element sets'' are disjoint: they do not share any vertices, edges, faces or cells. They may still overlap in space, sharing 4-content, volume, area, or lineage.|name=completely disjoint}} {{Efn|If the [[W:Euclidean distance|Pythagorean distance]] between any two vertices is {{sqrt|1}}, their geodesic distance is 1; they may be two adjacent vertices (in the curved 3-space of the surface), or a vertex and the center (in 4-space). If their Pythagorean distance is {{sqrt|2}}, their geodesic distance is 2 (whether via 3-space or 4-space, because the path along the edges is the same straight line with one 90^o bend in it as the path through the center). If their Pythagorean distance is {{sqrt|3}}, their geodesic distance is still 2 (whether on a hexagonal great circle past one 60^o bend, or as a straight line with one 60^o bend in it through the center). Finally, if their Pythagorean distance is {{sqrt|4}}, their geodesic distance is still 2 in 4-space (straight through the center), but it reaches 3 in 3-space (by going halfway around a hexagonal great circle).|name=Geodesic distance}} {{Efn|Two angles are required to fix the relative positions of two planes in 4-space.{{Sfn|Kim|Rote|2016|p=7|loc=§6 Angles between two Planes in 4-Space|ps=; "In four (and higher) dimensions, we need two angles to fix the relative position between two planes. (More generally, ''k'' angles are defined between ''k''-dimensional subspaces.)"}} Since all planes in the same [[W:hyperplane|hyperplane]] are 0 degrees apart in one of the two angles, only one angle is required in 3-space. Great hexagons in different hyperplanes are 60 degrees apart in ''both'' angles. Great squares in different hyperplanes are 90 degrees apart in ''both'' angles (completely orthogonal){{Efn|name=completely orthogonal planes}} or 60 degrees apart in ''both'' angles.{{Efn||name=Clifford parallel squares in the 16-cell and 24-cell}} Planes which are separated by two equal angles are called ''isoclinic''. Planes which are isoclinic have [[W:Clifford parallel|Clifford parallel]] great circles.{{Efn|name=Clifford parallels}} A great square and a great hexagon in different hyperplanes are neither isoclinic nor Clifford parallel; they are separated by a 90 degree angle ''and'' a 60 degree angle.|name=two angles between central planes}} {{Efn|The 24-cell contains 3 distinct 8-cells (tesseracts), rotated 60° isoclinically with respect to each other. The corresponding vertices of two 8-cells are {{radic|3}} (120°) apart. Each 8-cell contains 8 cubical cells, and each cube contains four {{radic|3}} chords (its long diagonals). The 8-cells are not completely disjoint{{Efn|name=completely disjoint}} (they share vertices), but each cube and each {{radic|3}} chord belongs to just one 8-cell. The {{radic|3}} chords joining the corresponding vertices of two 8-cells belong to the third 8-cell.|name=three 8-cells}} {{Efn|Departing from any vertex V₀ in the original great hexagon plane of isoclinic rotation P₀, the first vertex reached V₁ is 120 degrees away along a {{radic|3}} chord lying in a different hexagonal plane P₁. P₁ is inclined to P₀ at a 60° angle.{{Efn|P₀ and P₁ lie in the same hyperplane (the same central cuboctahedron) so their other angle of separation is 0.{{Efn|name=two angles between central planes}}}} The second vertex reached V₂ is 120 degrees beyond V₁ along a second {{radic|3}} chord lying in another hexagonal plane P₂ that is Clifford parallel to P₀.{{Efn|P₀ and P₂ are 60° apart in ''both'' angles of separation.{{Efn|name=two angles between central planes}} Clifford parallel planes are isoclinic (which means they are separated by two equal angles), and their corresponding vertices are all the same distance apart. Although V₀ and V₂ are ''two'' {{radic|3}} chords apart{{Efn|V₀ and V₂ are two {{radic|3}} chords apart on the geodesic path of this rotational isocline, but that is not the shortest geodesic path between them. In the 24-cell, it is impossible for two vertices to be more distant than ''one'' {{radic|3}} chord, unless they are antipodal vertices {{radic|4}} apart.{{Efn|name=Geodesic distance}} V₀ and V₂ are ''one'' {{radic|3}} chord apart on some other isocline. More generally, isoclines are geodesics because the distance between their ''adjacent'' vertices is the shortest distance between those two vertices, but a path between two vertices along a geodesic is not always the shortest distance between them (even on ordinary great circle geodesics).}}, P₀ and P₂ are just one {{radic|1}} edge apart (at every pair of ''nearest'' vertices).}} (Notice that V₁ lies in both intersecting planes P₁ and P₂, as V₀ lies in both P₀ and P₁. But P₀ and P₂ have ''no'' vertices in common; they do not intersect.) The third vertex reached V₃ is 120 degrees beyond V₂ along a third {{radic|3}} chord lying in another hexagonal plane P₃ that is Clifford parallel to P₁. The three {{radic|3}} chords lie in different 8-cells.{{Efn|name=three 8-cells}} V₀ to V₃ is a 360° isoclinic rotation.|name=360 degree geodesic path visiting 3 hexagonal planes}} {{Sfn|Mamone, Pileio & Levitt|2010|loc=§4.5 Regular Convex 4-Polytopes|pp=1438-1439|ps=; the 24-cell has 1152 symmetry operations (rotations and reflections) as enumerated in Table 2, symmetry group 𝐹₄.}} ==Notes== {{Regular convex 4-polytopes Notelist|wiki=W:}} ==Citations== {{Regular convex 4-polytopes Reflist|wiki=W:}} ==References== {{Refbegin}} * {{Cite book|title=A Week on the Concord and Merrimack Rivers|last=Thoreau|first=Henry David|author-link=W:Thoreau|publisher=James Munroe and Company|year=1849|isbn=|location=Boston|ref={{SfnRef|Thoreau|1849}}}} * {{Cite journal|title=Theoretical Evidence for Principles of Special Relativity Based on Isotropic and Uniform Four-Dimensional Space|first=Takuya|last=Yamashita|date=25 May 2023|doi= 10.20944/preprints202305.1785.v1|journal=Preprints|volume=2023|issue=2023051785|url=https://doi.org/10.20944/preprints202305.1785.v1}} * {{Cite_arXiv | arxiv=2512.02903v2 | date=2 January 2026 | title=Symmetry transformation group arising from the Laplace–Runge–Lenz vector | first1=Stephen C. | last1=Anco | first2=Mahdieh Gol Bashmani | last2=Moghadam | class=math-ph}} === [[Polyscheme|Polyschemes]] === {{Regular convex 4-polytopes Refs|wiki=W:}} {{Refend}} 53wilt9edmjp4cp2whip1q1zvafjro3 0 298645 2835234 2693265 2026-09-30T23:31:17Z U3230003 2967543 2835234 wikitext text/x-wiki {{title|Overchoice and motivation:<br>What is the overchoice effect, why does it occur, and who are most susceptible to it? }} {{MECR3|1=}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Far, far too much choice, Ballyvaughan-Baile ui Bheachain - geograph.org.uk - 1268283.jpg|thumb|187px|'''Figure 1'''. Excess choice can be overwhelming]] ; Have you ever... Have you ever been in a situation where you needed to make a choice but there were so many options you just couldn’t decide? Maybe you were picking a topic for a school assignment, or what movie to watch, or which career path to take? Choices are everywhere, and when you have too many options, it can become overwhelming and produce unwanted consequences. This is known as the overchoice effect (Scheibehenne et al., 2010; see Figure 1). {{RoundBoxBottom}} The overchoice effect is an important area of research in motivational psychology, as excessive options can disrupt people’s ability to make decisions – costing them time, energy, and ultimately reducing their satisfaction with their choices (Chernev et al., 2015). Since decision-making is a fundamental part of human behaviour, research on the effects of assortment size on motivation has extensive practical applicability, especially in marketing and educational contexts (Iyengar & Lepper, 2000). This chapter uses psychological science to explore key aspects of the overchoice effect – including the defining features of the overchoice effect, the mechanisms behind this phenomenon, and how personal characteristics can increase people’s susceptibility to its effects. {{RoundBoxTop|theme=3}} ;Focus questions: * What is the overchoice effect? * Why does the overchoice effect occur? * Who is most susceptible to the overchoice effect? {{RoundBoxBottom}} ==What is the overchoice effect? == The term, ''overchoice'' was first coined by Alvin Toffler in the 1970s; it was used to predict a future in which an abundance of choice would prevent people from making optimal decisions (Gourville & Soman, 2005).The overchoice effect (also known as choice overload), describes a phenomenon in which people experience various negative consequences, such as demotivation and decreased choice satisfaction, when they are required to choose from many options (Scheibehenne et al., 2010). Whilst the presence of a large choice set is a necessary precondition of the overchoice effect, more choices does not necessarily mean negative effects are inevitable (Scheibehenne et al., 2010). In fact, perceived choice deprivation is a more reliable predictor of decreased choice satisfaction than perceived choice excess (Reutskaja et al., 2022). Based on previous research, Chernev et al. (2015) developed a conceptual model of choice overload, which explains that the effect of assortment size on the overchoice effect is moderated by characteristics of both decisions (extrinsic factors) and decision makers (intrinsic factors). That is, certain factors related to a choice can increase or decrease the extent to which overchoice produces negative emotional and behavioural consequences{{gr}}. These factors are presented in Table 1. '''Table 1''' ''Antecedent Factors of Choice Overload'' {| class="wikitable" style="margin: auto;" |- ! Antecedent factor !! Description |- | Decision task difficulty || Factors which make choices more effortful and taxing (e.g., time constraints, decision accountability, presentation format). |- | Choice set complexity || How the features of the options within a choice set are related to each other (e.g., a lack of differentiation between options). |- |Preference uncertainty |Extent to which decision makers have preferences and feel knowledgeable about the choice being made. |- |Decision goal |The level of cognitive effort involved in the decision-making process (e.g., intention to make a decision, rather than just browse options). |} ''Note''. Adapted from Chernev et al. (2015) === Intrinsic motivation === Many dominant perspectives in psychology subscribe to the idea that providing choice is essential for promoting [[Motivation and emotion/Book/2013/Intrinsic motivation|''intrinsic motivation'']], a person’s motivation to engage in behaviours solely because they find it enjoyable (Patall et al., 2008). According to [[Motivation and emotion/Book/2011/Self-determination theory|self-determination theory]], the basic human needs for competence, relatedness, and autonomy lay the foundations for intrinsic motivation (Ryan & Deci, 2000). Since choice allows for greater autonomy, it may be considered that more choices would increase intrinsic motivation. However, the overchoice effect contradicts this assumption. In a famous study of overchoice by Iyengar and Lepper (2000), students were presented with a list of either six or 30 essay topics for an extra credit assessment. It was found that students in the limited-choice condition were more likely to successfully choose a topic and complete the essay. These students also received, on average, higher essay marks than those who selected their topic from an extensive list. Since all students were informed that their essay would not be graded, the higher quality of essays produced by the limited-choice group was suggested to reflect higher intrinsic motivation. These findings demonstrate that excessive choice may have demotivating effects. Although, since the study did not include a medium-size choice condition, it is not clear whether overchoice decreased intrinsic motivation or if limited choice increased intrinsic motivation. === Decision paralysis === Overchoice may also result in [[wikipedia:Analysis_paralysis|''decision paralysis'']], a phenomenon in which decision makers experience impaired or inhibited decision-making (Manolică et al., 2021). This concept is similar to what Chernev et al. (2015) describes as ''choice deferral'', which is when people postpone making a decision. Decision makers may struggle to commit to a choice when choosing among many options, due to factors such as overthinking (Manolică et al., 2021). This can cause people to become stuck or "paralysed" in the decision-making process. In one of Iyengar and Lepper’s (2000) experiments, it was found that whilst shoppers were more likely to approach a tasting table with an extensive array of jams, only 3% of those shoppers actually purchased a jam, whereas 30% of shoppers who had viewed a limited selection proceeded to purchase a jam. This shows that whilst a large assortment of options may initially entice decision makers and motivate them to approach a choice, it ultimately hinders their motivation to make a final decision, resulting in no decision being made. === Overchoice in online dating === Most research on overchoice has focused on decision-making in typical consumer contexts, with items such as jams, chocolates, birthday cards, and cleaning supplies (Dar-Nimrod et al., 2009; Diehl & Poyner, 2010; Iyengar & Lepper, 2000). Whilst these studies have advanced our knowledge of the choice overload phenomenon, it should be noted that decision-making affects people in various aspects of their lives, not just how they behave as consumers. As such, the overchoice effect is applicable to many different settings, including overchoice in online dating (see Figure 2). In a recent study, Thomas et al. (2022) tested the effects of overchoice on dating apps by asking participants to evaluate fake dating profiles. Participants first completed partner-matching questions, then were informed of the number of matches they received. This was manipulated experimentally between groups, including a low, moderate, and high number of matches. Results showed that as dating app users’ perceptions of a high number of potential partners increased, so did their fears of being single. The researchers suggested that when people are overwhelmed by excessive choice, it becomes harder to evaluate options and increases the expectation of being able to find a suitable partner – which, when unmet, may induce fears of being single. {{RoundBoxTop|theme=1}} ;Mini case study Francis adopted a pet dog six months ago and is still struggling to decide what to name it. Whenever Francis thinks they are ready to commit to a name, they start to worry that there might be better alternative options, and ends up not being able to decide at all. {{RoundBoxBottom}}<quiz display="simple"> {Which of these concepts best captures what Francis is experiencing? |type="()"} - Expectation disconfirmation + Decision paralysis - Intrinsic motivation </quiz> ==Why does the overchoice effect occur?== So far, this chapter has touched on the antecedent factors of the overchoice effect and briefly discussed how researchers have studied this phenomenon. Considering people encounter many types of decisions that occur in vastly different domains of life, how can psychological science construct an all-encompassing explanation of why the overchoice effect occurs? Rather than offering a single explanation, researchers have proposed several potential mechanisms for the overchoice effect. Understanding why the overchoice effect occurs is valuable, as it may provide useful insight into ways of mitigating its effects. === Expectation disconfirmation === One indication of choice overload is experiencing dissatisfaction with the choice (Chernev et al., 2015). The experience of perceiving an unwanted discrepancy between expectations and reality is known as negative expectation disconfirmation (Diehl & Poyner, 2010). Experimental studies of overchoice have shown that extensive choice sets can lead to more negative expectation disconfirmation, such that decision makers who believe a product has been selected from a large rather than small assortment, set high initial expectations and end up dissatisfied (Diehl & Poyner, 2010). When options are extensive, people may set unrealistically high expectations about being able to achieve a desired outcome, which ultimately increases their chances of experiencing disappointment (Grant & Schwartz, 2011). These findings suggest that decision makers in overchoice situations may benefit from setting realistic or even low expectations which are likely to be met or exceeded. === Increased cognitive costs === [[File:Man considering which of three labeled cups to choose while an opponent looks on.webp|left|thumb|213x213px|'''Figure 3'''. Overchoice is costly to mental energy]] Another mechanism which may explain the overchoice effect is increased cognitive costs. Having too many options to select from means more cognitive resources and mental energy is required to compare the different options (see Figure 3). This is a type of [[wikipedia:Information_overload|information overload]], which can make the decision-making process more onerous and demotivate people from making a choice (Scheibehenne et al., 2010). Cognitive costs may therefore explain why overchoice can result in outcomes such as decision paralysis and choice deferral. Referring back to self-determination theory (Ryan & Deci, 2000), whilst choices may increase autonomy, the cognitive resources required to make decisions in overchoice settings could undermine people's psychological need for competence. For example, excessive choices may make people feel like they do not have the mental energy or the expertise to make an informed decision, thus hindering their intrinsic motivation. In terms of addressing this problem, decision makers could try to reduce cognitive resource costs in overchoice situations by setting boundaries on how much time and effort they spend comparing different options. === Anticipated regret === Researchers have hypothesised that people experience the overchoice effect due to a fear of future regret (Iyengar & Lepper, 2000). As options increase, so does the potential for decision makers to engage in counterfactual thinking and dwell on “what ifs” after making their choice (Grant & Schwartz, 2011). Indeed, studies show that decision makers who select from extensive assortments tend to experience more regret about their choices compared to those who select from limited assortments (Iyengar & Lepper, 2000). Regret can also impact the decision-making process. For example, Gourville and Soman (2005) found that consumers were more likely to make a choice from a larger assortment if they were informed that their purchase was refundable. This demonstrates that reversibility of choice may mitigate the overchoice effect, as it reduces the potential for later regret. Based on these findings, decision makers may be able to better navigate overchoice by making room for potential future regret. For example, consumers could select products with a flexible return policy or a trial period. === The inverted U and brain activity === A study by Shah and Wolford (2007) suggested that the overchoice effect follows an inverted U shape. Their study found that whilst purchasing-behaviour increased with the number of options, this peaked at a moderate assortment size and began to decline again once the optimal selection size was surpassed. The mechanism behind this pattern of behaviour has been explored from a physiological perspective. For example, activity in the left striatum and right anterior cingulate cortex – structures involved in motivating decision-making behaviour, appears highest when participants select from a moderate-size choice set and lower when participants select from limited or extensive choice sets (Reutskaja et al., 2018) . This suggests an optimal level of choice facilitates behaviour by activating brain areas which motivate decision-making. It also illustrates that brain activity in extensive-choice conditions are similar to those observed in conditions of limited choice. Taken together, these findings show that whilst too many options can negatively impact decision-making motivation, it is ill-advised to offer too few options. {{RoundBoxTop|theme=1}} ;Mini case study Ollie goes to a large book store to find the perfect book to read. After choosing what he believed to be the "best" option, he discovers the book is not interesting, and feels disappointed as a result. {{RoundBoxBottom}}<quiz display="simple"> {Which of these concepts best captures what Ollie is experiencing? |type="()"} - Decision paralysis - Cognitive resource costs + Negative expectation disconfirmation </quiz> == Who is most susceptible to the overchoice effect? == The intensity of choice overload is influenced by individual differences and factors related to the decision maker (Chernev et al., 2015). A perceived excess of choice also appears to have varying effects on choice satisfaction across different countries, such that in some countries (e.g., Japan), excess choice actually has a positive effect on choice satisfaction (Reutskaja et al., 2022). In other words, overchoice does not affect everyone in the same way. === Lack of familiarity === [[File:HK 中環 Central 皇后大道中 Queen's Road Central the L-Place shop U-Select Supermarket bottled wines October 2020 SS2 01.jpg|thumb|266x266px|'''Figure 4.''' Those who are unfamiliar with a choice domain are more likely to be overwhelmed by large assortment sizes]] One personal factor which may make someone more susceptible to the overchoice effect is ''preference uncertainty'', which is a lack of prior preferences and expertise (Chernev et al., 2015). When a person is unfamiliar with a decision area, more cognitive resources are required to evaluate different options. Anticipating these time and energy costs may impair or demotivate decision-making all together (Scheibehenne et al., 2010). In a study by Beneke (2015), a sample of participants from South Africa were asked to select a wine from an online store. This was manipulated between groups, so that participants selected from either a large or reduced assortment. The results showed that assortment satisfaction did not differ between the two choice sets for consumers who felt highly familiar with wine. However, those with less familiarity experienced lower assortment satisfaction and higher perceived assortment costs (e.g., processing time, overwhelm, confusion) when the choice set was large (see Figure 4). Based on these findings, decision makers who are unfamiliar with the decision domain may be able to better navigate overchoice by consulting someone with more expertise. === Decision-making orientation === Overchoice may also affect people differently based on their decision-making orientation. For example, according to [[Motivation and emotion/Book/2019/Regulatory focus theory and goal pursuit|regulatory focus theory]], people’s decisions are driven by either a ''promotion orientation'' – characterised by a sensitivity to positive outcomes, or a ''prevention orientation'' – characterised by a sensitivity to negative outcomes (Polman, 2012). Theoretically, those who are prevention-oriented would be more vulnerable to the overchoice effect, because a larger choice set is likely to contain more unsatisfactory options; whereas promotion-oriented people would benefit from having more choices, as that would increase their chances of finding a suitable option (Polman, 2012). A study by Polman (2012) revealed that when participants were making a decision for themselves, they tended to report a prevention focus and were more likely to experience choice overload. However, this effect was reversed when participants were asked to make a decision for someone else, such that they tended to report a promotion focus and were more likely to be satisfied with a larger choice set. Interestingly, the study found that this reversed effect in proxy decision makers was absent when the decision makers were induced to feel accountable for their choices, presumably because it activated a prevention-focused orientation. Overall, this study demonstrates that large choice sets are more likely to negatively affect decision makers who feel a sense of accountability for their choices – whether they are making a decision for themselves or someone else, due to a heightened sensitivity to potential negative outcomes. === Maximisers vs satisficers === Similar to decision-making orientation, the effects of overchoice can also differ based on whether people adopt a maximising or satisficing decision-making strategy. [[wikipedia:Maximization_(psychology)|''Maximisers'']] are motivated to get the most out of their choice, often spending considerable effort comparing options in search of the best one (Schwartz et al., 2002). ''Satisficers'', however, make decisions based on what is “good enough”, without expending additional effort to go beyond an acceptable standard (Schwartz et al., 2002). The ‘maximisation paradox’ explains that those with maximising tendencies are more likely to sacrifice resources such as time and energy to increase their choice set, which ultimately results in higher choice dissatisfaction (Dar-Nimrod et al., 2009). This concept was illustrated in a study by Dar-Nimrod et al. (2009), which found that maximisers were more willing to give up their time (by completing an additional survey) to obtain a larger array of choices, compared to satisficers. The study also found that maximisers who selected from the larger array were less satisfied with their choice, compared to maximisers who selected from a smaller selection. Furthermore, choice satisfaction did not differ between selection sizes for satisficers. This may be because satisficers tend to minimise search costs by spending less effort searching different options within an extensive choice set (Reed et al., 2011). In terms of practical application, those who struggle with maximising tendencies could try to adopt a satisficing approach when evaluating options and avoid seeking out large selection sizes. {{RoundBoxTop|theme=1}};Mini case study Jen has recently started online dating. She spends a considerable amount of time swiping through profiles to try to find the perfect partner. She wants to make sure she has carefully evaluated all her options before deciding who to go on a date with. <quiz display="simple"> {What decision-making strategy does Jen seem to be using? |type="()"} + Maximising - Satisficing - Proxy decision making {Based on research on the overchoice effect, what is one way Jen might be able to reduce the negative effects of overchoice? |type="()"} - Spend more time swiping through profiles - Sign up to other dating apps to increase her options + Try to limit the number of profiles she swipes through </quiz> {{RoundBoxBottom}} ==Conclusion== The overchoice effect is a widely occurring psychological phenomenon in which excessive choice undermines intrinsic motivation (Iyengar & Lepper, 2000) and inhibits decision-making (Manolică et al., 2021). Overchoice can be observed in various contexts – including in consumer behaviour, education, and online dating. However, it is important to remember that increased choice does not guarantee negative outcomes, and choice deprivation also has undesirable consequences (Reutsakaja et al., 2022). Mechanisms underlying the overchoice effect include expectation disconfirmation (Diehl & Poyner, 2010), increased cognitive costs (Scheibehenne et al., 2010), anticipated regret (Iyengar & Lepper, 2000), and reduced activation in brain areas that motivate decision-making (Reutskaja et al., 2018). People who are most susceptible to the overchoice effect include those who lack familiarity with the choice (Beneke, 2015), feel accountable for their decisions (Polman, 2012), and seek to find the “best” option (Dar-Nimrod et al., 2009). A key message to take from the overchoice effect is that "more" is not always better. When people seek out more choices, they may unintentionally be making it harder for themselves to come to a satisfactory decision. However, decision makers can take comfort in knowing the overchoice effect is not inevitable. By understanding why this phenomenon occurs and who are most affected, it may be possible to mitigate its effects. Presented below is a summary of the practical recommendations that psychological science has to offer regarding the overchoice effect. {{RoundBoxTop|theme=3}} ;Recommendations for decision makers * Set realistic expectations (Diehl & Poyner, 2010) * Minimise cognitive costs by reducing the time and energy spent making decisions (Scheibehenne et al., 2010) * Select choices that are reversible (Lepper & Iyengar, 2000) * Adopt a satisficing approach by settling for a “good enough” option (Dar-Nimrod et al., 2009) * Increase familiarity with the choice domain (Beneke, 2015) {{RoundBoxBottom}} ==See also== * [[Motivation and emotion/Book/2023/Overchoice, motivation, and emotion|Overchoice, motivation, and emotion]] (Book chapter, 2023) * [[Motivation and emotion/Book/2023/Choice and emotion|Choice and emotion]] (Book chapter, 2023) * [[Motivation and emotion/Book/2022/Choice overload|Choice overload]] (Book chapter, 2022) * [[wikipedia:Information_overload|Information overload]] (Wikipedia) * [[wikipedia:Maximization_(psychology)|Maximisation (psychology)]] (Wikipedia) * [[wikipedia:Analysis_paralysis|Analysis paralysis]] (Wikipedia) ==References== {{Hanging indent|1= Beneke, J. (2015). Are consumers really bewildered by overchoice? An experimental approach to the tyranny of “too much”. ''Journal of Food Products Marketing'', ''21''(1), 90–101. https://doi.org/10.1080/10454446.2013.843490 Chernev, A., Böckenholt, U., & Goodman, J. (2015). Choice overload: A conceptual review and meta-analysis. ''Journal of Consumer Psychology'', ''25''(2), 333–358. https://doi.org/10.1016/j.jcps.2014.08.002 Dar-Nimrod, I., Rawn, C. D., Lehman, D. R., & Schwartz, B. (2009). The maximization paradox: The costs of seeking alternatives. ''Personality and Individual Differences'', ''46''(5), 631–635. https://doi.org/10.1016/j.paid.2009.01.007 Diehl, K, & Poyner, C. (2010). Great expectations?! Assortment size, expectations, and satisfaction. ''Journal of Marketing Research'', ''47''(2), 313–322. https://doi.org/10.1509/jmkr.47.2.312 Grant, A. M., & Schwartz, B. (2011). Too much of a good thing: The challenge and opportunity of the inverted U. ''Perspectives on Psychological Science'', ''6''(1), 61–76. https://doi.org/10.1177/1745691610393523 Gourville, J. T., & Soman, D. (2005). Overchoice and assortment type: When and why variety backfires. ''Marketing Science (Providence, R.I.)'', ''24''(3), 382–395. https://doi.org/10.1287/mksc.1040.0109 Iyengar, S. S., & Lepper, M. R. (2000). When choice is demotivating: Can one desire too much of a good thing? ''Journal of Personality and Social Psychology'', ''79''(6), 995–1006. https://doi.org/10.1037/0022-3514.79.6.995 Manolică, A., Guță, A-S., Roman, T., & Dragăn, L. M. (2021). Is consumer overchoice a reason for decision paralysis? ''Sustainability (Basel, Switzerland)'', ''13''(11), 5920. https://doi.org/10.3390/su13115920 Patall, E. A., Cooper, H., & Robinson, J. C. (2008). The effects of choice on intrinsic motivation and related outcomes: A meta-analysis or research findings. ''Psychological Bulletin'', ''13''(2), 270–300. https://doi.org/10.1037/0033-2909.134.2.270 Polman, E. (2012). Effects of self-other decision making on regulatory focus and choice overload. ''Journal of Personality and Social Psychology'', ''102''(5), 980–993. https://doi.org/10.1037/a0026966 Reed, D. D., Reed, F. D. D., Chok, J., & Brozyna, G. A. (2011). The “tyranny of choice”: Choice overload as a possible instance of effort discounting. ''The Psychological Record'', ''61''(4), 547–560. https://doi.org/10.1007/BF03395776 Reutskaja, E., Cheek, N. N., Iyengar, S., & Schwartz, B. (2022). Choice deprivation, choice overload, and satisfaction with choices across six nations. ''Journal of International Marketing (East Lansing, Mich.)'', ''30''(3), 18–34. https://doi.org/10.1177/1069031X211073821 Reutskaja, E., Lindner, Nagel, R., Andersen, R. A., & Camerer, C.F. (2018). Choice overload reduces neural signatures of choice set value in dorsal striatum and anterior cingulate cortex. ''Nature Human Behaviour'', ''2''(12), 925–935. https://doi.org/10.1038/s41562-018-0440-2 Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. ''The American Psychologist'', ''55''(1), 68–78. https://doi.org/10.1037/0003-066X.55.1.68 Scheibehenne, B., Greifeneder, R., & Todd, P. M. (2010). Can there ever be too many options? A meta-analytic review of choice overload. ''Journal of Consumer Research'', ''37''(3), 409–425. https://doi.org/10.1086/651235 Schwartz, B., Ward, A., Monterosso, J., Lyubomirsky, S., White, K., Lehman, D. R., & Diener, E. (2002). Maximizing versus satisficing: Happiness is a matter of choice. ''Journal of Personality and Social Psychology'', ''83''(5), 1178–1197. https://doi.org/10.1037/0022-3514.83.5.1178 Shah, A. M., & Wolford, G. (2007). Buying behavior as a function of parametric variation of number of choices. ''Psychological Science'', ''18''(5), 369–370. https://doi.org/10.1111/j.1467-9280.2007.01906.x Thomas, M. F., Binder, A., & Matthes, J. (2022). The agony of partner choice: The effect of excessive partner availability on fear of being single, self-esteem, and partner choice overload. ''Computers in Human Behaviour'', ''126'', 106977. https://doi.org/10.1016/j.chb.2021.106977 }} ==External links== * [https://www.youtube.com/watch?v=1pq5jnM1C-A Sheena Iyengar: How to make choosing easier] (Youtube, 2012) * [https://youtu.be/VO6XEQIsCoM The paradox of choice ''| Barry Schwartz''] (Youtube, 2007) * [https://thedecisionlab.com/biases/choice-overload-bias Why do we have a harder time choosing when we have more options?] (The Decision Lab, n.d) [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:{{#titleparts:{{PAGENAME}}|3}}/Top]] [[Category:Motivation and emotion/Book/Choice]] [[Category:Motivation and emotion/Book/Motivation]] n5cwh0ge5b30wd095muwnzdqwu0q9x7 2 301582 2835275 2584676 2026-10-01T05:07:06Z PicoMath 2975918 2835275 wikitext text/x-wiki Hi, my name is Lilly and I use she/her pronouns. I am mainly on [[wikipedia:User:PicoMath|Wikipedia]], but I might contribute to Wikiversity from time-to-time, possibly doing original research (a [[wikipedia:Mortal_sin|mortal sin]] on Wikipedia) here. Instructional resources that I may contribute are likely practice problem sets for mathematics and philosophy (especially philosophy, as many philosophy texts are lacking in practice problems). {{User Wikipedia}} {{User Mathcontrib}} 82q4svilajid1jbrz2x318usbbq04ug 0 318763 2835221 2700792 2026-09-30T19:14:44Z ~2026-52677-11 3111897 /* The Nature of Freedom and Its Limits */ 2835221 wikitext text/x-wiki [[w:Freedom|Freedom]] is a foundational principle of [[w:Human_rights|human rights]], [[w:Democracy|democracy]], and personal [[w:Autonomy|autonomy]].<ref>[[w:ChatGPT|ChatGPT]] generated this text responding to the prompt: “Write an essay entitled ‘Your freedom ends where mine begins’”.</ref> It is the ability to think, speak, and act according to one’s own will. However, freedom is not an absolute, boundless right—it exists within a framework of [[w:Duty|responsibility]] and [[Dignity|respect]] for others. The famous principle, often attributed to various thinkers<ref>[https://quoteinvestigator.com/2011/10/15/liberty-fist-nose/ Quote Investigator]. </ref>, states: ''"Your freedom ends where mine begins."'' This idea captures the delicate balance between individual liberty and collective well-being, emphasizing that true freedom does not include the right to harm or infringe upon the freedoms of others. == The Nature of Freedom and Its Limits == jjjjjFreedom is often misunderstood as the ability to do anything one desires, without constraint. However, in any society, unrestricted freedom leads to chaos, conflict, and oppression. Laws, social norms, and [[Moral Reasoning|ethical considerations]] exist to ensure that one person’s rights do not come at the expense of another’s. For example, [[w:Freedom_of_speech|freedom of speech]] is a fundamental right, but it does not extend to inciting violence, spreading harmful misinformation, or defaming others. Likewise, the right to personal autonomy includes making choices about one’s body and beliefs, but it does not grant the right to endanger others, such as refusing vaccination during a public health crisis. This principle is central to legal and political systems worldwide. Courts frequently weigh individual rights against public interest, ensuring that freedoms are exercised within reasonable boundaries. A person may have the right to play loud music in their home, but not at a volume that disturbs their neighbors. A business owner has the right to operate freely, but not to engage in discrimination or exploit workers. These boundaries prevent anarchy and uphold a fair, functioning society. == Social and Ethical Dimensions of Freedom == Beyond the legal sphere, the balance of freedom plays a crucial role in social and ethical interactions. Personal relationships, workplaces, and communities all depend on mutual respect. A person is free to express their opinions, but if they do so in a way that demeans or silences others, they undermine the very principle of freedom they claim to uphold. Similarly, [[w:Economic_freedom|economic freedom]] is essential for innovation and prosperity, but when unchecked, it can lead to [[w:Monopoly|monopolies]], exploitation, and social inequality. Workers have the right to fair wages and humane working conditions, just as business owners have the right to profit from their enterprises. Striking a balance between these freedoms ensures economic stability and social justice. Ethically, the idea that "your freedom ends where mine begins" is crucial in addressing moral dilemmas. A smoker may have the freedom to smoke, but that freedom does not extend to forcing others to inhale secondhand smoke. A driver has the freedom to operate their vehicle, but not to drive recklessly and endanger others. These are everyday examples of how freedom is regulated not only by laws but also by ethical considerations of fairness, harm, and responsibility. == The Importance of Mutual Respect == True freedom flourishes in an environment of mutual respect. Recognizing the limits of our own liberty allows for peaceful coexistence. The alternative—unrestricted personal freedom—often leads to the suppression of others. History provides countless examples: [[w:Colonialism|colonialism]], [[w:Oppression|oppression]], and [[w:Dictatorship|dictatorship]] arise when individuals or groups impose their will unchecked. In democratic societies, [[w:Civic_engagement|civic engagement]] depends on the recognition that others have rights too. Protesters may have the [[w:Freedom_of_assembly|freedom to assemble]], but they do not have the right to prevent others from accessing public spaces. Freedom of religion allows people to practice their faith, but not to impose their beliefs on others through coercion or law. The concept of shared space, both physically and ideologically, reinforces that one person’s liberty is not an excuse to infringe upon another’s. == Freedom in the Digital Age == In today’s world, digital freedom is a growing concern. The internet allows people to express themselves freely, but online harassment, misinformation, and privacy violations highlight the challenges of unregulated digital spaces. A person may have the right to share opinions online, but not to engage in [[w:Cyberbullying|cyberbullying]] or spread dangerous falsehoods. Social media platforms and governments struggle to balance free speech with the need to protect individuals from harm, showcasing the modern complexities of where one person’s freedom ends and another’s begins. == Conclusion: The Balance of Rights and Responsibilities == Freedom is not just a personal right; it is a shared responsibility. To ensure a just and functional society, we must acknowledge that our rights are limited by the rights of others. This principle applies in legal, social, and ethical contexts, shaping the way we interact and coexist. By recognizing that "your freedom ends where mine begins," we build a world that values both individual autonomy and collective [[w:Well-being|well-being]]. True freedom is not found in boundless self-interest but in mutual respect, fairness, and the responsible exercise of our rights. {{CourseCat}} nx70nfn9hs31nzithbzx75054j3ai13 0 324858 2835227 2831765 2026-09-30T22:03:34Z IanVG 2918363 /* Chapters */ 2835227 wikitext text/x-wiki This is the introduction course for thermodynamics, which is located in the [[Thermodynamics|topic of thermodynamics]]. Thermodynamics is the study of energy, energy transformation and their interactions with matter. The application of thermodynamics enables analysis of a wide range of technologies such as steam engines, refrigerators and turbines. "Thermodynamics" comes from the Greek words "therme" which means heat and "dynamikos" which means force, or power. So, "Thermodynamics" is the study of forces due to heat or heat due to forces. It deals with the conversion of energies through various forms and to various systems, as well as energies' relationships with the properties of a system, process and cycles. == Chapters == # Basic concepts and definitions ## [[Introduction to thermodynamics/Introduction|Introduction]] ## [[Introduction to thermodynamics/What is thermodynamics?|What is thermodynamics?]] ## [[Introduction to thermodynamics/System and surroundings|System and surroundings]] ## [[Introduction to thermodynamics/Extensive and intensive properties|Extensive and intensive properties]] ## [[Introduction to thermodynamics/State postulate|State postulate]] ## [[Introduction to thermodynamics/State, process, and cycle|State, process, and cycle]] ## [[Introduction to thermodynamics/Temperature and heat|Temperature and heat]] ## [[Introduction to thermodynamics/Chapter one review|Chapter one review]] # Thermodynamic properties of a pure substance ## [[Introduction to thermodynamics/Chapter introduction and learning objectives|Chapter introduction and learning objectives]] ## [[Introduction to thermodynamics/Pure substances|Pure substances]] ## [[Introduction to thermodynamics/Thermodynamic properties|Thermodynamic properties]] ## [[Introduction to thermodynamics/Phase diagrams|Phase diagrams]] ## [[Introduction to thermodynamics/Thermodynamic tables|Thermodynamic tables]] ## Chapter review ## Key Equations # Real and ideal gases ## [[Introduction to thermodynamics/Introduction to real and ideal gases|Introduction to real and ideal gases]] ## Ideal gas and ideal gas equation of state ## Real gas and compressibility factor ## Chapter review ## Key equations # First law of thermodynamics for closed systems ## Chapter introduction and learning objectives ## Internal energy in a system ## Heat transfer across a boundary ## Work ## [[Introduction to thermodynamics/The first law of thermodynamics for closed systems|The first law of thermodynamics for closed systems]] ## [[Introduction to thermodynamics/Chapter four review|Chapter four review]] ##Key equations # The first law of thermodynamics for a control volume ## Chapter introduction and learning objectives ## Enthalpy ## Mass and energy conservation equations in a control volume ## Applications of a the mass and energy conservation equations in steady flow devices ## Chapter review ## Key equations # Entropy and the second law of thermodynamics ## [[Introduction to thermodynamics/Chapter introduction and learning objectives|Chapter introduction and learning objectives]] ## Heat engine ## [[Introduction to thermodynamics/Refrigerator and heat pump|Refrigerator and heat pump]] ## [[Introduction to thermodynamics/The second law of thermodynamics: Kelvin-Planck and Clausius statements|The second law of thermodynamics: Kelvin-Planck and Clausius statements]] ## [[Introduction to thermodynamics/Carnot cycles|Carnot cycles]] ## [[Introduction to thermodynamics/Entropy and entropy generation|Entropy and entropy generation]] ## The second law of thermodynamics for closed systems ## Specific entropy of a state ## Applications of the second law of thermodynamics in closed systems ## The second law of thermodynamics for open systems ## [[Introduction to thermodynamics/Applications of the second law of thermodynamics in open systems|Applications of the second law of thermodynamics in open systems]] ## Chapter reivew ## Key equations #Absolute zero and the third law of thermodynamics ## Chapter introduction and learning objectives ## [[Introduction to thermodynamics/The third law of thermodynamics: Nernst principle|The third law of thermodynamics: Nernst principle]] ## [[Introduction to thermodynamics/Applications of the third law of dynamics|Applications of the third law of dynamics]] == Attribution == Parts of this course incorporate material from the [https://pressbooks.bccampus.ca/thermo1 Introduction to Engineering Thermodynamics] course published by Pressbooks.<ref> Yu Yan, C. (2022). Introduction to Engineering Thermodynamics. BCcampus. https://pressbooks.bccampus.ca/thermo1/</ref> == References == [[Category:Courses]] [[Category:Science]] [[Category:Thermodynamics]] eje4k7qqoec0yu7733y4ftcsw60moa0 0 326060 2835158 2835154 2026-09-30T12:37:16Z Amélie E. Pereira 3042711 /* Introduction */ Cite Q 2835158 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name=":15">{{Cite Q|Q121307039}}.</ref><ref name=":16">{{Cite journal|date=2023-08-01|title=A socio-technical transition perspective on positive tipping points in climate change mitigation: Analysing seven interacting feedback loops in offshore wind and electric vehicles acceleration|url=https://www.sciencedirect.com/science/article/pii/S0040162523003244|journal=Technological Forecasting and Social Change|language=en-US|volume=193|pages=122639|doi=10.1016/j.techfore.2023.122639|issn=0040-1625}}</ref><ref name=":17">{{Cite journal|last=Sovacool|first=Benjamin K.|last2=Geels|first2=Frank W.|last3=Andersen|first3=Allan Dahl|last4=Grubb|first4=Michael|last5=Jordan|first5=Andrew J.|last6=Kern|first6=Florian|last7=Kivimaa|first7=Paula|last8=Lockwood|first8=Matthew|last9=Markard|first9=Jochen|date=2025-03-01|title=The acceleration of low-carbon transitions: Insights, concepts, challenges, and new directions for research|url=https://www.sciencedirect.com/science/article/pii/S2214629625000295|journal=Energy Research & Social Science|volume=121|pages=103948|doi=10.1016/j.erss.2025.103948|issn=2214-6296}}</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences<ref>{{Cite journal|last=Kepes|first=Sven|last2=Bennett|first2=Andrew A.|last3=McDaniel|first3=Michael A.|date=2014-09|title=Evidence-Based Management and the Trustworthiness of Our Cumulative Scientific Knowledge: Implications for Teaching, Research, and Practice|url=https://journals.aom.org/doi/10.5465/amle.2013.0193|journal=Academy of Management Learning & Education|volume=13|issue=3|pages=446–466|doi=10.5465/amle.2013.0193|issn=1537-260X}}</ref><ref>Pfeffer, J., & Sutton, R. I. (2006). Evidence-Based Management. Harvard Business Review, 13. </ref>. Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite journal|last=Bornmann|first=Lutz|last2=Mutz|first2=Rüdiger|date=2015|title=Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/asi.23329|journal=Journal of the Association for Information Science and Technology|language=en|volume=66|issue=11|pages=2215–2222|doi=10.1002/asi.23329|issn=2330-1643}}</ref><ref name=":23">{{Cite journal|last=Hanson|first=Mark A.|last2=Barreiro|first2=Pablo Gómez|last3=Crosetto|first3=Paolo|last4=Brockington|first4=Dan|date=2024-11-01|title=The strain on scientific publishing|url=https://doi.org/10.1162/qss_a_00327|journal=Quantitative Science Studies|volume=5|issue=4|pages=823–843|doi=10.1162/qss_a_00327|issn=2641-3337}}</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name=":23" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge<ref>{{Cite journal|last=Hartman|first=Yvonne|last2=Darab|first2=Sandy|date=2012-01-01|title=A Call for Slow Scholarship: A Case Study on the Intensification of Academic Life and Its Implications for Pedagogy|url=https://doi.org/10.1080/10714413.2012.643740|journal=Review of Education, Pedagogy, and Cultural Studies|volume=34|issue=1-2|pages=49–60|doi=10.1080/10714413.2012.643740|issn=1071-4413}}</ref>. “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite journal|last=L.|first=Mobley, David|last2=M.|first2=Zuckerman, Daniel|date=2015-02-03|title=A proposal for regularly updated review/survey articles: "Perpetual Reviews"|url=https://arxiv.org/abs/1502.01329|journal=arXiv.org|language=en|doi=10.48550/arXiv.1502.01329}}</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref>. This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite journal|last=Elliott|first=Julian H.|last2=Synnot|first2=Anneliese|last3=Turner|first3=Tari|last4=Simmonds|first4=Mark|last5=Akl|first5=Elie A.|last6=McDonald|first6=Steve|last7=Salanti|first7=Georgia|last8=Meerpohl|first8=Joerg|last9=MacLehose|first9=Harriet|date=2017-11|title=Living systematic review: 1. Introduction—the why, what, when, and how|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435617306364|journal=Journal of Clinical Epidemiology|volume=91|pages=23–30|doi=10.1016/j.jclinepi.2017.08.010|issn=0895-4356}}</ref>,<ref>{{Cite journal|last=Uttley|first=Lesley|last2=Quintana|first2=Daniel S.|last3=Montgomery|first3=Paul|last4=Carroll|first4=Christopher|last5=Page|first5=Matthew J.|last6=Falzon|first6=Louise|last7=Sutton|first7=Anthea|last8=Moher|first8=David|date=2023-04|title=The problems with systematic reviews: a living systematic review|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435623000112|journal=Journal of Clinical Epidemiology|volume=156|pages=30–41|doi=10.1016/j.jclinepi.2023.01.011|issn=0895-4356}}</ref>,<ref name=":18">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful<ref>{{Cite journal|last=Haley|first=Usha C. V.|date=2023-09-01|title=Triviality and the Search for Scholarly Impact|url=https://doi.org/10.1177/01708406231175292|journal=Organization Studies|language=EN|volume=44|issue=9|pages=1547–1550|doi=10.1177/01708406231175292|issn=0170-8406}}</ref>. Wikipedia is a key knowledge dissemination platform widely used by students<ref>{{Cite journal|last=Sunvy|first=Ahmed Shafkat|last2=Reza|first2=Raiyan Bin|date=2023-04-12|title=Students’ Perception of Wikipedia as an Academic Information Source|url=https://ejournal.undiksha.ac.id/index.php/IJERR/article/view/57572|journal=Indonesian Journal Of Educational Research and Review|volume=6|issue=1|pages=134–147|doi=10.23887/ijerr.v6i1.57572|issn=2621-8984}}</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature<ref>{{Cite journal|last=Thompson|first=Neil|last2=Hanley|first2=Douglas|date=2017|title=Science Is Shaped by Wikipedia: Evidence from a Randomized Control Trial|url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3039505|journal=SSRN Electronic Journal|doi=10.2139/ssrn.3039505|issn=1556-5068}}</ref> and that some scholars cite directly Wikipedia<ref>{{Cite journal|last=Dooley|first=Patricia L.|date=2010-07-07|title=Wikipedia and the two-faced professoriate|url=https://doi.org/10.1145/1832772.1832803|journal=Proceedings of the 6th International Symposium on Wikis and Open Collaboration|series=WikiSym '10|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=1–2|doi=10.1145/1832772.1832803|isbn=978-1-4503-0056-8}}</ref>. However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives<ref>{{Cite journal|last=Chen|first=Yan|last2=Farzan|first2=Rosta|last3=Kraut|first3=Robert|last4=YeckehZaare|first4=Iman|last5=Zhang|first5=Ark Fangzhou|date=2024-05|title=Motivating Experts to Contribute to Digital Public Goods: A Personalized Field Experiment on Wikipedia|url=https://pubsonline.informs.org/doi/10.1287/mnsc.2023.4852|journal=Management Science|volume=70|issue=5|pages=3264–3280|doi=10.1287/mnsc.2023.4852|issn=0025-1909}}</ref>,<ref>{{Cite journal|last=Kincaid|first=Dustin W.|last2=Beck|first2=Whitney S.|last3=Brandt|first3=Jessica E.|last4=Mars Brisbin|first4=Margaret|last5=Farrell|first5=Kaitlin J.|last6=Hondula|first6=Kelly L.|last7=Larson|first7=Erin I.|last8=Shogren|first8=Arial J.|date=2021|title=Wikipedia can help resolve information inequality in the aquatic sciences|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/lol2.10168|journal=Limnology and Oceanography Letters|language=en|volume=6|issue=1|pages=18–23|doi=10.1002/lol2.10168|issn=2378-2242}}</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite journal|last=Ceci|first=Stephen J.|last2=Ginther|first2=Donna K.|last3=Kahn|first3=Shulamit|last4=Williams|first4=Wendy M.|date=2014-12-01|title=Women in Academic Science: A Changing Landscape|url=https://doi.org/10.1177/1529100614541236|journal=Psychological Science in the Public Interest|language=EN|volume=15|issue=3|pages=75–141|doi=10.1177/1529100614541236|issn=1529-1006}}</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite journal|last=Lam|first=Shyong (Tony) K.|last2=Uduwage|first2=Anuradha|last3=Dong|first3=Zhenhua|last4=Sen|first4=Shilad|last5=Musicant|first5=David R.|last6=Terveen|first6=Loren|last7=Riedl|first7=John|date=2011-10-03|title=WP:clubhouse?: an exploration of Wikipedia's gender imbalance|url=https://dl.acm.org/doi/10.1145/2038558.2038560|language=en|publisher=ACM|pages=1–10|doi=10.1145/2038558.2038560|isbn=978-1-4503-0909-7}}</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name=":15" /><ref name=":16" /><ref name=":17" /> and fragmented results coming from various disciplines<ref name=":20">{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|doi=10.1016/J.ERSS.2021.102444}}</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name=":18" />. They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name=":4" /> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name=":0" />). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only statements using a specitic source in order to map the content of a single academic article. First test here: https://w.wiki/PFqH *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} lm3imjm8f9eeio95is00sgs8x4oekwj 2835159 2835158 2026-09-30T12:38:26Z Amélie E. Pereira 3042711 2835159 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name=":16">{{Cite journal|date=2023-08-01|title=A socio-technical transition perspective on positive tipping points in climate change mitigation: Analysing seven interacting feedback loops in offshore wind and electric vehicles acceleration|url=https://www.sciencedirect.com/science/article/pii/S0040162523003244|journal=Technological Forecasting and Social Change|language=en-US|volume=193|pages=122639|doi=10.1016/j.techfore.2023.122639|issn=0040-1625}}</ref><ref name=":17">{{Cite journal|last=Sovacool|first=Benjamin K.|last2=Geels|first2=Frank W.|last3=Andersen|first3=Allan Dahl|last4=Grubb|first4=Michael|last5=Jordan|first5=Andrew J.|last6=Kern|first6=Florian|last7=Kivimaa|first7=Paula|last8=Lockwood|first8=Matthew|last9=Markard|first9=Jochen|date=2025-03-01|title=The acceleration of low-carbon transitions: Insights, concepts, challenges, and new directions for research|url=https://www.sciencedirect.com/science/article/pii/S2214629625000295|journal=Energy Research & Social Science|volume=121|pages=103948|doi=10.1016/j.erss.2025.103948|issn=2214-6296}}</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences<ref>{{Cite journal|last=Kepes|first=Sven|last2=Bennett|first2=Andrew A.|last3=McDaniel|first3=Michael A.|date=2014-09|title=Evidence-Based Management and the Trustworthiness of Our Cumulative Scientific Knowledge: Implications for Teaching, Research, and Practice|url=https://journals.aom.org/doi/10.5465/amle.2013.0193|journal=Academy of Management Learning & Education|volume=13|issue=3|pages=446–466|doi=10.5465/amle.2013.0193|issn=1537-260X}}</ref><ref>Pfeffer, J., & Sutton, R. I. (2006). Evidence-Based Management. Harvard Business Review, 13. </ref>. Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite journal|last=Bornmann|first=Lutz|last2=Mutz|first2=Rüdiger|date=2015|title=Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/asi.23329|journal=Journal of the Association for Information Science and Technology|language=en|volume=66|issue=11|pages=2215–2222|doi=10.1002/asi.23329|issn=2330-1643}}</ref><ref name=":23">{{Cite journal|last=Hanson|first=Mark A.|last2=Barreiro|first2=Pablo Gómez|last3=Crosetto|first3=Paolo|last4=Brockington|first4=Dan|date=2024-11-01|title=The strain on scientific publishing|url=https://doi.org/10.1162/qss_a_00327|journal=Quantitative Science Studies|volume=5|issue=4|pages=823–843|doi=10.1162/qss_a_00327|issn=2641-3337}}</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name=":23" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge<ref>{{Cite journal|last=Hartman|first=Yvonne|last2=Darab|first2=Sandy|date=2012-01-01|title=A Call for Slow Scholarship: A Case Study on the Intensification of Academic Life and Its Implications for Pedagogy|url=https://doi.org/10.1080/10714413.2012.643740|journal=Review of Education, Pedagogy, and Cultural Studies|volume=34|issue=1-2|pages=49–60|doi=10.1080/10714413.2012.643740|issn=1071-4413}}</ref>. “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite journal|last=L.|first=Mobley, David|last2=M.|first2=Zuckerman, Daniel|date=2015-02-03|title=A proposal for regularly updated review/survey articles: "Perpetual Reviews"|url=https://arxiv.org/abs/1502.01329|journal=arXiv.org|language=en|doi=10.48550/arXiv.1502.01329}}</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref>. This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite journal|last=Elliott|first=Julian H.|last2=Synnot|first2=Anneliese|last3=Turner|first3=Tari|last4=Simmonds|first4=Mark|last5=Akl|first5=Elie A.|last6=McDonald|first6=Steve|last7=Salanti|first7=Georgia|last8=Meerpohl|first8=Joerg|last9=MacLehose|first9=Harriet|date=2017-11|title=Living systematic review: 1. Introduction—the why, what, when, and how|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435617306364|journal=Journal of Clinical Epidemiology|volume=91|pages=23–30|doi=10.1016/j.jclinepi.2017.08.010|issn=0895-4356}}</ref>,<ref>{{Cite journal|last=Uttley|first=Lesley|last2=Quintana|first2=Daniel S.|last3=Montgomery|first3=Paul|last4=Carroll|first4=Christopher|last5=Page|first5=Matthew J.|last6=Falzon|first6=Louise|last7=Sutton|first7=Anthea|last8=Moher|first8=David|date=2023-04|title=The problems with systematic reviews: a living systematic review|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435623000112|journal=Journal of Clinical Epidemiology|volume=156|pages=30–41|doi=10.1016/j.jclinepi.2023.01.011|issn=0895-4356}}</ref>,<ref name=":18">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful<ref>{{Cite journal|last=Haley|first=Usha C. V.|date=2023-09-01|title=Triviality and the Search for Scholarly Impact|url=https://doi.org/10.1177/01708406231175292|journal=Organization Studies|language=EN|volume=44|issue=9|pages=1547–1550|doi=10.1177/01708406231175292|issn=0170-8406}}</ref>. Wikipedia is a key knowledge dissemination platform widely used by students<ref>{{Cite journal|last=Sunvy|first=Ahmed Shafkat|last2=Reza|first2=Raiyan Bin|date=2023-04-12|title=Students’ Perception of Wikipedia as an Academic Information Source|url=https://ejournal.undiksha.ac.id/index.php/IJERR/article/view/57572|journal=Indonesian Journal Of Educational Research and Review|volume=6|issue=1|pages=134–147|doi=10.23887/ijerr.v6i1.57572|issn=2621-8984}}</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature<ref>{{Cite journal|last=Thompson|first=Neil|last2=Hanley|first2=Douglas|date=2017|title=Science Is Shaped by Wikipedia: Evidence from a Randomized Control Trial|url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3039505|journal=SSRN Electronic Journal|doi=10.2139/ssrn.3039505|issn=1556-5068}}</ref> and that some scholars cite directly Wikipedia<ref>{{Cite journal|last=Dooley|first=Patricia L.|date=2010-07-07|title=Wikipedia and the two-faced professoriate|url=https://doi.org/10.1145/1832772.1832803|journal=Proceedings of the 6th International Symposium on Wikis and Open Collaboration|series=WikiSym '10|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=1–2|doi=10.1145/1832772.1832803|isbn=978-1-4503-0056-8}}</ref>. However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives<ref>{{Cite journal|last=Chen|first=Yan|last2=Farzan|first2=Rosta|last3=Kraut|first3=Robert|last4=YeckehZaare|first4=Iman|last5=Zhang|first5=Ark Fangzhou|date=2024-05|title=Motivating Experts to Contribute to Digital Public Goods: A Personalized Field Experiment on Wikipedia|url=https://pubsonline.informs.org/doi/10.1287/mnsc.2023.4852|journal=Management Science|volume=70|issue=5|pages=3264–3280|doi=10.1287/mnsc.2023.4852|issn=0025-1909}}</ref>,<ref>{{Cite journal|last=Kincaid|first=Dustin W.|last2=Beck|first2=Whitney S.|last3=Brandt|first3=Jessica E.|last4=Mars Brisbin|first4=Margaret|last5=Farrell|first5=Kaitlin J.|last6=Hondula|first6=Kelly L.|last7=Larson|first7=Erin I.|last8=Shogren|first8=Arial J.|date=2021|title=Wikipedia can help resolve information inequality in the aquatic sciences|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/lol2.10168|journal=Limnology and Oceanography Letters|language=en|volume=6|issue=1|pages=18–23|doi=10.1002/lol2.10168|issn=2378-2242}}</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite journal|last=Ceci|first=Stephen J.|last2=Ginther|first2=Donna K.|last3=Kahn|first3=Shulamit|last4=Williams|first4=Wendy M.|date=2014-12-01|title=Women in Academic Science: A Changing Landscape|url=https://doi.org/10.1177/1529100614541236|journal=Psychological Science in the Public Interest|language=EN|volume=15|issue=3|pages=75–141|doi=10.1177/1529100614541236|issn=1529-1006}}</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite journal|last=Lam|first=Shyong (Tony) K.|last2=Uduwage|first2=Anuradha|last3=Dong|first3=Zhenhua|last4=Sen|first4=Shilad|last5=Musicant|first5=David R.|last6=Terveen|first6=Loren|last7=Riedl|first7=John|date=2011-10-03|title=WP:clubhouse?: an exploration of Wikipedia's gender imbalance|url=https://dl.acm.org/doi/10.1145/2038558.2038560|language=en|publisher=ACM|pages=1–10|doi=10.1145/2038558.2038560|isbn=978-1-4503-0909-7}}</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name=":16" /><ref name=":17" /> and fragmented results coming from various disciplines<ref name=":20">{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|doi=10.1016/J.ERSS.2021.102444}}</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name=":18" />. They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name=":4" /> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name=":0" />). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only statements using a specitic source in order to map the content of a single academic article. First test here: https://w.wiki/PFqH *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} kkfbolakkaoh99qej9zlibm0yuh2yij 2835166 2835159 2026-09-30T12:41:25Z Amélie E. Pereira 3042711 mef sce 2835166 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name=":17">{{Cite journal|last=Sovacool|first=Benjamin K.|last2=Geels|first2=Frank W.|last3=Andersen|first3=Allan Dahl|last4=Grubb|first4=Michael|last5=Jordan|first5=Andrew J.|last6=Kern|first6=Florian|last7=Kivimaa|first7=Paula|last8=Lockwood|first8=Matthew|last9=Markard|first9=Jochen|date=2025-03-01|title=The acceleration of low-carbon transitions: Insights, concepts, challenges, and new directions for research|url=https://www.sciencedirect.com/science/article/pii/S2214629625000295|journal=Energy Research & Social Science|volume=121|pages=103948|doi=10.1016/j.erss.2025.103948|issn=2214-6296}}</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences<ref>{{Cite journal|last=Kepes|first=Sven|last2=Bennett|first2=Andrew A.|last3=McDaniel|first3=Michael A.|date=2014-09|title=Evidence-Based Management and the Trustworthiness of Our Cumulative Scientific Knowledge: Implications for Teaching, Research, and Practice|url=https://journals.aom.org/doi/10.5465/amle.2013.0193|journal=Academy of Management Learning & Education|volume=13|issue=3|pages=446–466|doi=10.5465/amle.2013.0193|issn=1537-260X}}</ref><ref>Pfeffer, J., & Sutton, R. I. (2006). Evidence-Based Management. Harvard Business Review, 13. </ref>. Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite journal|last=Bornmann|first=Lutz|last2=Mutz|first2=Rüdiger|date=2015|title=Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/asi.23329|journal=Journal of the Association for Information Science and Technology|language=en|volume=66|issue=11|pages=2215–2222|doi=10.1002/asi.23329|issn=2330-1643}}</ref><ref name=":23">{{Cite journal|last=Hanson|first=Mark A.|last2=Barreiro|first2=Pablo Gómez|last3=Crosetto|first3=Paolo|last4=Brockington|first4=Dan|date=2024-11-01|title=The strain on scientific publishing|url=https://doi.org/10.1162/qss_a_00327|journal=Quantitative Science Studies|volume=5|issue=4|pages=823–843|doi=10.1162/qss_a_00327|issn=2641-3337}}</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name=":23" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge<ref>{{Cite journal|last=Hartman|first=Yvonne|last2=Darab|first2=Sandy|date=2012-01-01|title=A Call for Slow Scholarship: A Case Study on the Intensification of Academic Life and Its Implications for Pedagogy|url=https://doi.org/10.1080/10714413.2012.643740|journal=Review of Education, Pedagogy, and Cultural Studies|volume=34|issue=1-2|pages=49–60|doi=10.1080/10714413.2012.643740|issn=1071-4413}}</ref>. “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite journal|last=L.|first=Mobley, David|last2=M.|first2=Zuckerman, Daniel|date=2015-02-03|title=A proposal for regularly updated review/survey articles: "Perpetual Reviews"|url=https://arxiv.org/abs/1502.01329|journal=arXiv.org|language=en|doi=10.48550/arXiv.1502.01329}}</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref>. This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite journal|last=Elliott|first=Julian H.|last2=Synnot|first2=Anneliese|last3=Turner|first3=Tari|last4=Simmonds|first4=Mark|last5=Akl|first5=Elie A.|last6=McDonald|first6=Steve|last7=Salanti|first7=Georgia|last8=Meerpohl|first8=Joerg|last9=MacLehose|first9=Harriet|date=2017-11|title=Living systematic review: 1. Introduction—the why, what, when, and how|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435617306364|journal=Journal of Clinical Epidemiology|volume=91|pages=23–30|doi=10.1016/j.jclinepi.2017.08.010|issn=0895-4356}}</ref>,<ref>{{Cite journal|last=Uttley|first=Lesley|last2=Quintana|first2=Daniel S.|last3=Montgomery|first3=Paul|last4=Carroll|first4=Christopher|last5=Page|first5=Matthew J.|last6=Falzon|first6=Louise|last7=Sutton|first7=Anthea|last8=Moher|first8=David|date=2023-04|title=The problems with systematic reviews: a living systematic review|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435623000112|journal=Journal of Clinical Epidemiology|volume=156|pages=30–41|doi=10.1016/j.jclinepi.2023.01.011|issn=0895-4356}}</ref>,<ref name=":18">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful<ref>{{Cite journal|last=Haley|first=Usha C. V.|date=2023-09-01|title=Triviality and the Search for Scholarly Impact|url=https://doi.org/10.1177/01708406231175292|journal=Organization Studies|language=EN|volume=44|issue=9|pages=1547–1550|doi=10.1177/01708406231175292|issn=0170-8406}}</ref>. Wikipedia is a key knowledge dissemination platform widely used by students<ref>{{Cite journal|last=Sunvy|first=Ahmed Shafkat|last2=Reza|first2=Raiyan Bin|date=2023-04-12|title=Students’ Perception of Wikipedia as an Academic Information Source|url=https://ejournal.undiksha.ac.id/index.php/IJERR/article/view/57572|journal=Indonesian Journal Of Educational Research and Review|volume=6|issue=1|pages=134–147|doi=10.23887/ijerr.v6i1.57572|issn=2621-8984}}</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature<ref>{{Cite journal|last=Thompson|first=Neil|last2=Hanley|first2=Douglas|date=2017|title=Science Is Shaped by Wikipedia: Evidence from a Randomized Control Trial|url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3039505|journal=SSRN Electronic Journal|doi=10.2139/ssrn.3039505|issn=1556-5068}}</ref> and that some scholars cite directly Wikipedia<ref>{{Cite journal|last=Dooley|first=Patricia L.|date=2010-07-07|title=Wikipedia and the two-faced professoriate|url=https://doi.org/10.1145/1832772.1832803|journal=Proceedings of the 6th International Symposium on Wikis and Open Collaboration|series=WikiSym '10|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=1–2|doi=10.1145/1832772.1832803|isbn=978-1-4503-0056-8}}</ref>. However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives<ref>{{Cite journal|last=Chen|first=Yan|last2=Farzan|first2=Rosta|last3=Kraut|first3=Robert|last4=YeckehZaare|first4=Iman|last5=Zhang|first5=Ark Fangzhou|date=2024-05|title=Motivating Experts to Contribute to Digital Public Goods: A Personalized Field Experiment on Wikipedia|url=https://pubsonline.informs.org/doi/10.1287/mnsc.2023.4852|journal=Management Science|volume=70|issue=5|pages=3264–3280|doi=10.1287/mnsc.2023.4852|issn=0025-1909}}</ref>,<ref>{{Cite journal|last=Kincaid|first=Dustin W.|last2=Beck|first2=Whitney S.|last3=Brandt|first3=Jessica E.|last4=Mars Brisbin|first4=Margaret|last5=Farrell|first5=Kaitlin J.|last6=Hondula|first6=Kelly L.|last7=Larson|first7=Erin I.|last8=Shogren|first8=Arial J.|date=2021|title=Wikipedia can help resolve information inequality in the aquatic sciences|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/lol2.10168|journal=Limnology and Oceanography Letters|language=en|volume=6|issue=1|pages=18–23|doi=10.1002/lol2.10168|issn=2378-2242}}</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite journal|last=Ceci|first=Stephen J.|last2=Ginther|first2=Donna K.|last3=Kahn|first3=Shulamit|last4=Williams|first4=Wendy M.|date=2014-12-01|title=Women in Academic Science: A Changing Landscape|url=https://doi.org/10.1177/1529100614541236|journal=Psychological Science in the Public Interest|language=EN|volume=15|issue=3|pages=75–141|doi=10.1177/1529100614541236|issn=1529-1006}}</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite journal|last=Lam|first=Shyong (Tony) K.|last2=Uduwage|first2=Anuradha|last3=Dong|first3=Zhenhua|last4=Sen|first4=Shilad|last5=Musicant|first5=David R.|last6=Terveen|first6=Loren|last7=Riedl|first7=John|date=2011-10-03|title=WP:clubhouse?: an exploration of Wikipedia's gender imbalance|url=https://dl.acm.org/doi/10.1145/2038558.2038560|language=en|publisher=ACM|pages=1–10|doi=10.1145/2038558.2038560|isbn=978-1-4503-0909-7}}</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name=":17" /> and fragmented results coming from various disciplines<ref name=":20">{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|doi=10.1016/J.ERSS.2021.102444}}</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name=":18" />. They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name=":4" /> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name=":0" />). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only statements using a specitic source in order to map the content of a single academic article. First test here: https://w.wiki/PFqH *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} ngak3rhj887hkvly7gprlllx23068n0 2835169 2835166 2026-09-30T12:44:53Z Amélie E. Pereira 3042711 mef 2835169 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences<ref>{{Cite journal|last=Kepes|first=Sven|last2=Bennett|first2=Andrew A.|last3=McDaniel|first3=Michael A.|date=2014-09|title=Evidence-Based Management and the Trustworthiness of Our Cumulative Scientific Knowledge: Implications for Teaching, Research, and Practice|url=https://journals.aom.org/doi/10.5465/amle.2013.0193|journal=Academy of Management Learning & Education|volume=13|issue=3|pages=446–466|doi=10.5465/amle.2013.0193|issn=1537-260X}}</ref><ref>Pfeffer, J., & Sutton, R. I. (2006). Evidence-Based Management. Harvard Business Review, 13. </ref>. Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite journal|last=Bornmann|first=Lutz|last2=Mutz|first2=Rüdiger|date=2015|title=Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/asi.23329|journal=Journal of the Association for Information Science and Technology|language=en|volume=66|issue=11|pages=2215–2222|doi=10.1002/asi.23329|issn=2330-1643}}</ref><ref name=":23">{{Cite journal|last=Hanson|first=Mark A.|last2=Barreiro|first2=Pablo Gómez|last3=Crosetto|first3=Paolo|last4=Brockington|first4=Dan|date=2024-11-01|title=The strain on scientific publishing|url=https://doi.org/10.1162/qss_a_00327|journal=Quantitative Science Studies|volume=5|issue=4|pages=823–843|doi=10.1162/qss_a_00327|issn=2641-3337}}</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name=":23" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge<ref>{{Cite journal|last=Hartman|first=Yvonne|last2=Darab|first2=Sandy|date=2012-01-01|title=A Call for Slow Scholarship: A Case Study on the Intensification of Academic Life and Its Implications for Pedagogy|url=https://doi.org/10.1080/10714413.2012.643740|journal=Review of Education, Pedagogy, and Cultural Studies|volume=34|issue=1-2|pages=49–60|doi=10.1080/10714413.2012.643740|issn=1071-4413}}</ref>. “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite journal|last=L.|first=Mobley, David|last2=M.|first2=Zuckerman, Daniel|date=2015-02-03|title=A proposal for regularly updated review/survey articles: "Perpetual Reviews"|url=https://arxiv.org/abs/1502.01329|journal=arXiv.org|language=en|doi=10.48550/arXiv.1502.01329}}</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref>. This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite journal|last=Elliott|first=Julian H.|last2=Synnot|first2=Anneliese|last3=Turner|first3=Tari|last4=Simmonds|first4=Mark|last5=Akl|first5=Elie A.|last6=McDonald|first6=Steve|last7=Salanti|first7=Georgia|last8=Meerpohl|first8=Joerg|last9=MacLehose|first9=Harriet|date=2017-11|title=Living systematic review: 1. Introduction—the why, what, when, and how|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435617306364|journal=Journal of Clinical Epidemiology|volume=91|pages=23–30|doi=10.1016/j.jclinepi.2017.08.010|issn=0895-4356}}</ref>,<ref>{{Cite journal|last=Uttley|first=Lesley|last2=Quintana|first2=Daniel S.|last3=Montgomery|first3=Paul|last4=Carroll|first4=Christopher|last5=Page|first5=Matthew J.|last6=Falzon|first6=Louise|last7=Sutton|first7=Anthea|last8=Moher|first8=David|date=2023-04|title=The problems with systematic reviews: a living systematic review|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435623000112|journal=Journal of Clinical Epidemiology|volume=156|pages=30–41|doi=10.1016/j.jclinepi.2023.01.011|issn=0895-4356}}</ref>,<ref name=":18">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful<ref>{{Cite journal|last=Haley|first=Usha C. V.|date=2023-09-01|title=Triviality and the Search for Scholarly Impact|url=https://doi.org/10.1177/01708406231175292|journal=Organization Studies|language=EN|volume=44|issue=9|pages=1547–1550|doi=10.1177/01708406231175292|issn=0170-8406}}</ref>. Wikipedia is a key knowledge dissemination platform widely used by students<ref>{{Cite journal|last=Sunvy|first=Ahmed Shafkat|last2=Reza|first2=Raiyan Bin|date=2023-04-12|title=Students’ Perception of Wikipedia as an Academic Information Source|url=https://ejournal.undiksha.ac.id/index.php/IJERR/article/view/57572|journal=Indonesian Journal Of Educational Research and Review|volume=6|issue=1|pages=134–147|doi=10.23887/ijerr.v6i1.57572|issn=2621-8984}}</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature<ref>{{Cite journal|last=Thompson|first=Neil|last2=Hanley|first2=Douglas|date=2017|title=Science Is Shaped by Wikipedia: Evidence from a Randomized Control Trial|url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3039505|journal=SSRN Electronic Journal|doi=10.2139/ssrn.3039505|issn=1556-5068}}</ref> and that some scholars cite directly Wikipedia<ref>{{Cite journal|last=Dooley|first=Patricia L.|date=2010-07-07|title=Wikipedia and the two-faced professoriate|url=https://doi.org/10.1145/1832772.1832803|journal=Proceedings of the 6th International Symposium on Wikis and Open Collaboration|series=WikiSym '10|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=1–2|doi=10.1145/1832772.1832803|isbn=978-1-4503-0056-8}}</ref>. However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives<ref>{{Cite journal|last=Chen|first=Yan|last2=Farzan|first2=Rosta|last3=Kraut|first3=Robert|last4=YeckehZaare|first4=Iman|last5=Zhang|first5=Ark Fangzhou|date=2024-05|title=Motivating Experts to Contribute to Digital Public Goods: A Personalized Field Experiment on Wikipedia|url=https://pubsonline.informs.org/doi/10.1287/mnsc.2023.4852|journal=Management Science|volume=70|issue=5|pages=3264–3280|doi=10.1287/mnsc.2023.4852|issn=0025-1909}}</ref>,<ref>{{Cite journal|last=Kincaid|first=Dustin W.|last2=Beck|first2=Whitney S.|last3=Brandt|first3=Jessica E.|last4=Mars Brisbin|first4=Margaret|last5=Farrell|first5=Kaitlin J.|last6=Hondula|first6=Kelly L.|last7=Larson|first7=Erin I.|last8=Shogren|first8=Arial J.|date=2021|title=Wikipedia can help resolve information inequality in the aquatic sciences|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/lol2.10168|journal=Limnology and Oceanography Letters|language=en|volume=6|issue=1|pages=18–23|doi=10.1002/lol2.10168|issn=2378-2242}}</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite journal|last=Ceci|first=Stephen J.|last2=Ginther|first2=Donna K.|last3=Kahn|first3=Shulamit|last4=Williams|first4=Wendy M.|date=2014-12-01|title=Women in Academic Science: A Changing Landscape|url=https://doi.org/10.1177/1529100614541236|journal=Psychological Science in the Public Interest|language=EN|volume=15|issue=3|pages=75–141|doi=10.1177/1529100614541236|issn=1529-1006}}</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite journal|last=Lam|first=Shyong (Tony) K.|last2=Uduwage|first2=Anuradha|last3=Dong|first3=Zhenhua|last4=Sen|first4=Shilad|last5=Musicant|first5=David R.|last6=Terveen|first6=Loren|last7=Riedl|first7=John|date=2011-10-03|title=WP:clubhouse?: an exploration of Wikipedia's gender imbalance|url=https://dl.acm.org/doi/10.1145/2038558.2038560|language=en|publisher=ACM|pages=1–10|doi=10.1145/2038558.2038560|isbn=978-1-4503-0909-7}}</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name=":20">{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|doi=10.1016/J.ERSS.2021.102444}}</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name=":18" />. They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name=":4" /> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name=":0" />). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only statements using a specitic source in order to map the content of a single academic article. First test here: https://w.wiki/PFqH *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} 7lfj190oy9ozc1qq6c7yqzrk90nu68l 2835170 2835169 2026-09-30T12:47:08Z Amélie E. Pereira 3042711 /* Introduction */ citeQ 2835170 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences<ref>{{Cite Q|Q134545576}}.</ref><ref>Pfeffer, J., & Sutton, R. I. (2006). Evidence-Based Management. Harvard Business Review, 13. </ref>. Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite journal|last=Bornmann|first=Lutz|last2=Mutz|first2=Rüdiger|date=2015|title=Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/asi.23329|journal=Journal of the Association for Information Science and Technology|language=en|volume=66|issue=11|pages=2215–2222|doi=10.1002/asi.23329|issn=2330-1643}}</ref><ref name=":23">{{Cite journal|last=Hanson|first=Mark A.|last2=Barreiro|first2=Pablo Gómez|last3=Crosetto|first3=Paolo|last4=Brockington|first4=Dan|date=2024-11-01|title=The strain on scientific publishing|url=https://doi.org/10.1162/qss_a_00327|journal=Quantitative Science Studies|volume=5|issue=4|pages=823–843|doi=10.1162/qss_a_00327|issn=2641-3337}}</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name=":23" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge<ref>{{Cite journal|last=Hartman|first=Yvonne|last2=Darab|first2=Sandy|date=2012-01-01|title=A Call for Slow Scholarship: A Case Study on the Intensification of Academic Life and Its Implications for Pedagogy|url=https://doi.org/10.1080/10714413.2012.643740|journal=Review of Education, Pedagogy, and Cultural Studies|volume=34|issue=1-2|pages=49–60|doi=10.1080/10714413.2012.643740|issn=1071-4413}}</ref>. “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite journal|last=L.|first=Mobley, David|last2=M.|first2=Zuckerman, Daniel|date=2015-02-03|title=A proposal for regularly updated review/survey articles: "Perpetual Reviews"|url=https://arxiv.org/abs/1502.01329|journal=arXiv.org|language=en|doi=10.48550/arXiv.1502.01329}}</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref>. This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite journal|last=Elliott|first=Julian H.|last2=Synnot|first2=Anneliese|last3=Turner|first3=Tari|last4=Simmonds|first4=Mark|last5=Akl|first5=Elie A.|last6=McDonald|first6=Steve|last7=Salanti|first7=Georgia|last8=Meerpohl|first8=Joerg|last9=MacLehose|first9=Harriet|date=2017-11|title=Living systematic review: 1. Introduction—the why, what, when, and how|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435617306364|journal=Journal of Clinical Epidemiology|volume=91|pages=23–30|doi=10.1016/j.jclinepi.2017.08.010|issn=0895-4356}}</ref>,<ref>{{Cite journal|last=Uttley|first=Lesley|last2=Quintana|first2=Daniel S.|last3=Montgomery|first3=Paul|last4=Carroll|first4=Christopher|last5=Page|first5=Matthew J.|last6=Falzon|first6=Louise|last7=Sutton|first7=Anthea|last8=Moher|first8=David|date=2023-04|title=The problems with systematic reviews: a living systematic review|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435623000112|journal=Journal of Clinical Epidemiology|volume=156|pages=30–41|doi=10.1016/j.jclinepi.2023.01.011|issn=0895-4356}}</ref>,<ref name=":18">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful<ref>{{Cite journal|last=Haley|first=Usha C. V.|date=2023-09-01|title=Triviality and the Search for Scholarly Impact|url=https://doi.org/10.1177/01708406231175292|journal=Organization Studies|language=EN|volume=44|issue=9|pages=1547–1550|doi=10.1177/01708406231175292|issn=0170-8406}}</ref>. Wikipedia is a key knowledge dissemination platform widely used by students<ref>{{Cite journal|last=Sunvy|first=Ahmed Shafkat|last2=Reza|first2=Raiyan Bin|date=2023-04-12|title=Students’ Perception of Wikipedia as an Academic Information Source|url=https://ejournal.undiksha.ac.id/index.php/IJERR/article/view/57572|journal=Indonesian Journal Of Educational Research and Review|volume=6|issue=1|pages=134–147|doi=10.23887/ijerr.v6i1.57572|issn=2621-8984}}</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature<ref>{{Cite journal|last=Thompson|first=Neil|last2=Hanley|first2=Douglas|date=2017|title=Science Is Shaped by Wikipedia: Evidence from a Randomized Control Trial|url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3039505|journal=SSRN Electronic Journal|doi=10.2139/ssrn.3039505|issn=1556-5068}}</ref> and that some scholars cite directly Wikipedia<ref>{{Cite journal|last=Dooley|first=Patricia L.|date=2010-07-07|title=Wikipedia and the two-faced professoriate|url=https://doi.org/10.1145/1832772.1832803|journal=Proceedings of the 6th International Symposium on Wikis and Open Collaboration|series=WikiSym '10|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=1–2|doi=10.1145/1832772.1832803|isbn=978-1-4503-0056-8}}</ref>. However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives<ref>{{Cite journal|last=Chen|first=Yan|last2=Farzan|first2=Rosta|last3=Kraut|first3=Robert|last4=YeckehZaare|first4=Iman|last5=Zhang|first5=Ark Fangzhou|date=2024-05|title=Motivating Experts to Contribute to Digital Public Goods: A Personalized Field Experiment on Wikipedia|url=https://pubsonline.informs.org/doi/10.1287/mnsc.2023.4852|journal=Management Science|volume=70|issue=5|pages=3264–3280|doi=10.1287/mnsc.2023.4852|issn=0025-1909}}</ref>,<ref>{{Cite journal|last=Kincaid|first=Dustin W.|last2=Beck|first2=Whitney S.|last3=Brandt|first3=Jessica E.|last4=Mars Brisbin|first4=Margaret|last5=Farrell|first5=Kaitlin J.|last6=Hondula|first6=Kelly L.|last7=Larson|first7=Erin I.|last8=Shogren|first8=Arial J.|date=2021|title=Wikipedia can help resolve information inequality in the aquatic sciences|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/lol2.10168|journal=Limnology and Oceanography Letters|language=en|volume=6|issue=1|pages=18–23|doi=10.1002/lol2.10168|issn=2378-2242}}</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite journal|last=Ceci|first=Stephen J.|last2=Ginther|first2=Donna K.|last3=Kahn|first3=Shulamit|last4=Williams|first4=Wendy M.|date=2014-12-01|title=Women in Academic Science: A Changing Landscape|url=https://doi.org/10.1177/1529100614541236|journal=Psychological Science in the Public Interest|language=EN|volume=15|issue=3|pages=75–141|doi=10.1177/1529100614541236|issn=1529-1006}}</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite journal|last=Lam|first=Shyong (Tony) K.|last2=Uduwage|first2=Anuradha|last3=Dong|first3=Zhenhua|last4=Sen|first4=Shilad|last5=Musicant|first5=David R.|last6=Terveen|first6=Loren|last7=Riedl|first7=John|date=2011-10-03|title=WP:clubhouse?: an exploration of Wikipedia's gender imbalance|url=https://dl.acm.org/doi/10.1145/2038558.2038560|language=en|publisher=ACM|pages=1–10|doi=10.1145/2038558.2038560|isbn=978-1-4503-0909-7}}</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name=":20">{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|doi=10.1016/J.ERSS.2021.102444}}</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name=":18" />. They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name=":4" /> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name=":0" />). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only statements using a specitic source in order to map the content of a single academic article. First test here: https://w.wiki/PFqH *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} 36y3vvq95loaj3lqpvn7is065r0rb0b 2835172 2835170 2026-09-30T12:49:37Z Amélie E. Pereira 3042711 /* Introduction */ mef 2835172 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite journal|last=Bornmann|first=Lutz|last2=Mutz|first2=Rüdiger|date=2015|title=Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/asi.23329|journal=Journal of the Association for Information Science and Technology|language=en|volume=66|issue=11|pages=2215–2222|doi=10.1002/asi.23329|issn=2330-1643}}</ref><ref name=":23">{{Cite journal|last=Hanson|first=Mark A.|last2=Barreiro|first2=Pablo Gómez|last3=Crosetto|first3=Paolo|last4=Brockington|first4=Dan|date=2024-11-01|title=The strain on scientific publishing|url=https://doi.org/10.1162/qss_a_00327|journal=Quantitative Science Studies|volume=5|issue=4|pages=823–843|doi=10.1162/qss_a_00327|issn=2641-3337}}</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name=":23" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge<ref>{{Cite journal|last=Hartman|first=Yvonne|last2=Darab|first2=Sandy|date=2012-01-01|title=A Call for Slow Scholarship: A Case Study on the Intensification of Academic Life and Its Implications for Pedagogy|url=https://doi.org/10.1080/10714413.2012.643740|journal=Review of Education, Pedagogy, and Cultural Studies|volume=34|issue=1-2|pages=49–60|doi=10.1080/10714413.2012.643740|issn=1071-4413}}</ref>. “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite journal|last=L.|first=Mobley, David|last2=M.|first2=Zuckerman, Daniel|date=2015-02-03|title=A proposal for regularly updated review/survey articles: "Perpetual Reviews"|url=https://arxiv.org/abs/1502.01329|journal=arXiv.org|language=en|doi=10.48550/arXiv.1502.01329}}</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref>. This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite journal|last=Elliott|first=Julian H.|last2=Synnot|first2=Anneliese|last3=Turner|first3=Tari|last4=Simmonds|first4=Mark|last5=Akl|first5=Elie A.|last6=McDonald|first6=Steve|last7=Salanti|first7=Georgia|last8=Meerpohl|first8=Joerg|last9=MacLehose|first9=Harriet|date=2017-11|title=Living systematic review: 1. Introduction—the why, what, when, and how|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435617306364|journal=Journal of Clinical Epidemiology|volume=91|pages=23–30|doi=10.1016/j.jclinepi.2017.08.010|issn=0895-4356}}</ref>,<ref>{{Cite journal|last=Uttley|first=Lesley|last2=Quintana|first2=Daniel S.|last3=Montgomery|first3=Paul|last4=Carroll|first4=Christopher|last5=Page|first5=Matthew J.|last6=Falzon|first6=Louise|last7=Sutton|first7=Anthea|last8=Moher|first8=David|date=2023-04|title=The problems with systematic reviews: a living systematic review|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435623000112|journal=Journal of Clinical Epidemiology|volume=156|pages=30–41|doi=10.1016/j.jclinepi.2023.01.011|issn=0895-4356}}</ref>,<ref name=":18">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful<ref>{{Cite journal|last=Haley|first=Usha C. V.|date=2023-09-01|title=Triviality and the Search for Scholarly Impact|url=https://doi.org/10.1177/01708406231175292|journal=Organization Studies|language=EN|volume=44|issue=9|pages=1547–1550|doi=10.1177/01708406231175292|issn=0170-8406}}</ref>. Wikipedia is a key knowledge dissemination platform widely used by students<ref>{{Cite journal|last=Sunvy|first=Ahmed Shafkat|last2=Reza|first2=Raiyan Bin|date=2023-04-12|title=Students’ Perception of Wikipedia as an Academic Information Source|url=https://ejournal.undiksha.ac.id/index.php/IJERR/article/view/57572|journal=Indonesian Journal Of Educational Research and Review|volume=6|issue=1|pages=134–147|doi=10.23887/ijerr.v6i1.57572|issn=2621-8984}}</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature<ref>{{Cite journal|last=Thompson|first=Neil|last2=Hanley|first2=Douglas|date=2017|title=Science Is Shaped by Wikipedia: Evidence from a Randomized Control Trial|url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3039505|journal=SSRN Electronic Journal|doi=10.2139/ssrn.3039505|issn=1556-5068}}</ref> and that some scholars cite directly Wikipedia<ref>{{Cite journal|last=Dooley|first=Patricia L.|date=2010-07-07|title=Wikipedia and the two-faced professoriate|url=https://doi.org/10.1145/1832772.1832803|journal=Proceedings of the 6th International Symposium on Wikis and Open Collaboration|series=WikiSym '10|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=1–2|doi=10.1145/1832772.1832803|isbn=978-1-4503-0056-8}}</ref>. However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives<ref>{{Cite journal|last=Chen|first=Yan|last2=Farzan|first2=Rosta|last3=Kraut|first3=Robert|last4=YeckehZaare|first4=Iman|last5=Zhang|first5=Ark Fangzhou|date=2024-05|title=Motivating Experts to Contribute to Digital Public Goods: A Personalized Field Experiment on Wikipedia|url=https://pubsonline.informs.org/doi/10.1287/mnsc.2023.4852|journal=Management Science|volume=70|issue=5|pages=3264–3280|doi=10.1287/mnsc.2023.4852|issn=0025-1909}}</ref>,<ref>{{Cite journal|last=Kincaid|first=Dustin W.|last2=Beck|first2=Whitney S.|last3=Brandt|first3=Jessica E.|last4=Mars Brisbin|first4=Margaret|last5=Farrell|first5=Kaitlin J.|last6=Hondula|first6=Kelly L.|last7=Larson|first7=Erin I.|last8=Shogren|first8=Arial J.|date=2021|title=Wikipedia can help resolve information inequality in the aquatic sciences|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/lol2.10168|journal=Limnology and Oceanography Letters|language=en|volume=6|issue=1|pages=18–23|doi=10.1002/lol2.10168|issn=2378-2242}}</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite journal|last=Ceci|first=Stephen J.|last2=Ginther|first2=Donna K.|last3=Kahn|first3=Shulamit|last4=Williams|first4=Wendy M.|date=2014-12-01|title=Women in Academic Science: A Changing Landscape|url=https://doi.org/10.1177/1529100614541236|journal=Psychological Science in the Public Interest|language=EN|volume=15|issue=3|pages=75–141|doi=10.1177/1529100614541236|issn=1529-1006}}</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite journal|last=Lam|first=Shyong (Tony) K.|last2=Uduwage|first2=Anuradha|last3=Dong|first3=Zhenhua|last4=Sen|first4=Shilad|last5=Musicant|first5=David R.|last6=Terveen|first6=Loren|last7=Riedl|first7=John|date=2011-10-03|title=WP:clubhouse?: an exploration of Wikipedia's gender imbalance|url=https://dl.acm.org/doi/10.1145/2038558.2038560|language=en|publisher=ACM|pages=1–10|doi=10.1145/2038558.2038560|isbn=978-1-4503-0909-7}}</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name=":20">{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|doi=10.1016/J.ERSS.2021.102444}}</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name=":18" />. They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name=":4" /> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name=":0" />). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only statements using a specitic source in order to map the content of a single academic article. First test here: https://w.wiki/PFqH *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} f0k1fmuqoahgjfisxkozgkjdgr8kc5g 2835174 2835172 2026-09-30T12:52:45Z Amélie E. Pereira 3042711 /* The problem of academic information overload */ 2835174 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge<ref>{{Cite journal|last=Hartman|first=Yvonne|last2=Darab|first2=Sandy|date=2012-01-01|title=A Call for Slow Scholarship: A Case Study on the Intensification of Academic Life and Its Implications for Pedagogy|url=https://doi.org/10.1080/10714413.2012.643740|journal=Review of Education, Pedagogy, and Cultural Studies|volume=34|issue=1-2|pages=49–60|doi=10.1080/10714413.2012.643740|issn=1071-4413}}</ref>. “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite journal|last=L.|first=Mobley, David|last2=M.|first2=Zuckerman, Daniel|date=2015-02-03|title=A proposal for regularly updated review/survey articles: "Perpetual Reviews"|url=https://arxiv.org/abs/1502.01329|journal=arXiv.org|language=en|doi=10.48550/arXiv.1502.01329}}</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref>. This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite journal|last=Elliott|first=Julian H.|last2=Synnot|first2=Anneliese|last3=Turner|first3=Tari|last4=Simmonds|first4=Mark|last5=Akl|first5=Elie A.|last6=McDonald|first6=Steve|last7=Salanti|first7=Georgia|last8=Meerpohl|first8=Joerg|last9=MacLehose|first9=Harriet|date=2017-11|title=Living systematic review: 1. Introduction—the why, what, when, and how|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435617306364|journal=Journal of Clinical Epidemiology|volume=91|pages=23–30|doi=10.1016/j.jclinepi.2017.08.010|issn=0895-4356}}</ref>,<ref>{{Cite journal|last=Uttley|first=Lesley|last2=Quintana|first2=Daniel S.|last3=Montgomery|first3=Paul|last4=Carroll|first4=Christopher|last5=Page|first5=Matthew J.|last6=Falzon|first6=Louise|last7=Sutton|first7=Anthea|last8=Moher|first8=David|date=2023-04|title=The problems with systematic reviews: a living systematic review|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435623000112|journal=Journal of Clinical Epidemiology|volume=156|pages=30–41|doi=10.1016/j.jclinepi.2023.01.011|issn=0895-4356}}</ref>,<ref name=":18">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful<ref>{{Cite journal|last=Haley|first=Usha C. V.|date=2023-09-01|title=Triviality and the Search for Scholarly Impact|url=https://doi.org/10.1177/01708406231175292|journal=Organization Studies|language=EN|volume=44|issue=9|pages=1547–1550|doi=10.1177/01708406231175292|issn=0170-8406}}</ref>. Wikipedia is a key knowledge dissemination platform widely used by students<ref>{{Cite journal|last=Sunvy|first=Ahmed Shafkat|last2=Reza|first2=Raiyan Bin|date=2023-04-12|title=Students’ Perception of Wikipedia as an Academic Information Source|url=https://ejournal.undiksha.ac.id/index.php/IJERR/article/view/57572|journal=Indonesian Journal Of Educational Research and Review|volume=6|issue=1|pages=134–147|doi=10.23887/ijerr.v6i1.57572|issn=2621-8984}}</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature<ref>{{Cite journal|last=Thompson|first=Neil|last2=Hanley|first2=Douglas|date=2017|title=Science Is Shaped by Wikipedia: Evidence from a Randomized Control Trial|url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3039505|journal=SSRN Electronic Journal|doi=10.2139/ssrn.3039505|issn=1556-5068}}</ref> and that some scholars cite directly Wikipedia<ref>{{Cite journal|last=Dooley|first=Patricia L.|date=2010-07-07|title=Wikipedia and the two-faced professoriate|url=https://doi.org/10.1145/1832772.1832803|journal=Proceedings of the 6th International Symposium on Wikis and Open Collaboration|series=WikiSym '10|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=1–2|doi=10.1145/1832772.1832803|isbn=978-1-4503-0056-8}}</ref>. However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives<ref>{{Cite journal|last=Chen|first=Yan|last2=Farzan|first2=Rosta|last3=Kraut|first3=Robert|last4=YeckehZaare|first4=Iman|last5=Zhang|first5=Ark Fangzhou|date=2024-05|title=Motivating Experts to Contribute to Digital Public Goods: A Personalized Field Experiment on Wikipedia|url=https://pubsonline.informs.org/doi/10.1287/mnsc.2023.4852|journal=Management Science|volume=70|issue=5|pages=3264–3280|doi=10.1287/mnsc.2023.4852|issn=0025-1909}}</ref>,<ref>{{Cite journal|last=Kincaid|first=Dustin W.|last2=Beck|first2=Whitney S.|last3=Brandt|first3=Jessica E.|last4=Mars Brisbin|first4=Margaret|last5=Farrell|first5=Kaitlin J.|last6=Hondula|first6=Kelly L.|last7=Larson|first7=Erin I.|last8=Shogren|first8=Arial J.|date=2021|title=Wikipedia can help resolve information inequality in the aquatic sciences|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/lol2.10168|journal=Limnology and Oceanography Letters|language=en|volume=6|issue=1|pages=18–23|doi=10.1002/lol2.10168|issn=2378-2242}}</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite journal|last=Ceci|first=Stephen J.|last2=Ginther|first2=Donna K.|last3=Kahn|first3=Shulamit|last4=Williams|first4=Wendy M.|date=2014-12-01|title=Women in Academic Science: A Changing Landscape|url=https://doi.org/10.1177/1529100614541236|journal=Psychological Science in the Public Interest|language=EN|volume=15|issue=3|pages=75–141|doi=10.1177/1529100614541236|issn=1529-1006}}</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite journal|last=Lam|first=Shyong (Tony) K.|last2=Uduwage|first2=Anuradha|last3=Dong|first3=Zhenhua|last4=Sen|first4=Shilad|last5=Musicant|first5=David R.|last6=Terveen|first6=Loren|last7=Riedl|first7=John|date=2011-10-03|title=WP:clubhouse?: an exploration of Wikipedia's gender imbalance|url=https://dl.acm.org/doi/10.1145/2038558.2038560|language=en|publisher=ACM|pages=1–10|doi=10.1145/2038558.2038560|isbn=978-1-4503-0909-7}}</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name=":20">{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|doi=10.1016/J.ERSS.2021.102444}}</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name=":18" />. They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name=":4" /> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name=":0" />). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only statements using a specitic source in order to map the content of a single academic article. First test here: https://w.wiki/PFqH *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} 24zvi0s7njjqkdsftth0f2j0qh5mgos 2835175 2835174 2026-09-30T12:54:30Z Amélie E. Pereira 3042711 /* The problem of academic information overload */ 2835175 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite journal|last=L.|first=Mobley, David|last2=M.|first2=Zuckerman, Daniel|date=2015-02-03|title=A proposal for regularly updated review/survey articles: "Perpetual Reviews"|url=https://arxiv.org/abs/1502.01329|journal=arXiv.org|language=en|doi=10.48550/arXiv.1502.01329}}</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref>. This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite journal|last=Elliott|first=Julian H.|last2=Synnot|first2=Anneliese|last3=Turner|first3=Tari|last4=Simmonds|first4=Mark|last5=Akl|first5=Elie A.|last6=McDonald|first6=Steve|last7=Salanti|first7=Georgia|last8=Meerpohl|first8=Joerg|last9=MacLehose|first9=Harriet|date=2017-11|title=Living systematic review: 1. Introduction—the why, what, when, and how|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435617306364|journal=Journal of Clinical Epidemiology|volume=91|pages=23–30|doi=10.1016/j.jclinepi.2017.08.010|issn=0895-4356}}</ref>,<ref>{{Cite journal|last=Uttley|first=Lesley|last2=Quintana|first2=Daniel S.|last3=Montgomery|first3=Paul|last4=Carroll|first4=Christopher|last5=Page|first5=Matthew J.|last6=Falzon|first6=Louise|last7=Sutton|first7=Anthea|last8=Moher|first8=David|date=2023-04|title=The problems with systematic reviews: a living systematic review|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435623000112|journal=Journal of Clinical Epidemiology|volume=156|pages=30–41|doi=10.1016/j.jclinepi.2023.01.011|issn=0895-4356}}</ref>,<ref name=":18">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful<ref>{{Cite journal|last=Haley|first=Usha C. V.|date=2023-09-01|title=Triviality and the Search for Scholarly Impact|url=https://doi.org/10.1177/01708406231175292|journal=Organization Studies|language=EN|volume=44|issue=9|pages=1547–1550|doi=10.1177/01708406231175292|issn=0170-8406}}</ref>. Wikipedia is a key knowledge dissemination platform widely used by students<ref>{{Cite journal|last=Sunvy|first=Ahmed Shafkat|last2=Reza|first2=Raiyan Bin|date=2023-04-12|title=Students’ Perception of Wikipedia as an Academic Information Source|url=https://ejournal.undiksha.ac.id/index.php/IJERR/article/view/57572|journal=Indonesian Journal Of Educational Research and Review|volume=6|issue=1|pages=134–147|doi=10.23887/ijerr.v6i1.57572|issn=2621-8984}}</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature<ref>{{Cite journal|last=Thompson|first=Neil|last2=Hanley|first2=Douglas|date=2017|title=Science Is Shaped by Wikipedia: Evidence from a Randomized Control Trial|url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3039505|journal=SSRN Electronic Journal|doi=10.2139/ssrn.3039505|issn=1556-5068}}</ref> and that some scholars cite directly Wikipedia<ref>{{Cite journal|last=Dooley|first=Patricia L.|date=2010-07-07|title=Wikipedia and the two-faced professoriate|url=https://doi.org/10.1145/1832772.1832803|journal=Proceedings of the 6th International Symposium on Wikis and Open Collaboration|series=WikiSym '10|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=1–2|doi=10.1145/1832772.1832803|isbn=978-1-4503-0056-8}}</ref>. However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives<ref>{{Cite journal|last=Chen|first=Yan|last2=Farzan|first2=Rosta|last3=Kraut|first3=Robert|last4=YeckehZaare|first4=Iman|last5=Zhang|first5=Ark Fangzhou|date=2024-05|title=Motivating Experts to Contribute to Digital Public Goods: A Personalized Field Experiment on Wikipedia|url=https://pubsonline.informs.org/doi/10.1287/mnsc.2023.4852|journal=Management Science|volume=70|issue=5|pages=3264–3280|doi=10.1287/mnsc.2023.4852|issn=0025-1909}}</ref>,<ref>{{Cite journal|last=Kincaid|first=Dustin W.|last2=Beck|first2=Whitney S.|last3=Brandt|first3=Jessica E.|last4=Mars Brisbin|first4=Margaret|last5=Farrell|first5=Kaitlin J.|last6=Hondula|first6=Kelly L.|last7=Larson|first7=Erin I.|last8=Shogren|first8=Arial J.|date=2021|title=Wikipedia can help resolve information inequality in the aquatic sciences|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/lol2.10168|journal=Limnology and Oceanography Letters|language=en|volume=6|issue=1|pages=18–23|doi=10.1002/lol2.10168|issn=2378-2242}}</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite journal|last=Ceci|first=Stephen J.|last2=Ginther|first2=Donna K.|last3=Kahn|first3=Shulamit|last4=Williams|first4=Wendy M.|date=2014-12-01|title=Women in Academic Science: A Changing Landscape|url=https://doi.org/10.1177/1529100614541236|journal=Psychological Science in the Public Interest|language=EN|volume=15|issue=3|pages=75–141|doi=10.1177/1529100614541236|issn=1529-1006}}</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite journal|last=Lam|first=Shyong (Tony) K.|last2=Uduwage|first2=Anuradha|last3=Dong|first3=Zhenhua|last4=Sen|first4=Shilad|last5=Musicant|first5=David R.|last6=Terveen|first6=Loren|last7=Riedl|first7=John|date=2011-10-03|title=WP:clubhouse?: an exploration of Wikipedia's gender imbalance|url=https://dl.acm.org/doi/10.1145/2038558.2038560|language=en|publisher=ACM|pages=1–10|doi=10.1145/2038558.2038560|isbn=978-1-4503-0909-7}}</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name=":20">{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|doi=10.1016/J.ERSS.2021.102444}}</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name=":18" />. They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name=":4" /> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name=":0" />). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only statements using a specitic source in order to map the content of a single academic article. First test here: https://w.wiki/PFqH *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} miom3bf1lqphjfo1p1sh0cgasd9r8r0 2835179 2835175 2026-09-30T12:57:52Z Amélie E. Pereira 3042711 /* The problem of knowledge synthesis */ mef 2835179 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite journal|last=Elliott|first=Julian H.|last2=Synnot|first2=Anneliese|last3=Turner|first3=Tari|last4=Simmonds|first4=Mark|last5=Akl|first5=Elie A.|last6=McDonald|first6=Steve|last7=Salanti|first7=Georgia|last8=Meerpohl|first8=Joerg|last9=MacLehose|first9=Harriet|date=2017-11|title=Living systematic review: 1. Introduction—the why, what, when, and how|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435617306364|journal=Journal of Clinical Epidemiology|volume=91|pages=23–30|doi=10.1016/j.jclinepi.2017.08.010|issn=0895-4356}}</ref>,<ref>{{Cite journal|last=Uttley|first=Lesley|last2=Quintana|first2=Daniel S.|last3=Montgomery|first3=Paul|last4=Carroll|first4=Christopher|last5=Page|first5=Matthew J.|last6=Falzon|first6=Louise|last7=Sutton|first7=Anthea|last8=Moher|first8=David|date=2023-04|title=The problems with systematic reviews: a living systematic review|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435623000112|journal=Journal of Clinical Epidemiology|volume=156|pages=30–41|doi=10.1016/j.jclinepi.2023.01.011|issn=0895-4356}}</ref>,<ref name=":18">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful<ref>{{Cite journal|last=Haley|first=Usha C. V.|date=2023-09-01|title=Triviality and the Search for Scholarly Impact|url=https://doi.org/10.1177/01708406231175292|journal=Organization Studies|language=EN|volume=44|issue=9|pages=1547–1550|doi=10.1177/01708406231175292|issn=0170-8406}}</ref>. Wikipedia is a key knowledge dissemination platform widely used by students<ref>{{Cite journal|last=Sunvy|first=Ahmed Shafkat|last2=Reza|first2=Raiyan Bin|date=2023-04-12|title=Students’ Perception of Wikipedia as an Academic Information Source|url=https://ejournal.undiksha.ac.id/index.php/IJERR/article/view/57572|journal=Indonesian Journal Of Educational Research and Review|volume=6|issue=1|pages=134–147|doi=10.23887/ijerr.v6i1.57572|issn=2621-8984}}</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature<ref>{{Cite journal|last=Thompson|first=Neil|last2=Hanley|first2=Douglas|date=2017|title=Science Is Shaped by Wikipedia: Evidence from a Randomized Control Trial|url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3039505|journal=SSRN Electronic Journal|doi=10.2139/ssrn.3039505|issn=1556-5068}}</ref> and that some scholars cite directly Wikipedia<ref>{{Cite journal|last=Dooley|first=Patricia L.|date=2010-07-07|title=Wikipedia and the two-faced professoriate|url=https://doi.org/10.1145/1832772.1832803|journal=Proceedings of the 6th International Symposium on Wikis and Open Collaboration|series=WikiSym '10|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=1–2|doi=10.1145/1832772.1832803|isbn=978-1-4503-0056-8}}</ref>. However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives<ref>{{Cite journal|last=Chen|first=Yan|last2=Farzan|first2=Rosta|last3=Kraut|first3=Robert|last4=YeckehZaare|first4=Iman|last5=Zhang|first5=Ark Fangzhou|date=2024-05|title=Motivating Experts to Contribute to Digital Public Goods: A Personalized Field Experiment on Wikipedia|url=https://pubsonline.informs.org/doi/10.1287/mnsc.2023.4852|journal=Management Science|volume=70|issue=5|pages=3264–3280|doi=10.1287/mnsc.2023.4852|issn=0025-1909}}</ref>,<ref>{{Cite journal|last=Kincaid|first=Dustin W.|last2=Beck|first2=Whitney S.|last3=Brandt|first3=Jessica E.|last4=Mars Brisbin|first4=Margaret|last5=Farrell|first5=Kaitlin J.|last6=Hondula|first6=Kelly L.|last7=Larson|first7=Erin I.|last8=Shogren|first8=Arial J.|date=2021|title=Wikipedia can help resolve information inequality in the aquatic sciences|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/lol2.10168|journal=Limnology and Oceanography Letters|language=en|volume=6|issue=1|pages=18–23|doi=10.1002/lol2.10168|issn=2378-2242}}</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite journal|last=Ceci|first=Stephen J.|last2=Ginther|first2=Donna K.|last3=Kahn|first3=Shulamit|last4=Williams|first4=Wendy M.|date=2014-12-01|title=Women in Academic Science: A Changing Landscape|url=https://doi.org/10.1177/1529100614541236|journal=Psychological Science in the Public Interest|language=EN|volume=15|issue=3|pages=75–141|doi=10.1177/1529100614541236|issn=1529-1006}}</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite journal|last=Lam|first=Shyong (Tony) K.|last2=Uduwage|first2=Anuradha|last3=Dong|first3=Zhenhua|last4=Sen|first4=Shilad|last5=Musicant|first5=David R.|last6=Terveen|first6=Loren|last7=Riedl|first7=John|date=2011-10-03|title=WP:clubhouse?: an exploration of Wikipedia's gender imbalance|url=https://dl.acm.org/doi/10.1145/2038558.2038560|language=en|publisher=ACM|pages=1–10|doi=10.1145/2038558.2038560|isbn=978-1-4503-0909-7}}</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name=":20">{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|doi=10.1016/J.ERSS.2021.102444}}</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name=":18" />. They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name=":4" /> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name=":0" />). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only statements using a specitic source in order to map the content of a single academic article. First test here: https://w.wiki/PFqH *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} 0z72zys338k4mc9k4lavth1tk7fixpt 2835183 2835179 2026-09-30T13:15:02Z Jeanne Noiraud 1366702 /* Filter statements */ 2835183 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite journal|last=Elliott|first=Julian H.|last2=Synnot|first2=Anneliese|last3=Turner|first3=Tari|last4=Simmonds|first4=Mark|last5=Akl|first5=Elie A.|last6=McDonald|first6=Steve|last7=Salanti|first7=Georgia|last8=Meerpohl|first8=Joerg|last9=MacLehose|first9=Harriet|date=2017-11|title=Living systematic review: 1. Introduction—the why, what, when, and how|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435617306364|journal=Journal of Clinical Epidemiology|volume=91|pages=23–30|doi=10.1016/j.jclinepi.2017.08.010|issn=0895-4356}}</ref>,<ref>{{Cite journal|last=Uttley|first=Lesley|last2=Quintana|first2=Daniel S.|last3=Montgomery|first3=Paul|last4=Carroll|first4=Christopher|last5=Page|first5=Matthew J.|last6=Falzon|first6=Louise|last7=Sutton|first7=Anthea|last8=Moher|first8=David|date=2023-04|title=The problems with systematic reviews: a living systematic review|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435623000112|journal=Journal of Clinical Epidemiology|volume=156|pages=30–41|doi=10.1016/j.jclinepi.2023.01.011|issn=0895-4356}}</ref>,<ref name=":18">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful<ref>{{Cite journal|last=Haley|first=Usha C. V.|date=2023-09-01|title=Triviality and the Search for Scholarly Impact|url=https://doi.org/10.1177/01708406231175292|journal=Organization Studies|language=EN|volume=44|issue=9|pages=1547–1550|doi=10.1177/01708406231175292|issn=0170-8406}}</ref>. Wikipedia is a key knowledge dissemination platform widely used by students<ref>{{Cite journal|last=Sunvy|first=Ahmed Shafkat|last2=Reza|first2=Raiyan Bin|date=2023-04-12|title=Students’ Perception of Wikipedia as an Academic Information Source|url=https://ejournal.undiksha.ac.id/index.php/IJERR/article/view/57572|journal=Indonesian Journal Of Educational Research and Review|volume=6|issue=1|pages=134–147|doi=10.23887/ijerr.v6i1.57572|issn=2621-8984}}</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature<ref>{{Cite journal|last=Thompson|first=Neil|last2=Hanley|first2=Douglas|date=2017|title=Science Is Shaped by Wikipedia: Evidence from a Randomized Control Trial|url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3039505|journal=SSRN Electronic Journal|doi=10.2139/ssrn.3039505|issn=1556-5068}}</ref> and that some scholars cite directly Wikipedia<ref>{{Cite journal|last=Dooley|first=Patricia L.|date=2010-07-07|title=Wikipedia and the two-faced professoriate|url=https://doi.org/10.1145/1832772.1832803|journal=Proceedings of the 6th International Symposium on Wikis and Open Collaboration|series=WikiSym '10|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=1–2|doi=10.1145/1832772.1832803|isbn=978-1-4503-0056-8}}</ref>. However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives<ref>{{Cite journal|last=Chen|first=Yan|last2=Farzan|first2=Rosta|last3=Kraut|first3=Robert|last4=YeckehZaare|first4=Iman|last5=Zhang|first5=Ark Fangzhou|date=2024-05|title=Motivating Experts to Contribute to Digital Public Goods: A Personalized Field Experiment on Wikipedia|url=https://pubsonline.informs.org/doi/10.1287/mnsc.2023.4852|journal=Management Science|volume=70|issue=5|pages=3264–3280|doi=10.1287/mnsc.2023.4852|issn=0025-1909}}</ref>,<ref>{{Cite journal|last=Kincaid|first=Dustin W.|last2=Beck|first2=Whitney S.|last3=Brandt|first3=Jessica E.|last4=Mars Brisbin|first4=Margaret|last5=Farrell|first5=Kaitlin J.|last6=Hondula|first6=Kelly L.|last7=Larson|first7=Erin I.|last8=Shogren|first8=Arial J.|date=2021|title=Wikipedia can help resolve information inequality in the aquatic sciences|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/lol2.10168|journal=Limnology and Oceanography Letters|language=en|volume=6|issue=1|pages=18–23|doi=10.1002/lol2.10168|issn=2378-2242}}</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite journal|last=Ceci|first=Stephen J.|last2=Ginther|first2=Donna K.|last3=Kahn|first3=Shulamit|last4=Williams|first4=Wendy M.|date=2014-12-01|title=Women in Academic Science: A Changing Landscape|url=https://doi.org/10.1177/1529100614541236|journal=Psychological Science in the Public Interest|language=EN|volume=15|issue=3|pages=75–141|doi=10.1177/1529100614541236|issn=1529-1006}}</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite journal|last=Lam|first=Shyong (Tony) K.|last2=Uduwage|first2=Anuradha|last3=Dong|first3=Zhenhua|last4=Sen|first4=Shilad|last5=Musicant|first5=David R.|last6=Terveen|first6=Loren|last7=Riedl|first7=John|date=2011-10-03|title=WP:clubhouse?: an exploration of Wikipedia's gender imbalance|url=https://dl.acm.org/doi/10.1145/2038558.2038560|language=en|publisher=ACM|pages=1–10|doi=10.1145/2038558.2038560|isbn=978-1-4503-0909-7}}</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name=":20">{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|doi=10.1016/J.ERSS.2021.102444}}</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name=":18" />. They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name=":4" /> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name=":0" />). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} coxde0rtwjj4djar6x8eows4edh3mim 2835184 2835183 2026-09-30T13:18:37Z Amélie E. Pereira 3042711 /* The problem of knowledge synthesis */ 2835184 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref>,<ref>{{Cite Q|Q134545630}}.</ref>,<ref name=":18">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful<ref>{{Cite journal|last=Haley|first=Usha C. V.|date=2023-09-01|title=Triviality and the Search for Scholarly Impact|url=https://doi.org/10.1177/01708406231175292|journal=Organization Studies|language=EN|volume=44|issue=9|pages=1547–1550|doi=10.1177/01708406231175292|issn=0170-8406}}</ref>. Wikipedia is a key knowledge dissemination platform widely used by students<ref>{{Cite journal|last=Sunvy|first=Ahmed Shafkat|last2=Reza|first2=Raiyan Bin|date=2023-04-12|title=Students’ Perception of Wikipedia as an Academic Information Source|url=https://ejournal.undiksha.ac.id/index.php/IJERR/article/view/57572|journal=Indonesian Journal Of Educational Research and Review|volume=6|issue=1|pages=134–147|doi=10.23887/ijerr.v6i1.57572|issn=2621-8984}}</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature<ref>{{Cite journal|last=Thompson|first=Neil|last2=Hanley|first2=Douglas|date=2017|title=Science Is Shaped by Wikipedia: Evidence from a Randomized Control Trial|url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3039505|journal=SSRN Electronic Journal|doi=10.2139/ssrn.3039505|issn=1556-5068}}</ref> and that some scholars cite directly Wikipedia<ref>{{Cite journal|last=Dooley|first=Patricia L.|date=2010-07-07|title=Wikipedia and the two-faced professoriate|url=https://doi.org/10.1145/1832772.1832803|journal=Proceedings of the 6th International Symposium on Wikis and Open Collaboration|series=WikiSym '10|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=1–2|doi=10.1145/1832772.1832803|isbn=978-1-4503-0056-8}}</ref>. However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives<ref>{{Cite journal|last=Chen|first=Yan|last2=Farzan|first2=Rosta|last3=Kraut|first3=Robert|last4=YeckehZaare|first4=Iman|last5=Zhang|first5=Ark Fangzhou|date=2024-05|title=Motivating Experts to Contribute to Digital Public Goods: A Personalized Field Experiment on Wikipedia|url=https://pubsonline.informs.org/doi/10.1287/mnsc.2023.4852|journal=Management Science|volume=70|issue=5|pages=3264–3280|doi=10.1287/mnsc.2023.4852|issn=0025-1909}}</ref>,<ref>{{Cite journal|last=Kincaid|first=Dustin W.|last2=Beck|first2=Whitney S.|last3=Brandt|first3=Jessica E.|last4=Mars Brisbin|first4=Margaret|last5=Farrell|first5=Kaitlin J.|last6=Hondula|first6=Kelly L.|last7=Larson|first7=Erin I.|last8=Shogren|first8=Arial J.|date=2021|title=Wikipedia can help resolve information inequality in the aquatic sciences|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/lol2.10168|journal=Limnology and Oceanography Letters|language=en|volume=6|issue=1|pages=18–23|doi=10.1002/lol2.10168|issn=2378-2242}}</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite journal|last=Ceci|first=Stephen J.|last2=Ginther|first2=Donna K.|last3=Kahn|first3=Shulamit|last4=Williams|first4=Wendy M.|date=2014-12-01|title=Women in Academic Science: A Changing Landscape|url=https://doi.org/10.1177/1529100614541236|journal=Psychological Science in the Public Interest|language=EN|volume=15|issue=3|pages=75–141|doi=10.1177/1529100614541236|issn=1529-1006}}</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite journal|last=Lam|first=Shyong (Tony) K.|last2=Uduwage|first2=Anuradha|last3=Dong|first3=Zhenhua|last4=Sen|first4=Shilad|last5=Musicant|first5=David R.|last6=Terveen|first6=Loren|last7=Riedl|first7=John|date=2011-10-03|title=WP:clubhouse?: an exploration of Wikipedia's gender imbalance|url=https://dl.acm.org/doi/10.1145/2038558.2038560|language=en|publisher=ACM|pages=1–10|doi=10.1145/2038558.2038560|isbn=978-1-4503-0909-7}}</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name=":20">{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|doi=10.1016/J.ERSS.2021.102444}}</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name=":18" />. They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name=":4" /> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name=":0" />). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} alfcbniymi8ptkmzrykotsqxirwjlqv 2835185 2835184 2026-09-30T13:25:02Z Amélie E. Pereira 3042711 2835185 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref>,<ref>{{Cite Q|Q134545630}}.</ref>,<ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful<ref>{{Cite journal|last=Haley|first=Usha C. V.|date=2023-09-01|title=Triviality and the Search for Scholarly Impact|url=https://doi.org/10.1177/01708406231175292|journal=Organization Studies|language=EN|volume=44|issue=9|pages=1547–1550|doi=10.1177/01708406231175292|issn=0170-8406}}</ref>. Wikipedia is a key knowledge dissemination platform widely used by students<ref>{{Cite journal|last=Sunvy|first=Ahmed Shafkat|last2=Reza|first2=Raiyan Bin|date=2023-04-12|title=Students’ Perception of Wikipedia as an Academic Information Source|url=https://ejournal.undiksha.ac.id/index.php/IJERR/article/view/57572|journal=Indonesian Journal Of Educational Research and Review|volume=6|issue=1|pages=134–147|doi=10.23887/ijerr.v6i1.57572|issn=2621-8984}}</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature<ref>{{Cite journal|last=Thompson|first=Neil|last2=Hanley|first2=Douglas|date=2017|title=Science Is Shaped by Wikipedia: Evidence from a Randomized Control Trial|url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3039505|journal=SSRN Electronic Journal|doi=10.2139/ssrn.3039505|issn=1556-5068}}</ref> and that some scholars cite directly Wikipedia<ref>{{Cite journal|last=Dooley|first=Patricia L.|date=2010-07-07|title=Wikipedia and the two-faced professoriate|url=https://doi.org/10.1145/1832772.1832803|journal=Proceedings of the 6th International Symposium on Wikis and Open Collaboration|series=WikiSym '10|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=1–2|doi=10.1145/1832772.1832803|isbn=978-1-4503-0056-8}}</ref>. However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives<ref>{{Cite journal|last=Chen|first=Yan|last2=Farzan|first2=Rosta|last3=Kraut|first3=Robert|last4=YeckehZaare|first4=Iman|last5=Zhang|first5=Ark Fangzhou|date=2024-05|title=Motivating Experts to Contribute to Digital Public Goods: A Personalized Field Experiment on Wikipedia|url=https://pubsonline.informs.org/doi/10.1287/mnsc.2023.4852|journal=Management Science|volume=70|issue=5|pages=3264–3280|doi=10.1287/mnsc.2023.4852|issn=0025-1909}}</ref>,<ref>{{Cite journal|last=Kincaid|first=Dustin W.|last2=Beck|first2=Whitney S.|last3=Brandt|first3=Jessica E.|last4=Mars Brisbin|first4=Margaret|last5=Farrell|first5=Kaitlin J.|last6=Hondula|first6=Kelly L.|last7=Larson|first7=Erin I.|last8=Shogren|first8=Arial J.|date=2021|title=Wikipedia can help resolve information inequality in the aquatic sciences|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/lol2.10168|journal=Limnology and Oceanography Letters|language=en|volume=6|issue=1|pages=18–23|doi=10.1002/lol2.10168|issn=2378-2242}}</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite journal|last=Ceci|first=Stephen J.|last2=Ginther|first2=Donna K.|last3=Kahn|first3=Shulamit|last4=Williams|first4=Wendy M.|date=2014-12-01|title=Women in Academic Science: A Changing Landscape|url=https://doi.org/10.1177/1529100614541236|journal=Psychological Science in the Public Interest|language=EN|volume=15|issue=3|pages=75–141|doi=10.1177/1529100614541236|issn=1529-1006}}</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite journal|last=Lam|first=Shyong (Tony) K.|last2=Uduwage|first2=Anuradha|last3=Dong|first3=Zhenhua|last4=Sen|first4=Shilad|last5=Musicant|first5=David R.|last6=Terveen|first6=Loren|last7=Riedl|first7=John|date=2011-10-03|title=WP:clubhouse?: an exploration of Wikipedia's gender imbalance|url=https://dl.acm.org/doi/10.1145/2038558.2038560|language=en|publisher=ACM|pages=1–10|doi=10.1145/2038558.2038560|isbn=978-1-4503-0909-7}}</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name=":20">{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|doi=10.1016/J.ERSS.2021.102444}}</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="<ref name="Spadaroal2022">" />. They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name=":4" /> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name=":0" />). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} jxu25kurkmgwkgm287v52vfqy4quxev 2835186 2835185 2026-09-30T13:34:32Z Amélie E. Pereira 3042711 /* The problem of scientific results dissemination */ mef 2835186 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref>,<ref>{{Cite Q|Q134545630}}.</ref>,<ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite journal|last=Ceci|first=Stephen J.|last2=Ginther|first2=Donna K.|last3=Kahn|first3=Shulamit|last4=Williams|first4=Wendy M.|date=2014-12-01|title=Women in Academic Science: A Changing Landscape|url=https://doi.org/10.1177/1529100614541236|journal=Psychological Science in the Public Interest|language=EN|volume=15|issue=3|pages=75–141|doi=10.1177/1529100614541236|issn=1529-1006}}</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite journal|last=Lam|first=Shyong (Tony) K.|last2=Uduwage|first2=Anuradha|last3=Dong|first3=Zhenhua|last4=Sen|first4=Shilad|last5=Musicant|first5=David R.|last6=Terveen|first6=Loren|last7=Riedl|first7=John|date=2011-10-03|title=WP:clubhouse?: an exploration of Wikipedia's gender imbalance|url=https://dl.acm.org/doi/10.1145/2038558.2038560|language=en|publisher=ACM|pages=1–10|doi=10.1145/2038558.2038560|isbn=978-1-4503-0909-7}}</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name=":20">{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|doi=10.1016/J.ERSS.2021.102444}}</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="<ref name="Spadaroal2022">" />. They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name=":4" /> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name=":0" />). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} 532nm5jpambm08bm4o7qtj5l13jusez 2835187 2835186 2026-09-30T13:37:24Z Amélie E. Pereira 3042711 /* Wikimedia projects */ 2835187 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref>,<ref>{{Cite Q|Q134545630}}.</ref>,<ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite journal|last=Ceci|first=Stephen J.|last2=Ginther|first2=Donna K.|last3=Kahn|first3=Shulamit|last4=Williams|first4=Wendy M.|date=2014-12-01|title=Women in Academic Science: A Changing Landscape|url=https://doi.org/10.1177/1529100614541236|journal=Psychological Science in the Public Interest|language=EN|volume=15|issue=3|pages=75–141|doi=10.1177/1529100614541236|issn=1529-1006}}</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite journal|last=Lam|first=Shyong (Tony) K.|last2=Uduwage|first2=Anuradha|last3=Dong|first3=Zhenhua|last4=Sen|first4=Shilad|last5=Musicant|first5=David R.|last6=Terveen|first6=Loren|last7=Riedl|first7=John|date=2011-10-03|title=WP:clubhouse?: an exploration of Wikipedia's gender imbalance|url=https://dl.acm.org/doi/10.1145/2038558.2038560|language=en|publisher=ACM|pages=1–10|doi=10.1145/2038558.2038560|isbn=978-1-4503-0909-7}}</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name=":20">{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|doi=10.1016/J.ERSS.2021.102444}}</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name=":4" /> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name=":0" />). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} 35rnhxwjkasc95qhsrk9jlk9xlnfxfw 2835188 2835187 2026-09-30T13:44:59Z Amélie E. Pereira 3042711 /* The problem of knowledge synthesis */ 2835188 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite journal|last=Ceci|first=Stephen J.|last2=Ginther|first2=Donna K.|last3=Kahn|first3=Shulamit|last4=Williams|first4=Wendy M.|date=2014-12-01|title=Women in Academic Science: A Changing Landscape|url=https://doi.org/10.1177/1529100614541236|journal=Psychological Science in the Public Interest|language=EN|volume=15|issue=3|pages=75–141|doi=10.1177/1529100614541236|issn=1529-1006}}</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite journal|last=Lam|first=Shyong (Tony) K.|last2=Uduwage|first2=Anuradha|last3=Dong|first3=Zhenhua|last4=Sen|first4=Shilad|last5=Musicant|first5=David R.|last6=Terveen|first6=Loren|last7=Riedl|first7=John|date=2011-10-03|title=WP:clubhouse?: an exploration of Wikipedia's gender imbalance|url=https://dl.acm.org/doi/10.1145/2038558.2038560|language=en|publisher=ACM|pages=1–10|doi=10.1145/2038558.2038560|isbn=978-1-4503-0909-7}}</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name=":20">{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|doi=10.1016/J.ERSS.2021.102444}}</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name=":4" /> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name=":0" />). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} r8sl4rrzztr1g1jufqen62xty0php68 2835189 2835188 2026-09-30T13:47:26Z Amélie E. Pereira 3042711 /* The problem of scientific results dissemination */ mef 2835189 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name=":20">{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|doi=10.1016/J.ERSS.2021.102444}}</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name=":4" /> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name=":0" />). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} 4i8gdedydpp12q9x5a2t3dtf9svk6ju 2835190 2835189 2026-09-30T14:09:24Z Amélie E. Pereira 3042711 /* The problem of scientific results dissemination */ 2835190 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name=":20">{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|doi=10.1016/J.ERSS.2021.102444}}</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name=":4" /> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name=":0" />). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} 3s6g07vyma1ef745uua5ij2ogdlqw6v 2835191 2835190 2026-09-30T14:13:16Z Amélie E. Pereira 3042711 /* Just sustainability transition */ mef 2835191 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name=":3" /><ref name=":1" /><ref name=":4">{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name=":20">{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|doi=10.1016/J.ERSS.2021.102444}}</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name=":4" /> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name=":0" />). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} jiokd6o01od3hbnnrlluxkga7vzh1g9 2835192 2835191 2026-09-30T14:14:00Z Amélie E. Pereira 3042711 /* Database search */ 2835192 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name=":3" /><ref name=":1" /><ref name=":4">{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name=":20">{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|doi=10.1016/J.ERSS.2021.102444}}</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name=":4" /> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} lh0ycvo4hp0ssfzgqpa4kwemjknjw96 2835193 2835192 2026-09-30T14:20:17Z Amélie E. Pereira 3042711 /* Just sustainability transition */ mef 2835193 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name=":1" /><ref name=":4">{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name=":20">{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|doi=10.1016/J.ERSS.2021.102444}}</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name=":4" /> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} edu5j2e2hwufuof0yza8ptwkp934tvr 2835194 2835193 2026-09-30T14:22:46Z Amélie E. Pereira 3042711 /* Just sustainability transition */ 2835194 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name=":4">{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name=":20">{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|doi=10.1016/J.ERSS.2021.102444}}</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name=":4" /> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} 8egvxevoyxziydl1zzswak0wtgunkel 2835195 2835194 2026-09-30T14:25:10Z Amélie E. Pereira 3042711 /* Just sustainability transition */ 2835195 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name=":20">{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|doi=10.1016/J.ERSS.2021.102444}}</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name=":4" /> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} rbho29lg0yhqjg7j7twxegz8y83zuy3 2835196 2835195 2026-09-30T14:25:41Z Amélie E. Pereira 3042711 /* Database search */ 2835196 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name=":20">{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|doi=10.1016/J.ERSS.2021.102444}}</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} fldayjcy9k06w19zhs41z8pzyrw2m2m 2835197 2835196 2026-09-30T14:27:39Z Amélie E. Pereira 3042711 /* Just sustainability transition */ 2835197 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} b1tndsss34yrys5b4b2stxpvn58l4ry 2835198 2835197 2026-09-30T14:31:32Z Amélie E. Pereira 3042711 /* Contradictions */ 2835198 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} 27xbr8r4t3hfjktthojpk1skxg0p4qe 2835199 2835198 2026-09-30T15:11:14Z Amélie E. Pereira 3042711 /* Living reviews */ 2835199 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q |Q50084143}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} df6vaikml0fks9bm968vued3me1atff 2835200 2835199 2026-09-30T15:21:45Z Amélie E. Pereira 3042711 /* Living reviews */ 2835200 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} mf17osxupxnh83ygkgq60ifdy311lex 2835202 2835200 2026-09-30T15:30:30Z Amélie E. Pereira 3042711 /* The problem of knowledge synthesis */ 2835202 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} 384libq7guubs6q1jor1l3ikqyxr6sj 2835203 2835202 2026-09-30T15:31:11Z Amélie E. Pereira 3042711 /* Wikimedia projects */ 2835203 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} edn6h256c6995kndxy19wmond2pqy0w 2835204 2835203 2026-09-30T15:31:32Z Amélie E. Pereira 3042711 /* Wikimedia projects */ 2835204 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} gwycfz83wrkx108eimeln5pppks4ybz 2835205 2835204 2026-09-30T15:34:59Z Amélie E. Pereira 3042711 /* Living reviews */ 2835205 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name=":6" /><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} rrn4p4oftrcc2p80lnul3yot51ax849 2835207 2835205 2026-09-30T15:55:22Z Amélie E. Pereira 3042711 /* Living reviews */ 2835207 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name=":13" />. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} daozd6wfu0ooak0bvbatgybjihd4xua 2835208 2835207 2026-09-30T16:02:49Z Amélie E. Pereira 3042711 /* Living reviews */ 2835208 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} qxysi5zfoxefec2klraohugf6qubwww 2835209 2835208 2026-09-30T16:04:26Z Amélie E. Pereira 3042711 /* Living reviews */ 2835209 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, and a "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} qja221d649r6qi4xyy4tbnshf1kojhe 2835288 2835209 2026-10-01T08:43:27Z Amélie E. Pereira 3042711 /* Wikimedia projects */ 2835288 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name=":9">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph<ref name=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} 6en1a94olouzg68cic3875l4qb94mow 2835289 2835288 2026-10-01T08:44:21Z Amélie E. Pereira 3042711 2835289 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} smdhqjtr4c2xrspv7blfu0u57nctv8q 2835291 2835289 2026-10-01T08:47:39Z Amélie E. Pereira 3042711 /* Wikimedia projects */ 2835291 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} ki18d2poktyom1fzrmbgm1dfy4xpg19 2835292 2835291 2026-10-01T08:49:41Z Amélie E. Pereira 3042711 2835292 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref>{{Cite Q|Q141606483}}.</ref> Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} tjluw40iqabyopjmag611uwjs8witgk 2835293 2835292 2026-10-01T08:50:18Z Amélie E. Pereira 3042711 2835293 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</ref>. Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} esdbyl68uuijs5xrhsfjunaux2nl4by 2835294 2835293 2026-10-01T08:53:26Z Amélie E. Pereira 3042711 /* Wikimedia projects */ 2835294 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name=":25" /><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} nxtun7r58rv8g584vuqkgfe56s0yyv1 2835295 2835294 2026-10-01T08:53:58Z Amélie E. Pereira 3042711 2835295 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data<ref>{{Cite journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</ref>. Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} tht2rns7anumi562dv2o9v9lsp6vt54 2835296 2835295 2026-10-01T08:55:56Z Amélie E. Pereira 3042711 /* Wikimedia projects */ 2835296 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022<ref>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</ref>. It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} lvt8nuw409oabop6zby8g306d67b6pg 2835297 2835296 2026-10-01T08:57:15Z Amélie E. Pereira 3042711 /* Use of Wikidata and Wikiversity for research */ 2835297 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref>{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition. Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} bkqgchw13om0id2a2nzrhpcksx2izbg 2835298 2835297 2026-10-01T09:00:04Z Amélie E. Pereira 3042711 /* Use of Wikidata and Wikiversity for research */ 2835298 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} st5x64cn4fasswtghj97rq6gvk3gnn0 2835299 2835298 2026-10-01T09:00:46Z Amélie E. Pereira 3042711 /* Use of Wikidata and Wikiversity for research */ 2835299 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020)ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} 7qdto4b3ghb3nunbbqj98wxopus2ybe 2835300 2835299 2026-10-01T09:01:11Z Amélie E. Pereira 3042711 /* Use of Wikidata and Wikiversity for research */ 2835300 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies.The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services. Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation. / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} hvmnpq7ou5xqnkzqdojzq3ywgf2bd00 2835301 2835300 2026-10-01T09:04:24Z Amélie E. Pereira 3042711 /* Use of Wikidata and Wikiversity for research */ 2835301 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing <ref name=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines <ref name=":24" />. Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} goacgh2m8bjk17qatstduzh8tepwsc9 2835304 2835301 2026-10-01T09:18:57Z Amélie E. Pereira 3042711 /* Supporting inductive research */ 2835304 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</ref>. === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} i4cfsjikpne6uxu8gwmnnt04x0a3729 2835308 2835304 2026-10-01T09:49:04Z Amélie E. Pereira 3042711 /* Quality assessment */ 2835308 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite Q|Q28942543}}.</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} 17qusff0dq98cy8i60x3hnyk6da80gy 2835309 2835308 2026-10-01T09:50:36Z Amélie E. Pereira 3042711 /* Quality assessment */ 2835309 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps<ref>{{Cite journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</ref>. Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority." The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}</ref><ref>{{Cite Q|Q28942543}}.</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} 9wo33pifekddd0asfy30gqkg3otmuig 2835310 2835309 2026-10-01T09:51:59Z Amélie E. Pereira 3042711 /* Quality assessment */ 2835310 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}.</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}.</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} gsmrub3msm7b0wwqhqhf205d8g3j20c 2835311 2835310 2026-10-01T09:53:38Z Amélie E. Pereira 3042711 /* Quality assessment */ 2835311 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}.</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}.</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} 9j840x8nxsexm2yn7l5f16qxxsbqfwh 2835312 2835311 2026-10-01T09:54:53Z Amélie E. Pereira 3042711 /* Quality assessment */ 2835312 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite Q|Q107425133}}.</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}.</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}.</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} 8zdjpp581pogahxaz9wzt26luqo88g2 2835313 2835312 2026-10-01T09:55:52Z Amélie E. Pereira 3042711 /* Quality assessment */ 2835313 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints<ref>{{Cite Q|Q107425133}}.</ref>. Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}.</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}.</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} fij8yhj6wr9yhlzy2vj7uefc2dqoqlu 2835314 2835313 2026-10-01T09:56:29Z Amélie E. Pereira 3042711 /* Quality assessment */ 2835314 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion<ref>{{Cite journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</ref>. Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}.</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}.</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}.</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} 3xil2li24xwretzo8iary2jgf4v7oho 2835315 2835314 2026-10-01T09:58:43Z Amélie E. Pereira 3042711 /* Discussion */ 2835315 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles<ref>{{Cite web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</ref>. === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}.</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}.</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}.</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} qsfk8tl3341r23tyef8k4bmx7smx1jb 2835316 2835315 2026-10-01T10:02:25Z Amélie E. Pereira 3042711 /* Advantages of Wikiversity */ 2835316 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication<ref>{{Cite journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</ref>). The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}.</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}.</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}.</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} kwufp47jyjqslxwp7gybb8iw52oofjf 2835317 2835316 2026-10-01T10:03:45Z Amélie E. Pereira 3042711 /* Advantages of Wikiversity */ 2835317 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}.</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}.</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}.</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} nlxmtv2npax6mwh614ma0phomouggq4 2835318 2835317 2026-10-01T10:06:26Z Amélie E. Pereira 3042711 /* Knowledge modelling in Wikidata : second round of analysis */ 2835318 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references<ref>{{Cite journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</ref>.Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}.</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}.</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}.</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} kgkexkusp5d884p1k47ivlnrv2wf1nw 2835319 2835318 2026-10-01T10:11:04Z Amélie E. Pereira 3042711 2835319 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}.</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}.</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}.</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} inmaqxcqo1huniwpgv8th1ekif6yfls 2835320 2835319 2026-10-01T10:12:51Z Amélie E. Pereira 3042711 /* Conceptual modelling */ 2835320 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}.</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}.</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}.</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} h334b8qeeygiganth4ij2o2piy5zxp9 2 327236 2835278 2830271 2026-10-01T06:41:28Z Dick Bos 24466 WikiJournal 2835278 wikitext text/x-wiki &nbsp; [[File:On_Expedition_2015_MARBLE_Maastricht_University_2.JPG|thumb|Maastricht University, 2015-05-06. Explaining the principles of Wikipedia for students with [[User:Taketa]] (left) and [[User:Romaine]] (right)]] {{#babel:nl-N|en-3|de-2|fr-1}} &nbsp; My name is Dick Bos. I'm from the Netherlands. I work on the [[:w:nl:Gebruiker:Dick Bos|Dutch]] and [[en:User:Dick Bos|English]] wikipedia, on the English wikisource, on Wikimedia Commons etc. See my userpages there, please. * [[File:Wikipedia-logo-v2.svg|16px|alt=16 px Wikipedia logo]] Wikipedia: ** Dutch: [[w:nl:Gebruiker:Dick_Bos]] ** English: [[w:en:User:Dick Bos]] * [[Image:wikisource-logo.svg|16x16px]] WikiSource: ** [[s:en:User:Dick Bos|User:Dick Bos]] on en-ws [[m:User:Dick Bos/where|Click here]] for the most complete and up to date list of my userpages on Wikimedia-projects. &nbsp; My projects: * [[User:Dick Bos/Marx|Karl Marx]] (and Friedrich Engels) * [[User:Dick Bos/Ricardo|David Ricardo]] == Handy == * [[Help:Contents]] ([[WV:HELP]]) * [[Help:CSS at Wikiversity]] == Interesting == * [[WikiJournal of Humanities|WikiJournal (of Humanities)]] is hosted here on Wikiversity r6htv513r9jqt4e5vm2aqq5v5h59nxp 2 330795 2835272 2834457 2026-10-01T04:53:36Z U3285438 3103750 /* Social contributions */ +1 2835272 wikitext text/x-wiki == About me == Hello! My name is Zara (''she/her''). I am a '''third-year student''' at the [https://www.canberra.edu.au/ University of Canberra (UC)], studying a Bachelor of Science in Psychology with a Breadth Major in Counselling Studies. I am hoping to undertake postgraduate studies in [[wikipedia:Clinical_psychology|clinical psychology]], and I am particularly '''interested in working with children and adolescents'''. [[File:Canadian swimmer at 2019 international tournament.jpg|thumb|150x150px|'''Figure 1.''' As a competitive swimmer, my favourite stroke was butterfly. ]] I am currently undertaking the unit [[Motivation and emotion|Motivation and Emotion]] at UC. Some of my hobbies include: * Reading * [[wikipedia:Swimming|Swimming]] (see Figure 1) == Book chapter I'm working on == I am writing a book chapter on [[Motivation and emotion/Book/2026/Emotion dysregulation|emotion dysregulation]] for the [[Motivation and emotion/Book|Motivation and emotion book]] project. Through this chapter I will be exploring the question "what is emotion dysregulation, what are its consequences and how can it be managed?" My interest in this topic stems from my experience as a classroom support assistant in a primary school. Within this role, I work with young students to help build emotional literacy and support them in regulating their emotions. I am eager to further my understanding of emotion dysregulation and share this knowledge with others. == Social contributions == #[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/455261?entry_id=805511 Posted in a UCLearn discussion thread to share the areas of motivation and emotion I am interested in exploring this semester.] (18 Aug. 2026) #[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/455261?entry_id=805526 Responded to a peer's discussion post on UCLearn.] (18 Aug. 2026) #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FCancer_screening_and_emotion&diff=2823381&oldid=2762016 Fixed grammatical error to improve clarity.] (20 Aug. 2026) #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2021%2FTo-do_lists&diff=2823387&oldid=2672363 Made small stylistic correction in formatting.] (20 Aug. 2026) #[https://en.wikiversity.org/w/index.php?title=Talk%3AMotivation_and_emotion%2FBook%2F2025%2FPain_avoidance_motivation&diff=2823539&oldid=2758910 Recommended a relevant book chapter for inclusion in the 'See also' section.] (20 Aug. 2026) #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FCoercive_control_in_intimate_partner_violence&diff=2825669&oldid=2811025 Edited a past book chapter's ''See also'' section to include a missing source citation in parentheses after the relevant link.] (25 Aug. 2026) #[https://en.wikiversity.org/w/index.php?title=Talk%3AMotivation_and_emotion%2FBook%2F2026%2FBuilding_therapeutic_alliance&diff=2830378&oldid=2829992 Offered a relevant therapeutic framework that could be included in my peer's book chapter.] (02 Sept. 2026) #[[Talk:Motivation and emotion/Book/2026/Fear extinction#c-U3285438-20260902052100-Food for thought: Integrating Pavlov's classical conditioning|Suggested integrating a relevant theory to help contextualise key concepts in my peer's book chapter.]] (02 Sept. 2026) #[[Talk:Motivation and emotion/Book/2026/Sun exposure and protection motivation#c-U3285438-20260903051900-Food for thought: The health belief model|Suggested including a relevant theory (the health belief model) in my peer's book chapter as an additional lens for understanding health behaviour change]] (03 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FExtended_process_model_of_emotion_regulation&diff=2832166&oldid=2830650 Added the recommended ''External links'' heading to a peer's book chapter through a direct edit.] (08 Sept. 2026) #[[Talk:Motivation and emotion/Book/2026/Extended process model of emotion regulation#c-U3285438-20260908043300-Recommendation for 'see also' section|Provided feedback on a book chapter's talk page. Recommended relocating the current ''See also'' links to the ''External links'' section and suggested a relevant chapter as an alternative.]] (08 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FCompetence_motivation_in_self-determination_theory&diff=2832537&oldid=2831095 Added the recommended ''See also'' heading to a peer's book chapter through a direct edit.] (10 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Talk%3AMotivation_and_emotion%2FBook%2F2026%2FCompetence_motivation_in_self-determination_theory&diff=2832538&oldid=2830994 Suggested a relevant book chapter to link in the ''See also'' section via the book chapter's talk page]. (10 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FHypothalamus_and_homeostatic_motivation&diff=2833547&oldid=2831670 Added bullet points to a book chapter's focus questions through a direct edit] (17 Sept. 2026) #[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457901?entry_id=818681 Provided constructive feedback on the use of headings in a peer's book chapter (UCLearn discussion post)] (17 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Talk%3AMotivation_and_emotion%2FBook%2F2026%2FRomantic_entertainment_and_love_beliefs&diff=2833564&oldid=2833099 Recommended relevant resources to include in the ''External links'' section] (17 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2023%2FLong-term_injury_in_high_performance_field_athletes_and_emotion&diff=2834436&oldid=2577971 Copyediting - corrected spelling error in subheading] (25 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Talk%3AMotivation_and_emotion%2FBook%2F2026%2FAthletic_identity_loss_and_returning_to_sport_after_injury&diff=2834437&oldid=2832726 Suggestion for ''See also'' section] (25 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FImpulsivity_versus_sensation-seeking&diff=2834441&oldid=2833140 Added bullet points to a book chapter's focus questions through a direct edit] (25 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FMindsets_and_stigma&diff=2834447&oldid=2833565 Added bullet points to another book chapter's focus questions through a direct edit] (25 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Talk%3AMotivation_and_emotion%2FBook%2F2026%2FMindsets_and_stigma&diff=2834455&oldid=2829318 Recommendations for ''External links'' section] (25 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FMindsets_and_stigma&diff=2834456&oldid=2834447 Fixed feature box syntax] (25 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Talk%3AMotivation_and_emotion%2FBook%2F2026%2FParental_motivations_for_homeschooling&diff=2835271&oldid=2834378 Resource recommendations] (1 Oct. 2026) nk3m3hjtlq684xyf3nlwvl6jspi1nzp 2835274 2835272 2026-10-01T05:03:41Z U3285438 3103750 /* Social contributions */ +1 2835274 wikitext text/x-wiki == About me == Hello! My name is Zara (''she/her''). I am a '''third-year student''' at the [https://www.canberra.edu.au/ University of Canberra (UC)], studying a Bachelor of Science in Psychology with a Breadth Major in Counselling Studies. I am hoping to undertake postgraduate studies in [[wikipedia:Clinical_psychology|clinical psychology]], and I am particularly '''interested in working with children and adolescents'''. [[File:Canadian swimmer at 2019 international tournament.jpg|thumb|150x150px|'''Figure 1.''' As a competitive swimmer, my favourite stroke was butterfly. ]] I am currently undertaking the unit [[Motivation and emotion|Motivation and Emotion]] at UC. Some of my hobbies include: * Reading * [[wikipedia:Swimming|Swimming]] (see Figure 1) == Book chapter I'm working on == I am writing a book chapter on [[Motivation and emotion/Book/2026/Emotion dysregulation|emotion dysregulation]] for the [[Motivation and emotion/Book|Motivation and emotion book]] project. Through this chapter I will be exploring the question "what is emotion dysregulation, what are its consequences and how can it be managed?" My interest in this topic stems from my experience as a classroom support assistant in a primary school. Within this role, I work with young students to help build emotional literacy and support them in regulating their emotions. I am eager to further my understanding of emotion dysregulation and share this knowledge with others. == Social contributions == #[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/455261?entry_id=805511 Posted in a UCLearn discussion thread to share the areas of motivation and emotion I am interested in exploring this semester.] (18 Aug. 2026) #[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/455261?entry_id=805526 Responded to a peer's discussion post on UCLearn.] (18 Aug. 2026) #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FCancer_screening_and_emotion&diff=2823381&oldid=2762016 Fixed grammatical error to improve clarity.] (20 Aug. 2026) #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2021%2FTo-do_lists&diff=2823387&oldid=2672363 Made small stylistic correction in formatting.] (20 Aug. 2026) #[https://en.wikiversity.org/w/index.php?title=Talk%3AMotivation_and_emotion%2FBook%2F2025%2FPain_avoidance_motivation&diff=2823539&oldid=2758910 Recommended a relevant book chapter for inclusion in the 'See also' section.] (20 Aug. 2026) #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FCoercive_control_in_intimate_partner_violence&diff=2825669&oldid=2811025 Edited a past book chapter's ''See also'' section to include a missing source citation in parentheses after the relevant link.] (25 Aug. 2026) #[https://en.wikiversity.org/w/index.php?title=Talk%3AMotivation_and_emotion%2FBook%2F2026%2FBuilding_therapeutic_alliance&diff=2830378&oldid=2829992 Offered a relevant therapeutic framework that could be included in my peer's book chapter.] (02 Sept. 2026) #[[Talk:Motivation and emotion/Book/2026/Fear extinction#c-U3285438-20260902052100-Food for thought: Integrating Pavlov's classical conditioning|Suggested integrating a relevant theory to help contextualise key concepts in my peer's book chapter.]] (02 Sept. 2026) #[[Talk:Motivation and emotion/Book/2026/Sun exposure and protection motivation#c-U3285438-20260903051900-Food for thought: The health belief model|Suggested including a relevant theory (the health belief model) in my peer's book chapter as an additional lens for understanding health behaviour change]] (03 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FExtended_process_model_of_emotion_regulation&diff=2832166&oldid=2830650 Added the recommended ''External links'' heading to a peer's book chapter through a direct edit.] (08 Sept. 2026) #[[Talk:Motivation and emotion/Book/2026/Extended process model of emotion regulation#c-U3285438-20260908043300-Recommendation for 'see also' section|Provided feedback on a book chapter's talk page. Recommended relocating the current ''See also'' links to the ''External links'' section and suggested a relevant chapter as an alternative.]] (08 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FCompetence_motivation_in_self-determination_theory&diff=2832537&oldid=2831095 Added the recommended ''See also'' heading to a peer's book chapter through a direct edit.] (10 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Talk%3AMotivation_and_emotion%2FBook%2F2026%2FCompetence_motivation_in_self-determination_theory&diff=2832538&oldid=2830994 Suggested a relevant book chapter to link in the ''See also'' section via the book chapter's talk page]. (10 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FHypothalamus_and_homeostatic_motivation&diff=2833547&oldid=2831670 Added bullet points to a book chapter's focus questions through a direct edit] (17 Sept. 2026) #[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457901?entry_id=818681 Provided constructive feedback on the use of headings in a peer's book chapter (UCLearn discussion post)] (17 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Talk%3AMotivation_and_emotion%2FBook%2F2026%2FRomantic_entertainment_and_love_beliefs&diff=2833564&oldid=2833099 Recommended relevant resources to include in the ''External links'' section] (17 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2023%2FLong-term_injury_in_high_performance_field_athletes_and_emotion&diff=2834436&oldid=2577971 Copyediting - corrected spelling error in subheading] (25 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Talk%3AMotivation_and_emotion%2FBook%2F2026%2FAthletic_identity_loss_and_returning_to_sport_after_injury&diff=2834437&oldid=2832726 Suggestion for ''See also'' section] (25 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FImpulsivity_versus_sensation-seeking&diff=2834441&oldid=2833140 Added bullet points to a book chapter's focus questions through a direct edit] (25 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FMindsets_and_stigma&diff=2834447&oldid=2833565 Added bullet points to another book chapter's focus questions through a direct edit] (25 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Talk%3AMotivation_and_emotion%2FBook%2F2026%2FMindsets_and_stigma&diff=2834455&oldid=2829318 Recommendations for ''External links'' section] (25 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FMindsets_and_stigma&diff=2834456&oldid=2834447 Fixed feature box syntax] (25 Sept. 2026) #[https://en.wikiversity.org/w/index.php?title=Talk%3AMotivation_and_emotion%2FBook%2F2026%2FParental_motivations_for_homeschooling&diff=2835271&oldid=2834378 Resource recommendations] (1 Oct. 2026) #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FParental_motivations_for_homeschooling&diff=2835273&oldid=2834379 Shifted figure to the right and updated caption] (1 Oct. 2026) ozkvq0jy861ie7iphlb1pscyxubwodb 0 330824 2835264 2832412 2026-10-01T03:25:03Z ~2026-52775-69 3111915 /* Sources of Alcohol */ cv 2835264 wikitext text/x-wiki = Bartending Basics = What is a [[wikipedia:Bartender|bartender]]? At its simplest, a bartender serves drinks at a bar. In reality, a bartender selects, mixes, pours, and serves drinks while hosting patrons and creating a hospitable atmosphere at a bar, pub, restaurant, nightclub, living room or [[wikipedia:Parking_lot|parking lot]]. A bartender must have a variety of skills, both technical and interpersonal in order to be successful. A bartender can work in many locations, but this course will focus on bartenders that tend to tend in bars. This lesson covers: # [[Bartending/Bartending Basics#Sources of Alcohol|Sources of Alcohol]] # [[Bartending/Bartending Basics#Types of Alcohol|Types of Alcohol]] # [[Bartending/Bartending Basics#Tools of Bartending|Tools of Bartending]] # [[Bartending/Bartending Basics#Safety|Safety]] == Sources of Alcohol == Behind the bar, you are the expert in the room on alcohol. While no one can claim to know everything on alcohol, it's important to have the basics. This and the next lesson focus on learning what alcohol is and what kind of drinks and liquors are made with it. Every alcoholic drink you've ever had has included the same basic type of alcohol: '''[[wikipedia:Ethanol|ethanol]]'''. Ethanol is one of the three alcohols and the only one that humans can safely drink. All alcoholic beverages (be it beer, wine or a spirit) contain ethanol. There are hundreds of different beverages and liquors that are served at bars around the world. The method of refining raw ingredients into a final product with ethanol is what distinguishes each type of beverage. Fortunately they're all related to each other (since they all contain ethanol) and have some major categories to guide us in understanding what they are. The first step to make any type of alcohol is [[wikipedia:fermentation|fermentation]]. === Fermentation === [[File:40168_2022_1274_Fig6.webp|thumb|People get very scientific with it.]] Using a process that has existed for thousands of years, we can employ a fungus called [[wikipedia:Yeast#Uses|yeast]] to create alcohol. This process is called fermentation. At its base, fermentation for alcohol production is the process of using yeast to convert sugars to ethanol. "Sugars" is intentionally plural. There are many places you can find sugar suitable for fermentation, and you can derive sugar from grains, fruits and vegetables. The source of the sugar is often what defines what type of final alcoholic beverage you get. We'll talk more on how fermenting different materials yields different drinks in a moment. Fermentation happens in a couple of steps. # '''Mashing''': Grains like barley or rice are milled into a coarse flour and fruits are mashed into a pulp. These are sometimes mixed with hot water, where enzymes convert starches to sugars. For beer, this mash is then often boiled. # '''Fermentation''': The mash is transferred to a fermentation vessel. Yeast is added, and fermentation begins. Over a varying period of time (often 5-10 days), yeast consumes the sugars, producing alcohol and carbon dioxide. This is called primary fermentation. # '''Conditioning and Packaging''': After primary fermentation, there is often secondary fermentation or conditioning to add or mature flavors and to clarify. It’s then sometimes carbonated and packaged. Now fermented, there is some amount of alcohol in your drink. But what if ''some'' isn't enough? A secondary process called [[wikipedia:Distillation|distillation]] allowed for fermented drinks and solutions to be concentrated into spirits. === Distillation === [[File:Alambins_industrials_per_a_la_destil·lació_de_licors_a_Catalunya.jpg|left|thumb|Industrial stills for liquor production in Catalonia]] Distillation is a process by which brewers can concentrate the level of alcohol in a drink. Fermentation alone cannot make alcohol concentrations like that of vodka or gin. To reach that level of concentration, [[wiktionary:distiller|distillers]] (referring to both the apparatus that distills and the person that runs it) can boil off and collect the alcohol produced by fermentation. Distillation happens in a few steps: # The fermented substance is placed into a vessel called a [[wikipedia:Still|still]] (this is where di''still''ation gets its name). # The ferment is heated slowly from room temperature until it reaches the boiling point of ethanol. The boiling point of ethanol is lower than the boiling point of water, so the ethanol will vaporize, leaving the water behind. # The ethanol vapor rises through a column until it reaches the condenser. In the condenser, the vapor makes contact with the a cold surface that cools it back into a liquid state. # The ethanol is collected, and the process is often repeated to further concentrate and purify the result. Sometimes the process is done without having to stop and restart in a process called continuous distillation. The result of distillation is a liquor with a higher amount of alcohol by volume (ABV) than before. === Alcohol By Volume === The amount of alcohol in a drink is calculated based on the percent of ethanol compared to non-ethanol in the total beverage, which is called Alcohol by Volume or ABV for short. For example, if a beverage has an ABV of 50%, half of liquid in the drink will be ethanol and the other half will be everything else. ABV is important to understand, because it is the basis of drinking and serving drinks safely as well as how many drinks are categorized. While all alcohol is made through fermentation, the process of fermentation alone can only create a concentration of alcohol of about 5% to 20% ABV. Spirits are generally distilled liquids that have a higher ABV (20% or more, as high as 95%). This distinction lower-ABV drinks like wine, beer and cider versus higher-ABV spirits like vodka, gin and whiskey. == Types of Alcohol == Fermentation and distilling are the core of all alcohol production, but there many more ways that brewers and distillers affect their final product. This incredible flow chart shows many of the processes of fermentation, distillation, carbonation, ageing and processing that make different alcoholic drinks. Take a look at it and compare the different starting ingredients with each other, and then compare the starting ingredients with their final products. [[File:Alcohol_Flow_Chart.svg|center|frame|Alcohol Flow Chart]] There is so much to learn about alcohol, and while you should be knowledgeable on the different types, you by no means need to be an expert (see: sommelier) to be a bartender. Below follows an overview of each family of alcohol, but if you want to learn more you can click on the links to Wikipedia pages in each subsection below, or I recommend browsing the [[wikipedia:Portal:Liquor|Liquor Portal]] to view all that Wikipedia has to offer. Hopefully it's easier to see now how beverages and spirits can both be categorized based on what they're fermented from and how concentrated their alcohol content is. Let's use these categories to talk more about each major type of alcohol. === Wine, Beer and Cider (Low-ABV Drinks) === ==== Wine ==== We call fermented grape juice [[wikipedia:wine|wine]]. Yeast is added to pressed grapes to develop it into one of four types: [[wikipedia:Red_wine|red]], [[wikipedia:white_wine|white]], [[wikipedia:rose_wine|rosé]], and [[wikipedia:Orange_wine|orange]]. The type of grape and the duration of the contact with the skins of the grapes help to define which type of wine is produced. The table below is from the Wikipedia page on wine. {| class="wikitable" |+Colors of wine ! !Long contact with grape skins !Short contact with grape skins |- !Red grapes |'''''Red wine''''', made from dark-colored red grape varieties. The actual color of the wine can range from dark pink to almost black. The juice from red grapes is actually pale gray; the color of red wine and some of its flavor (notably tannins) comes from phenolics in the skin, seeds and stem fragments of the grape, extracted by allowing the grapes to soak in the juice. |'''''Rosé wine''''', which gains color from red grape skins, but not enough to qualify it as a red wine. The color can range from a very pale pink to pale red. There are two primary ways to produce rosé wine. The preferred technique is allowing a short period of maceration after crushing red grapes, which extracts a certain amount of color. The juice is then fermented like a white wine. An alternative is blending a small amount of finished red wine into finished white wine. |- !White grapes |'''''Orange wine''''', sometimes called amber wine, is made with white grapes but with the skins allowed to macerate during and beyond fermentation, similar to red wine production. This results in their darker color compared to white wines, and produces a deliberately astringent result. |'''''White wine''''', typically made from white grape varieties (those with yellow or green skins), and range from practically colorless to golden. When skin contact is used, to improve the flavor or to increase the body or aging potential, it is usually limited to between four and 24 hours; any longer leads to bitterness. |} ''Common names: There are thousands of wine varietals. Red wines like Cabernet Sauvignon, Merlot, Pinot Noir, Malbec, Zinfandel; white wines like Chardonnay, Sauvignon Blanc, Pinot Grigio, Riesling; and rosé wines like Provence, White Zinfandel and Pink Moscato.'' In addition to the colors of wine, wine can be [[wikipedia:Sparkling_wine|sparkling]] or still. Wine can also be [[wikipedia:Fortified_wine|fortified]]. Fortifying a wine is the process of adding a distilled spirit to the fermented wine. ''Common names: Sparkling wine includes Champagne, Prosecco and other Brut wines. Fortified wines include Port, Sherry and Vermouth.'' ==== Fruit Wine, Cider and Perry ==== [[wikipedia:Fruit_wine|Fruit wine]] is mostly what it sounds like: wine made from fruits other than grapes. A variety of fruits can be used, some common ones include cherry, plum, dandelion and pineapple. Fruit wine is far less common than traditional grape wines, and is often called by the fruit it's fermented from (ex. "cherry wine" or "dandelion wine"). [[wikipedia:Cider|Cider]] is a beverage made specifically from fermenting apples. Despite being a sort of wine fermented from fruit, it isn't considered a fruit wine due to its unique cultural history as a beverage. Its name can cause some confusion particularly in the United States and Canada, where "cider" also refers to unfiltered and sometimes spiced apple juice that has not been fermented. The term "hard cider" is sometimes used to distinguish the alcoholic beverage due to this overlap. Cider can also be carbonated to make a sparkling cider. [[wikipedia:Perry|Perry]], or Pear Cider, is another fruit wine exception. Fermented pears create a drink called perry, that though technically is a wine made from fruit, is considered its own thing. ''Common names: There are thousands of brands of fruit wine, cider and perry. You may have some on tap or bottled; it's mostly important to know the names of what you have.'' [[File:Beer_in_glasses_and_steins_on_a_table_with_bottles_in_the_background_and_a_brick_wall_(15700131777).jpg|thumb|264x264px|There are many varieties of beer.]] ==== Beer ==== [[wikipedia:beer|Beer]] is an ancient drink that has been brewed around the world for hundreds of years. Most beers have four basic ingredients: grain, hops, yeast and water. [[wikipedia:Hops|Hops]] are a type of dried flower that give beer flavor. While there are thousands of brands of beer, there are only a few main types: * '''Lagers''' - One of the two main types of beer, with Ales. Lighter and crisp, refreshing, less bitter than Ale. ** Amber Lager - A medium, amber color with a slight bitterness. ''Common Names: Yuengling'' ** Pale Lager - Light in color and flavor, not very bitter. Easy drinking and very popular. ''Common Names: Red Stripe, Heineken, Pabst Blue Ribbon (PBR), Hamms'' ** Pilsner - Medium amber in color. Hoppy and flavorful. ''Common Names: Modelo Especial, Stella Artois, Pilsner Urquell'' * '''Ales''' - The other main type of beer, with Lager. Richer and flavorful, more bitter than Lager. ** Pale Ale - A diverse group of beer that various depending on its country of origin. Generally balanced taste that pairs with many foods. ''Common Names: Sierra Nevada, Boulevard'' ** Indian Pale Ale (IPA) - Often very bitter and fruity. A unique tasting beer with bite. ''Common Names: Voodoo Ranger, many other large brands have an IPA'' ** Stouts and Porters - Dark beers that have rich, roasted flavors often imitating chocolate or coffee. These beers can feel like a meal. ''Common Names: Guinness, Imperial Stouts, Breakfast Stouts'' ** Wheat Beer - Ales that have some wheat added to them. It can give them a fruity, almost banana like flavor. ''Common Names: Blue Moon'' * Radlers and Shandys - Beers that have been mixed with a fruit juice. Radlers can be any type of citrus while Shandys are always lemon juice. Very refreshing, summary drinks. * Sour Beer - Beer that's, well, sour. Tangy and punchy, usually served in a smaller "sour beer" glass since they pack a punch. * Light Beer - Any beer with an especially low ABV is a light beer (less than 4% ABV), though the term is sometimes also used for low-calorie beers. ''Common Names: Bud Light, Coors Light'' ==== Sake ==== [[wikipedia:sake|Sake]] is a drink brewed from rice, and is sometimes also called rice wine though it is brewed more similarly to beer. Like beer and wine, sake has a wide range of flavor profiles though it is often fruity and light. It is sometimes served lightly warmed in ceramic cups depending on the variety of sake. ''Common Names: Dassai, Hakutsuru, Kubota'' === Spirits (High-ABV Drinks) === [[File:Alcoholic_beverages.jpg|thumb|High-ABV spirits like vodka and brandy.]] ==== Vodka ==== [[wikipedia:vodka|Vodka]] is a spirit that can be distilled from many sources including grains, potatoes and sugarcane before the pure ethanol is diluted with water. It is generally a neutral spirit, meaning it has little taste and is mostly pure ethanol and water. This isn't entirely true though, as each vodka has its own impurities and subtle flavor profiles. Vodka is also commonly flavored, as its neutral taste allows it to take on flavor easily. It can served up, often freezer chilled, or mixed into many cocktails. ''Common Names: Absolut, Smirnoff, Kettle One'' ==== Gin ==== [[wikipedia:Gin|Gin]] is a spirit flavored with [[wikipedia:juniper_berries|juniper berries]] and other botanicals. It has a distinct herbal flavor, and different brands will have their own flavor profile, and perceived dryness. [[File:Agave_tequilana_2.jpg|thumb|Agave is a plant native to Mexico.]] ''Common Names: Beefeater, Tanqueray, Hendrick's, Plymouth'' ==== Mezcal (Tequila) ==== [[wikipedia:mezcal|Mezcal]] is a spirit distilled from Agave. The most common type of mezcal is [[wikipedia:tequila|Tequila]], which is distilled only from [[wikipedia:blue_agave|blue agave]]. Many people mistake mezcal for a type of tequila due to tequila's popularity, but it is the other way around. Mezcal and tequila are often aged, which impart a darker, more amber color the longer it sits. Mezcal often has a smokey flavor and can also be sweet, fruity or earthy, and can be enjoyed chilled, up or in many popular cocktails. ''Common Names: Casamigos, Patrón, Jose Cuervo'' ==== Rum ==== [[wikipedia:rum|Rum]] is a spirit distilled from [[wikipedia:sugarcane|sugarcane]] then aged in barrels. The less-aged rum has a lighter color, and is called "light rum". It is most commonly used in cocktails, like the Mojito and the Daiquiri. "Aged" or "Dark" rum has a much deeper flavor is often drank straight or on the rocks. Rum originates from and maintains strong ties to the history of the people of the [[wikipedia:caribbean|Caribbean]] and appears commonly in cultural cuisines as well as drinks. I encourage you to learn about the history of rum, as it can teach a lot about sugarcane as a [[wikipedia:Sugar_plantations_in_the_Caribbean|plantation crop]] and the[[wikipedia:Atlantic_slave_trade|Transatlantic Slave Trade]]. ''Common Names: Baccardi, Captain Morgan, Malibu'' ==== Brandy ==== [[wikipedia:Brandy|Brandy]] is made by distilling wine. While most brandy is made from grapes, it can be made from any fruit to yield a [[wikipedia:Fruit_brandy|fruit brandy]]. ''Common names: Cognac and Armagnac'' ==== Whiskey ==== [[wikipedia:whiskey|Whiskey]] is made by fermenting, distilling then aging in barrels various grains. Whiskey drinkers can be particular, as there are many types of whiskey. Some whiskey is "malted", meaning it uses grains that have been malted. Malting is the process of allowing grains to germinate (begin to sprout), before heating them to halt the germination. This yields "malt whiskey". The specific grain used also yields different types of whiskey, for example fermenting rye yields "rye whiskey". "[[wikipedia:Scotch_whisky|Scotch]]" is simply whiskey from Scotland and is also called Scotch Whiskey. ''Common Names: Jameson, Jack Daniel's, Crown Royale'' ==== Soju ==== [[wikipedia:soju|Soju]] is a made by distilling rice or other grains. Similarly to vodka, it is a neutral spirit that is most flavorless. It is often flavored with fruits and florals. It can be served up or mixed into cocktails. ''Common Names: Jinro'' ==== Liqueurs ==== [[wikipedia:liqueur|Liqueurs]] are spirits that have been heavily flavored and sweetened. They are used very frequently in cocktails to impart their particular flavor. Liqueurs can be used to add a flavor that would otherwise be troublesome, like coffee, liquorish, or almond. Sometimes they're served up as a dessert or a [[wikipedia:digestif|digestif]]. ''Common Names: Kahlua, Aperol, Campari, Amaretto, Cointreau, and many, many more'' == Tools of Bartending == You'll be using both common and specialty tools as a bartender. A collection of such tools are below. Start by trying to name as many of them as you can. Note how many are familiar to you, how many you've seen but cannot name, and how many are unfamiliar. A key to the image follows. [[File:Bartools2.jpg|border|center]] Answer key: (1) champagne bottle stopper, (2) kitchen knife, (3) ice tongs, (4) ice scoop, (5) ice bucket, (6) small bar spoon, (7) cocktail-pick, (8) jigger, (9) mesh strainer, (10) boston shaker (metal bottom), (11) bar spoon, (12) lime/lemon squeezer, (13) hawthorn strainer, (14) zester, (15) boston shaker (mixing glass), (16) muddler, (17) citrus reamer, (18) fine grater, (19) Y-peeler, (20) wine key. How'd you do? Some of these items you'll see more often than others. I want to draw special attention these crucial pieces: * '''Jigger''' (8) - A small double sided measuring device used to quickly portion spirits and other ingredients. Though the exact measurements may change depending on where you are and the manufacturer, in the US most jiggers measure 1.5 oz on one end and 0.75 oz on the other. * '''Juicer and Peeler''' (12 & 19) - Many cocktails rely on citrus for flavor and fragrance. The handheld juicer and the peeler are commonly used both at the start of the shift to prep the citrus for the day, collecting fresh citrus juice and peels for adding to cocktails. * '''The Boston Shaker''' (10 & 15) - This is the industry standard for fast, versatile and accurate cocktail mixing. Coming in two parts, often one side is glass and the other is metal, though often both are metal. The two parts are sealed together allowing for a cocktail to be shaker vigorously inside before being cracked apart without spilling. * '''The Hawthorn Strainer''' (23) - The final piece to any Boston Shaker. This uniquely shaped strainer allows for cocktails to be poured into a glass while leaving the ice in the shaker. These are tools you will see every time you step in to bar to make a cocktail. == Safety == A good bartender is the difference between a safe time for your bar patrons and an unsafe environment. It is your responsibility to keep both yourself and your bar patrons safe. It is important first to understand how alcohol affects the body in order to understand how to properly make and serve drinks, so first let's review ABV. Alcohol by Volume is a percentage of ethanol to all other contents of a drink. However, ABV does not tell you everything about drink. A standard beer has about 5% ABV while a shot of whiskey has about 40% ABV, but because you would only drink about 1.5 oz of whiskey, and would drink 12 oz beer, the total amount of alcohol ingested would actually be about the same. This is the idea behind a "standard drink". A standard drink contains one "unit" of alcohol regardless of how much liquid it contains in total. The chart below shows some examples of standard drink equivalents. Each of the below drinks contain one unit of alcohol. [[File:NIH_standard_drink_comparison.jpg|center|frame|National Institute of Health's "standard drink".]] Some general best practices when consuming alcohol: * One unit of alcohol per hour is around what a liver can process. This is generally a safer cadence of drinking. * Drink a glass of water for every unit of alcohol consumed to stay hydrated. * Avoid drinking on an empty stomach. Eating while consuming alcohol slows the alcohol's absorption into the blood and curbs its effects. * Don't order a double. Ordering and serving drinks with more than one standard unit of alcohol in it can cause you or others to become more impaired more quickly than intended. Try to keep it to the cadence of one standard drink per hour. Standards should be upheld both with your own drinking and the drinking of the patrons at your bar. Some standards to uphold in your bar are: * '''Never drink and drive'''. Alcohol impairs motor coordination and clouds judgement. Drinking and then driving puts your own life and the lives of everyone around you in immediate danger. Even if you are under the legal limit in your area, you are impaired after one drink. This should be enforced both for yourself and for your bar patrons. * '''You can say no'''. It's always okay to say no to a drink. Ordering something without alcohol is always an option. Good friends don't pressure you to drink when you don't want to. You can leave a situation when you are uncomfortable. * '''Alcohol is not medicine'''. Addiction is real and treatable. Help is available. * '''Abuse isn't acceptable'''. You are not a punching bag. It is not bad hospitality to stand up for yourself. Sometimes people drink more than they intended and may become too inebriated to be served. Some signs that this is the case are: * Slurred speech * Stumbling * Glazed over or unfocused eyes * Speaking too loudly or two softly * Repeating questions or ordering from multiple bartenders If you meet a bar patron who has had too much to drink, you can help by offering water, tea, coffee or food, helping them find their group, or asking another member of the staff at your bar for help. It may be that what's needed is to no longer serve the bar patron. This is called "cutting them off". When a bar patron is cut off, they will no longer be served alcohol for the rest of the service. This can be embarrassing, both for the bar patron and the bartender, so it's best practice to be kind, clear and discrete. If a patron is aggressive however, all bets are off and they should be removed from the bar. Bartenders have legal obligations depending on where you work. This can include checking the legal age of the patrons at your bar and monitoring the alcohol intake of the patrons at your bar. Sometimes, a bartender can be held individually liable for the failure to meet these obligations. Take the time to find a reputable source to discover what the legal obligation of bartenders in your area are now. This concludes Lesson 1: Bartending Basics. You can move on now to [[Bartending/Mixing Drinks|Lesson 2: Mixing Drinks]]. [[Category:Professional and vocational studies]] [[Category:Professions]] [[Category:Drinks]] {{BookCat}} f0sc8u9ndez9ikujbpypyy39blonpzj 0 330941 2835157 2834189 2026-09-30T12:36:59Z SJPiper 3107750 Removed double spacing in text 2835157 wikitext text/x-wiki {{title|Akrasia:<br>Why do people act against their better judgement?}} __TOC__ ==Overview== {{RoundBoxTop|theme=5}}'''Consider this scenario''' Jordan signed up for a gym membership at the start of the year, determined to improve his physical and mental health. He bought new workout clothes, saved a list of routines and even told his friends he was committed to exercising. But when his alarm goes off at 6:30am, he hits snooze, telling himself he will simply go after work instead. By 5:00pm, he's too tired to go. The idea of lifting weights is too emotionally heavy and stress inducing for him, so Jordan chooses to stay home and watch a TV show. Each time Jordan's alarm goes off, he ignores it, even though he knows that going to the gym is a healthy option and helps him gain confidence although the short-term comfort of staying at home outweighs those feelings. Jordan isn't lazy, he's experiencing akrasia, a predictable motivational and emotional conflict between long term goals and short-term impulses. {{RoundBoxBottom}} [[File:Woman Stressed At Work Illustration.jpg|thumb|Figure 1. A women experiencing stressful situation with conflicting priorities. ]] This Chapter explains and explores why people act against their better judgment. It describes this through psychological explanations of self-control and regulation, motivational deficits, and emotional avoidance. This phenomenon has been named Akrasia. '''The problem''': Akrasia is a phenomenon many people experience. The problem is that it affects many areas of an individual's life, such as academics, health choices, financial decisions, and relationships. This is because many people intend to make choices that align with their values and goals, yet often make choices that move them further away from them. This gap between intention and action can lead to issues with wellbeing and a sense of success in life. Understanding akrasia is important because it undermines goal achievement, wellbeing, and personal goals. It reflects the tension between reflective, value-based intentions and impulsive actions. Understanding the psychological science behind this concept matters because it gives you tools to understand the conflict by examining self-regulation and cognitive bias. This will also give you techniques to help reduce akrasia so you can reach the goals you have set.{{RoundBoxTop|theme=5}}'''Focus questions''' [[File:Crystal Clear app ktip.svg|left|20px|]] * What is akrasia? * What psychological processes contribute to akrasia and the conflict between long term and short term impulses? * How do motivation and emotion interact to influence why people act against their better judgement ? * What evidence based strategies can help people reduce akrasia and act more consistently in line with their goals ? {{RoundBoxBottom}} == Akrasia == ==== What is Akrasia ==== Akrasia refers to the psychological phenomenon of acting against one's better judgment, and psychological research explains it as a product of predictable conflicts within the human self-regulation system. Rather than moral weakness, akrasia reflects tension between reflective, long-term intentions and immediate, emotionally driven short-term impulses. Studies in self-regulation highlight how failures in goal monitoring, susceptibility to short-term rewards and reduced sensitivity to long-term consequences make an individual more likely to behave in ways that contradict their own considered goals. Motivation research further shows that hedonic impulses- such as seeking comfort or avoiding discomfort can overpower reflective decision-making, producing patterns of self-indulgence or avoidance. Dialogical self-theory adds that akrasia can emerge from competing internal "voices" such as the disciplined self and the comfort-seeking self, each shaped by social and cultural influences. This phenomenon involves cognitive, emotional, and motivational processes. Together, they contribute to the intention-action gap that leads to what is described as Akasia. [[File:Aristotle Altemps Inv8575.jpg|thumb|Figure 2. An image of Aristotle ]] ==== Historical background: where did the term Akrasia come from? ==== Akrasia originates from ancient Greek philosophy. Particularly Aristotle, who used the term akrasia to describe " weakness of will", etc. Describe what he argued about failure to understand emotions and impulses. Historically, Akrasia has been recognised for thousands of years. The concept originates in ancient Greek philosophy, particularly in the work of Aristotle, who used the term akrasia to describe "weakness of will"; Aristotle argued that people sometimes fail to act in accordance with their rational understanding because emotions, desires, or impulses temporarily overpower reason.  In his view, akrasia occurs when the rational part of the mind identifies the best course of action. However, the nonrational part disrupts this judgment and pulls behaviour toward short-term gratification. This failure is not due to ignorance but to momentary inability to manage or correctly interpret one's emotional and motivational states. Earlier, Socrates debated whether akrasia was even possible, suggesting that if someone acted wrongly, it must be because they misunderstood what was truly good. Aristotle disagreed, emphasising that people can genuinely know the right action yet still fail to follow it. He suggested that individuals often misjudge the force of their impulses, treating them as rational justifications in the moment.  This historical debate helped lay the foundation for modern psychological explanations. Contemporary theories echo Aristotle's insight: people often experience a conflict between reflective, long-term reasoning and immediate, affect-driven impulses, and behaviour often follows whichever system is strongest in the moment.   (Bobonich & Destree, 2007). == Akrasia as a motivational and emotional conflict == '''Focus question''': what psychological processes contribute to akrasia and the conflict between long term and short term impulses? Akasia is easier to understand when framed as a psychological conflict between internal systems that operate under different rules, time scales, and motivational priorities (Frederick, Loewenstein, & O’Donoghue, 2002). From a psychological perspective, long-term goals are maintained by reflective, value-based processes that rely on executive functioning, future planning and a coherent sense of identity- the part of the mind that says "finishing my degree matters for my future". These goals are cognitively effortful, meaning they require working memory, sustained attention, and the ability to tolerate discomfort in the service of a future outcome. In contrast, short-term impulses arise from fast, affect-driven systems that prioritise immediate emotional states. When someone feels tired, stressed or bored, the short-term system generates urges like "I just want to relax now". These impulses are not irrational; they are grounded in the brain's reward circuitry, which is highly sensitive to immediate relief and comfort (Sirois & Pychyl,  2013). Psychology research shows that akrasia often occurs when tasks evoke negative affect, such as states of anxiety, frustration, or uncertainty. Under these conditions, people tend to prioritise short-term affective rewards, such as relief from discomfort, even when they consciously prefer the long-term outcomes. This means that akrasia can serve as a mood repair strategy, where avoidance temporarily improves emotional states at the cost of long-term goals (Steel, P. (2007).   Dual-process models explain this dynamic by distinguishing between two interacting systems: a fast, automatic, emotionally reactive system called system 1 and a slower, reflective, future-oriented system called system 2. Akrasia is when system 1 dominates behaviour in the moment, overpowering the deliberate reasoning of system 2.  Factors such as cognitive load, stress, and emotional discomfort weaken reflective control, making impulsive choices more likely.  All this to say, akrasia results from how human motivational and emotional systems compete for behavioural control (Hofmann, Friese, & Strack, 2009).  == Self‑regulation and self‑control == '''Failures in self‑regulation contribute to akrasia''': Self-regulation is a multifaceted process that describes an individual's ability to manage emotions, thoughts, and behaviours in ways that yield positive results. Failure occurs when an individual cannot coordinate behaviours, emotions, or attention to achieve a long-term goal (Catanese, 2024).  While we cannot yet identify a single cause of self-regulation failure, we can identify patterns that produce it (Baumeister & Heatherton, 1996).  Self-regulation failure can cause undeniable harm by leading individuals to act in ways that may harm them or others financially, physically, or emotionally. Self–regulation failure can be broken down into different conceptualisations of how it occurs; one is the three-part feedback loop proposed by Carver and Scheier (1981).   The first part describes standards, the ideals and goals; without proper standards, self-regulation is hindered. The second part is monitoring; this is where individuals must account for their actions in relation to their standards, meaning that if someone is not holding themselves accountable to meet their standards, failure often starts here.  The third part of operating is when monitoring falls short of the standards, and the process of changing the goal or state begins.  Failure occurs because, while a person can set a goal and monitor effectively, they may still fail to achieve it (Baumeister & Heatherton, 1996). Bella (2023) describes another way self-regulation failure can occur, with similar underlying factors to Carver's and Scheier's (1981).  She argues that akrasia is best understood as a conflict between internal systems. Specifically, the reflective system represents long-term values and goals, while the impulsive system responds to immediate emotional and motivational states. When these systems compete, behaviour becomes inconsistent, fragmented, and vulnerable to short-term impulses. Failure indicates that the individual's ability to manage impulses and emotions and maintain goal-directed behaviour is compromised. This vulnerability is not a character flaw, but a predictable psychological pattern that arises when regulatory processes are overloaded, undermined, and not integrated effectively. More precisely, akrasia occurs when the impulsive system becomes more dominant because short-term impulses feel more compelling, and long-term goals feel more distant and effortful. This is what makes a person act against their better judgment, even when they fully understand the potential long-term consequences. (Bella, 2023) Understanding self-regulation failure would help identify solutions to acts of akrasia and other motivation conflicts. Understanding allows an individual to alter their response to a stimulus. '''Discuss ego depletion''' Another concept that helps describe why akrasia might occur is ego depletion.  Ego depletion is the idea that self-control operates like a limited resource. When people expend self-control, they regulate their emotions, resist temptations, make decisions, and force themselves to finish difficult tasks. Once this limited resource of self-control is depleted, their ability to persist, inhibit impulses, or act according to long-term goals becomes significantly impaired.   Baumeister, Bratislavsky, and Tice (1998) proposed that self-control relies on a single, general resource. This means any act of self-control consumes this resource, leaving a person temporarily less capable of exerting further control.  When individuals become depleted, they are more vulnerable to short-term impulses, making akrasia more likely. This is possible even when the long-term goal is important; they lack the regulatory strength to act on it. More recent work by Inzlicht and Schmeichel (2012) challenges the idea of self-control as a resource, arguing instead that ego depletion reflects shifts in motivation, attention, and affect. After exerting self-control, people become less motivated to exert effort and less attentive to long-term goals. This still supports the idea that akrasia is a regulatory system that shifts towards seeking short-term rewards over long-term intentions.  These processes make akrasia more likely, as individuals who are depleted struggle to inhibit impulses or tolerate discomfort. In everyday life, ego depletion can be seen when a student intends to study after a long day but instead chooses to relax because their regulatory capacity is drained.  In these moments, the long-term goal remains valued, but the ability to fulfil it is compromised.{{Robelbox|theme=5|width=60%|title=1.1 - Module overview|iconwidth=47px|icon=Nuvola_apps_korganizer.svg}}<div style="{{Robelbox/pad}}"> <quiz display=simple> { Which subject best explains how failures in self regulation contribute to akrasia? } |type="()"} - Ego Depletion - Temporal discounting + Internal system conflict </quiz> </div> {{Robelbox-close}} == Motivational theories == [[File:Self-Determination-Theory-Visual 1.png|thumb|Figure 3: Self-Determination Theory visual diagram ]] ===== Self‑determination theory: ===== Self-determination theory explains innate psychological needs in relation to human motivation (Ryan & Deci, 2000). It was developed by Edward Deci and Richard Ryan (1985). The theory describes how humans have an innate predisposition for psychological growth and development, fueled by three basic psychological needs. Needs are defined as inherent and motivating (Ryan & Deci, 2017). Once fulfilled, these needs contribute to a person's health and well-being. The first need identified is autonomy. It is when one's behaviour is self-directed and congruent with their personal interests and values. This need is satisfied when an individual's actions fulfil their desires and feel authentic to them (Deci & Ryan, 2015).   The second is competence: the urge to feel capable and develop a mastery of performing tasks.  To satisfy this, an individual can challenge their skills and abilities (Vansteenkiste et al., 2020). Lastly, relatedness is the feeling of connection and belonging. It is fulfilled when an individual feels capable of caring for others and being cared for. When an individual's needs are not satisfied, however, this can result in illness or discontent (Deci & Ryan, 2000).  STD proposes that not all motivation is equal, meaning that the focus should be on how and why a person is motivated. To understand why akrasia occurs, it is crucial to understand the difference between autonomous and controlled motivation. Autonomous motivation includes two forms: intrinsic motivation, which refers to engaging in an act because it is personally meaningful and interesting. Integrated regulation refers to acting because it’s aligned with one’s values and sense of self (Deci, 1972).  Individuals must feel a sense of choice, volition, and psychological freedom, rather than pressure to perform.  When these needs are met, individuals show satisfaction with the three needs.  Akrasia becomes less likely when motivation is autonomous. When people genuinely value a goal, they are more likely to tolerate discomfort, delay gratification, and persist even when it is difficult. This is because the action feels internally meaningful, individuals feel capable of reaching their end goal, and they feel supported in their action, so short-term impulses have less power.  An individual may still act autonomously, even in accordance with external expectations, if they believe their behaviour remains consistent with their values and is of their own volition (Ryan & Deci 2017). Controlled motivation describes the feelings of pressure and tension. It occurs when behaviour is driven not by personal values or genuine interest but by external demands, internal pressure or avoidance of guilt and shame. This is the opposite of autonomous motivation and often causes akrasia. Similar to autonomous motivation, it breaks down into two main forms. External regulation: acting to obtain a reward or avoid punishment.  Introjected regulation, acting to avoid guilt, anxiety, or maintain self-worth.  In both cases, behaviour tends not to be fully self-endorsed.  Controlled motivation increases akrasia; it makes tasks feel aversive, even when the individual knows the long-term goal is important, because this creates emotional friction and associates tasks with stress, guilt, or obligation.  When an individual feels controlled, they are more likely to avoid the task, procrastinate, or act against their better judgment (Deci et al., 2012).{{RoundBoxTop|theme=5}} ''' Example scenario''' Annie really wants to get her psychology degree, but she finds studying difficult however she continues to engage and attend class to achieve her goal. She is pushing through a desire to disengage, procrastinate, and stop in order to feel a sense of achievement that she did herself. {{RoundBoxBottom}} *expectancy‑value theory: actions based an appraisal of successes (reference: Wigfield, A., & Eccles, J. S. (2000). Expectancy–Value Theory of Achievement Motivation. ''Contemporary Educational Psychology'', ''25''(1), 68–81.https://doi.org/10.1006/ceps.1999.1015) *Show how motivation quality affects the likelihood of acting in line with long‑term goal * emotional avoidance: tasks that evoke frustration are avoided this is a form of regulation ( reference : De Castella, K., Platow, M. J., Tamir, M., & Gross, J. J. (2018). Beliefs about emotion: implications for avoidance-based emotion regulation and psychological health. ''Cognition and Emotion'', ''32''(4), 773–795. https://doi.org/10.1080/02699931.2017.1353485) <quiz display="simple"> {SDT is primarly concerned with ? :} - How rewards increase performance + How basic psychological needs influence motivation - How motivation shapes decision making {SDT views motivation as ?:} - A simple intrinsic/extinsic split - A set of unrelated catagories + A continuum from controlled to autonomous </quiz> == Reduction Techniques == Present practical, research‑supported strategies for reducing akrasia, Explain why each strategy works and how individuals can apply it: *Reducing cognitive load: working memory has a limited capacity so when this is reached tasks can become a source of impairment, techniques such as task chunking can help reduce the load. ( reference: Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. ''Cognitive Science'', ''12''(2), 257–285. https://doi.org/10.1207/s15516709cog1202_40 ) * Enhancing autonomous motivation : Autonomy supportive techniques that help enegemnt with tasks. (Reference: Reeve, J., & Jang, H. (2006). What Teachers Say and Do to Support Students’ Autonomy During a Learning Activity. ''Journal of Educational Psychology'', ''98''(1), 209–218. https://doi.org/10.1037/0022-0663.98.1.209 ) * goal‑setting theory: challenging akrasia ( reference: Locke, E. A., & Latham, G. P. (2002). Building a practically useful theory of goal setting and task motivation: A 35-year odyssey. ''The American Psychologist'', ''57''(9), 705–717. https://doi.org/10.1037/0003-066X.57.9.705) <quiz display="simple"> {Which technique would you use? :} - Reduction of cognitive load - Autonomous motivation - Goal Setting </quiz> == The Understanding of Psychological Science Of Akarsia and Support == '''Focus question''': what strategies are there to reduce to act of akrasia and act more consciously in line with their goals? Empirical fining both support and refine theoretical models of akrasia by showing that it arises from multiple interaction processes, rather than simple tendency to put of work, reach on self-regulation failure(Bella, 2024), ego depletion (Baumeister et al., 1998; inzlicht & schmeichel, 2012) and self-determination theory (Deci & Ryan, 200) collectively demonstrate that akrasia reflects conflicts between long term, value based intentions and short term, affect driven impulses, shaped by motivational quality, emotional avoidance and cognitive load. These findings challenge overly simplistic models that treat akrasia as simply procrastination or lack of willpower, and instead support integrative frameworks in which internal systems, basic psychological needs and situational demands jointly determine whether people act in line with their better judgement. This integrated knowledge has important implications for improving motivational and emotional lives. Interventions should not only focus on trying harder, but also support autonomous motivation and emotional regulation while reducing unnecessary control and guilt. By targeting these mechanisms, individuals are more likely to experience motivation that is self-endorsed, resilient to discomfort, and aligned with long-term goals (Sirois & Pychyl, 2013).    * {{RoundBoxTop|theme=5}} ADD scenario that follows up on jordans problem with a solutions based on principles discussed {{RoundBoxBottom}} ==Conclusion== * summarise the most important points in 3–5 sentences. * Align with subtitle and focus questions. * Highlight implications for personal growth and psychological wellbeing. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== * [[Motivation and emotion/Book/2011/Self-determination theory|Self-determination theory]] (Book chapter, 2011) * [[wikipedia:Goal_setting|Goal setting]] (Wikipedia) * [[wikipedia:Motivation|Motivation]] (Wikipedia) ==References== {{Hanging indent|1= Bobonich C., & Destrée, P. (2007). Akrasia in Greek Philosophy: From Socrates to Plotinus. BRILL .106, 1-11. https://books.google.com.au/books?id=so097j_jPBsC&dq=akrasia+historical+background&lr=&source=gbs_navlinks_s Bella, A. F. (2023). Psychological underpinnings of akrasia: A new integrative framework based on self-regulation vulnerabilities and failures. New Ideas in Psychology, 70, Article 101027. https://doi.org/10.1016/j.newideapsych.2023.101027) Baumeister, R. F., et al. (1998). Ego depletion: Is the active self a limited resource? Journal of Personality and Social Psychology. DOI: https://doi.org/10.1037/0022-3514.74.5.1252 (doi.org in Bing) Deci, E. L., & Ryan, R. M. (2000). The “What” and “Why” of Goal Pursuits: Human Needs and the Self-Determination of Behavior. Psychological Inquiry, 11(4), 227–268. https://doi.org/10.1207/S15327965PLI1104-01 De Castella, K., Platow, M. J., Tamir, M., & Gross, J. J. (2018). Beliefs about emotion: implications for avoidance-based emotion regulation and psychological health. Cognition and Emotion, 32(4), 773–795. https://doi.org/10.1080/02699931.2017.1353485 Frederick, S., Loewenstein, G., & O’Donoghue, T. (2002). Time discounting and time preference: A critical review. Journal of Economic Literature, 40(2), 351–401. https://doi.org/10.1257/002205102320161311 Hofmann, W., Friese, M., & Strack, F. (2009). Impulse and self-control from a dual-systems perspective. Perspectives on Psychological Science, 4(2), 162–176. https://doi.org/10.1111/j.1745-6924.2009.01116.x Inzlicht, M., & Schmeichel, B. J. (2012). What Is Ego Depletion? Toward a Mechanistic Revision of the Resource Model of Self-Control. Perspectives on Psychological Science, 7(5), 450–463. https://doi.org/10.1177/1745691612454134 Locke, E. A., & Latham, G. P. (2002). Building a practically useful theory of goal setting and task motivation: A 35-year odyssey. The American Psychologist, 57(9), 705–717. https://doi.org/10.1037/0003-066X.57.9.705) Reeve, J., & Jang, H. (2006). What Teachers Say and Do to Support Students’ Autonomy During a Learning Activity. Journal of Educational Psychology, 98(1), 209–218. https://doi.org/10.1037/0022-0663.98.1.20 Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1207/s15516709cog1202_4 Sirois, F. M., & Pychyl, T. A. (2013). Procrastination and the priority of short-term mood regulation: Consequences for future self. Personality and Individual Differences, 55(6), 653–658. https://doi.org/10.1016/j.paid.2013.06.011 Steel, P. (2007). The nature of procrastination: A meta-analytic and theoretical review of quintessential self-regulatory failure. Psychological Bulletin, 133(1), 65–94. https://doi.org/10.1037/0033-2909.133.1.65 Wigfield, A., & Eccles, J. S. (2000). Expectancy–Value Theory of Achievement Motivation. Contemporary Educational Psychology, 25(1), 68–81. https://doi.org/10.1006/ceps.1999.1015}} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== * [https://pmc.ncbi.nlm.nih.gov/articles/PMC3062191/ Cognitive neuroscience of self regulation failure] (National library of medicine) {{ic|This should be in references and cited}} * [https://www.youtube.com/watch?v=jHGFlyHnhFQ Self control and Akrasia] (YouTube) [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Self-control]] eu40p5uzxjc9ekxn5qz5mtkwjs2qh09 828 331015 2835235 2835079 2026-09-30T23:35:51Z Helpme2222 3106525 2835235 Scribunto text/plain -- My function for teaching grammar local p = {}; local frame = mw.getCurrentFrame() local grammatical_moods = { "Jelen ido", "Mult ido", "Felszolito mod", "Felteteles mod" } local balls = { grammatical_moods } function p.teamfightSource() local frame = mw.getCurrentFrame() local pageContent = mw.html.create(nil) local i = 1 while (frame.args["team"..i.."_ball1"]) do local teamTable = mw.html.create("table") :addClass("wikitable sortable") :node( mw.html.create( 'tr' ) :node( mw.html.create( 'th' ):node("Participant") ) :node( mw.html.create( 'th' ):node("Contribution") ) :node( mw.html.create( 'th' ):node("Final scaling value") ) :node( mw.html.create( 'th' ):node("Final health") ) ) local j = 1 while (frame.args["team"..i.."_ball"..j]) do teamTable:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j]) ) -- ball also needs to have form and stuff. :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_score"] --[[..]] --[[get contribution type]]) ) -- test: see wordpad comment :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_scaledTo"] --[[..]] --[[get scaling feature]]) ) :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_health"]) ) ) end pageContent:node( mw.html.create("h3"):node("Team "..i) ) :node( teamTable ) end pageContent:node( mw.html.create("h2"):node("Outcome") ) local j = 1 while (frame.args["team"..frame.args.winningTeam.."_ball"..j]) do pageContent:node( --[[sprite of ball, linked to team section]] ) end pageContent:node( "Team" ) end local toggleButton = mw.html.create( 'span' ) :css({ float = "right", ["margin-right"] = "0", ["font-weight"] = "normal" }) :addClass("mw-customtoggle-Infobox") :node("[Click to toggle]") function p.subheading( discrim, b_content, content ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( (discrim) and "mw-collapsible" ) :node( mw.html.create( 'th' ) :attr( "colspan", "2" ) :css( "text-align","left" ) :node((discrim) and b_content or content) :node((discrim) and toggleButton) ) end function p.s_subheading( s_content ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( "mw-collapsible mw-collapsed" ) :node( mw.html.create( 'th' ) :attr( "colspan", "2" ) :css( "text-align","left" ) :node(s_content) :node(toggleButton) ) end function p.row( discrim, name, data ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( (discrim) and "mw-collapsible" ) :node( mw.html.create( 'td' ) :css( "font-weight","bold" ) :node(name) ) :node( mw.html.create( 'td' ) :node(data) ) end function p.s_row( s_name, s_data ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass("mw-collapsible mw-collapsed") :node( mw.html.create( 'td' ) :css( "font-weight","bold" ) :node(s_name) ) :node( mw.html.create( 'td' ) :node(s_data) ) end function p.var(symbol) return frame:expandTemplate{ title = "Template:Var", args = {symbol} } end function p.iseq() return table.concat({ frame.args[1] .. ( (frame.args[1] == "User:Helpme2222/Sandbox/'") and " is equal to User:Helpme2222/Sandbox/'" or " is not equal to User:Helpme2222/Sandbox/'"), frame.args[1] .. ( (frame.args[1] == "User:Helpme2222/Sandbox/&#039;") and " is equal to User:Helpme2222/Sandbox/&#039;" or " is not equal to User:Helpme2222/Sandbox/&#039;"), frame.args[1] .. ( (frame.args[1] == "Helpme2222/Sandbox/'") and " is equal to Helpme2222/Sandbox/'" or " is not equal to Helpme2222/Sandbox/'"), frame.args[1] .. ( (frame.args[1] == "Helpme2222/Sandbox/&#039;") and " is equal to Helpme2222/Sandbox/&#039;" or " is not equal to Helpme2222/Sandbox/&#039;"), }, "<br>") end function p.iseqNamed() return table.concat({ frame.args.arg .. ( (frame.args.arg == "User:Helpme2222/Sandbox/'") and " is equal to User:Helpme2222/Sandbox/'" or " is not equal to User:Helpme2222/Sandbox/'"), frame.args.arg .. ( (frame.args.arg == "User:Helpme2222/Sandbox/&#039;") and " is equal to User:Helpme2222/Sandbox/&#039;" or " is not equal to User:Helpme2222/Sandbox/&#039;"), frame.args.arg .. ( (frame.args.arg == "Helpme2222/Sandbox/'") and " is equal to Helpme2222/Sandbox/'" or " is not equal to Helpme2222/Sandbox/'"), frame.args.arg .. ( (frame.args.arg == "Helpme2222/Sandbox/&#039;") and " is equal to Helpme2222/Sandbox/&#039;" or " is not equal to Helpme2222/Sandbox/&#039;"), }, "<br>") end function p.infoboxWBB() -- Passing expressions of conditional value: https://www.lua.org/pil/3.3.html --[[ https://www.mediawiki.org/wiki/LUAREF#mw.html:node Thankfully, these operations interpret passed nils as no-ops (I'm technically using false though. Somehow that works anyways?)]] local frame = mw.getCurrentFrame() local ballname = frame.args["Title"] or tostring(mw.title.getCurrentTitle()) local Entities = p -- require("Module:Entities") local featureCount = tonumber(frame.args["Feature count"]) or 1 local s_featureCount = tonumber(frame.args["SUPER Feature count"]) or featureCount local matchCount = { total = mw.site.stats.pagesInCategory( ballname .."'s Match History", "pages" ), standard = mw.site.stats.pagesInCategory( ballname .."'s Match History/Weapon Ball Battles/Standard", "pages" ), } local matchWinCount = { standard = mw.site.stats.pagesInCategory( ballname.."'s Match History/Weapon Ball Battles/Standard/Won", "pages" ), } local s_matchCount = { total = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History", "pages" ), standard = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History/Weapon Ball Battles/Standard", "pages" ), } local s_matchWinCount = { standard = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History/Weapon Ball Battles/Standard/Won", "pages" ), } local isSuper = frame.args["SUPER Feature count"] or frame.args["SUPER Type"] or frame.args["SUPER Debuted"] or (s_matchCount.total > 0) or nil -- for some reason, html:node interprets false-valued parameters as no-op signals, while html:addClass does not. The extra "or nil" had to be added since this is used in :addClass calls. -- TITLE local infobox = mw.html.create( 'table' ) :addClass("wikitable") :css({ float = "right"; ["margin-left"] = "10px" }) :node( mw.html.create( 'tr' ) :node( mw.html.create( 'th' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass((isSuper) and "mw-collapsible" or nil) :node("<big>" .. ballname .. "</big>") ) ) :node((isSuper) and mw.html.create( 'tr' ) :node( mw.html.create( 'th' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass("mw-collapsible mw-collapsed") :node("<big>" .. (frame.args["SUPER Title"] or ("Super " .. ballname)) .. "</big>") ) ) -- IMAGES :node((frame.args["Images"]) and mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass((frame.args["SUPER Images"]) and "mw-collapsible") :node(frame.args["Images"]) ) ) :node((frame.args["SUPER Images"]) and mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass("mw-collapsible mw-collapsed") :node(frame.args["SUPER Images"]) ) ) -- SECTION: Identification -- Section Heading :node( p.subheading( (frame.args["SUPER Type"]), "Base Identification", "Basic Info" ) ) :node( (frame.args["SUPER Type"]) and p.s_subheading( "Super Identification" ) ) -- Type :node( p.row( (frame.args["SUPER Type"]), "Type", frame.args["Type"] ) ) :node( (frame.args["SUPER Type"]) and p.s_row( "Type", frame.args["SUPER Type"] ) ) -- Color local color = frame.args["Color"] or Entities.getBallAttribute( "Entities/Weapon Ball Battles/Balls/Data", ballname, "color" ) infobox:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :css("font-weight", "bold") :node("Color") ) :node( mw.html.create( 'td' ) :node( (color ~= "") and frame:expandTemplate{ title = "Color", args = {color} } or "[[Module:Entities/Weapon Ball Battles/Balls/Data|<i>Add color...</i>]]" ) ) ) -- Emoji local emoji = frame.args["Emoji"] or Entities.getBallAttribute( "Entities/Weapon Ball Battles/Balls/Data", ballname, "emoji" ) infobox:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :css("font-weight", "bold") :node("Emoji") ) :node( mw.html.create( 'td' ) :node( (emoji ~= "") and ( emoji .. " <code>" .. p.emojiCodepointInternal(emoji) .. "</code>") or "[[Module:Entities/Weapon Ball Battles/Balls/Data|<i>Add emoji...</i>]]" ) ) ) -- SECTION: Scaling Characteristics --[[ Some data will be collected first. ]] -- (Base) Behavior local features = {} local starts = {} local scalings = {} if (featureCount > 1) then for i = 1, featureCount do table.insert(features, { frame.args["Feature "..i], " (" .. p.var(frame.args["Var "..i]) .. ")" }) table.insert(starts, { p.var( frame.args["Var0 "..i] or (frame.args["Var "..i].."₀") ) .. ": ", frame.args["Starting value "..i] }) table.insert(scalings, { p.var( "Δ"..(frame.args["Var "..i]) ) .. ": ", frame.args["Scaling "..i] }) end else -- These weird ass tables are meant to be compatible with the clone-and-overwrite operation the supers may undergo if the SUPER feature count, unlike the hypothetical base feature count, is greater than 1 features[1] = {frame.args["Feature"],""} starts[1] = {"",frame.args["Starting value"]} scalings[1] = {"",frame.args["Scaling"]} end -- Super Behavior local s_features local s_starts local s_scalings -- for some reason, html:node interprets false-valued parameters as no-op signals, while html:addClass does not. These booleans below are therefore left undefined (nil) as default. local has_s_features; local has_s_starts; local has_s_scalings; if (frame.args["SUPER Feature count"]) then if s_featureCount > 1 then -- Deep copy base characteristics, i.e. use them as default, overwrite what is explicitly specified as new super data s_features = mw.clone(features) s_starts = mw.clone(starts) s_scalings = mw.clone(scalings) -- If # of super features != # of base features, trim or expand the deep-copied tables accordingly. Avoid index errors. if s_featureCount > featureCount then for i = featureCount + 1, s_featureCount do table.insert( s_features, {"",""} ) table.insert( s_starts, {"",""} ) table.insert( s_scalings, {"",""} ) end elseif s_featureCount < featureCount then for i = s_featureCount + 1, featureCount do s_features[i] = nil s_starts[i] = nil s_scalings[i] = nil end end -- Parse super data, set the has_s_... flags if triggered for i = 1,s_featureCount do if frame.args["SUPER Feature "..i] then s_features[i][1] = frame.args["SUPER Feature "..i] if (not has_s_features) then has_s_features = true end end if frame.args["SUPER Starting value "..i] then s_starts[i][2] = frame.args["SUPER Starting value "..i] if (not has_s_starts) then has_s_starts = true end end if frame.args["SUPER Scaling "..i] then s_scalings[i][2] = frame.args["SUPER Scaling "..i] if (not has_s_scalings) then has_s_scalings = true end end if frame.args["SUPER Var "..i] then s_features[i][2] = " (" .. p.var(frame.args["SUPER Var "..i]) .. ")" s_starts[i][1] = p.var( frame.args["SUPER Var0 "..i] or (frame.args["SUPER Var "..i].."₀") ) .. ": " s_scalings[i][1] = p.var( '<span style="font-style:normal">Δ</span>'..(frame.args["SUPER Var "..i]) ) .. ": " if (not has_s_features) then has_s_features = true end if (not has_s_starts) then has_s_starts = true end if (not has_s_scalings) then has_s_scalings = true end end s_features[i] = table.concat(s_features[i]) s_starts[i] = table.concat(s_starts[i]) s_scalings[i] = table.concat(s_scalings[i]) end s_features = table.concat(s_features,"<br>") s_starts = table.concat(s_starts,"<br>") s_scalings = table.concat(s_scalings,"<br>") else -- # of super features = 1? just write directly to the variable if frame.args["SUPER Var"] or frame.args["SUPER Feature"] then has_s_features = true s_features = frame.args["SUPER Feature"] end if frame.args["SUPER Var0"] or frame.args["SUPER Var"] or frame.args["SUPER Starting value"] then has_s_starts = true s_starts = frame.args["SUPER Starting value"] end if frame.args["SUPER Scaling"] then has_s_scalings = true s_scalings = frame.args["SUPER Scaling"] end end end -- finalize base data as strings now that work is otherwise complete if (featureCount > 1) then for i = 1, featureCount do features[i] = table.concat(features[i]) starts[i] = table.concat(starts[i]) scalings[i] = table.concat(scalings[i]) end features = table.concat(features,"<br>") starts = table.concat(starts,"<br>") scalings = table.concat(scalings,"<br>") else features = features[1][1] starts = starts[1][2] scalings = scalings[1][2] end --[[ Begin rendering ]] -- Section Heading infobox:node( p.subheading( (frame.args["SUPER Feature count"]), "Base Scaling Characteristics", "Scaling Characteristics" ) ) :node( (frame.args["SUPER Feature count"]) and p.s_subheading( "Super Scaling Characteristics" ) ) -- Features :node( p.row( (has_s_features), (featureCount > 1) and "Features" or ( (frame.args["Var"]) and ("Feature (" .. p.var(frame.args["Var"]) .. ")") or "Feature" ), features ) ) :node( (has_s_features) and p.s_row( (s_featureCount > 1) and "Features" or ( (frame.args["SUPER Var"]) and ("Feature (" .. p.var(frame.args["SUPER Var"]) .. ")") or "Feature" ), s_features ) ) -- Starting values :node( p.row( (has_s_starts), (featureCount > 1) and "Starting values" or ( (frame.args["Var"]) and ("Starting value (" .. ( p.var(frame.args["Var0"] or (frame.args["Var"].."₀") ) ) .. ")") or "Starting value" ), starts ) ) :node( (has_s_starts) and p.s_row( (s_featureCount > 1) and "Starting values" or ( (frame.args["SUPER Var"]) and ("Starting value (" .. ( p.var(frame.args["SUPER Var0"] or (frame.args["SUPER Var"].."₀") ) ) .. ")") or "Starting value" ), s_starts ) ) -- Scaling :node( p.row( (has_s_scalings), "Scaling", scalings) ) :node( (has_s_scalings) and p.s_row("Scaling", s_scalings) ) -- SECTION: Career --[[ Some data will be collected first. ]] -- (Base) Games played local gamesPlayedText = {} if matchCount.total > 0 then table.insert(gamesPlayedText, matchCount.total .. " (total)") if matchCount.standard > 0 then table.insert(gamesPlayedText, matchCount.standard .. " (standard)") end end -- (Base) Winrate local winrateText = {} if matchCount.total > 0 then if matchCount.standard > 0 then table.insert(winrateText, p.roundedPct(matchWinCount.standard,matchCount.standard) .. "% (standard)" ) end end -- Super Games played local s_gamesPlayedText = {} if s_matchCount.total > 0 then table.insert(s_gamesPlayedText, s_matchCount.total .. " (total)") if s_matchCount.standard > 0 then table.insert(s_gamesPlayedText, s_matchCount.standard .. " (standard)") end end -- Super Winrate local s_winrateText = {} if s_matchCount.total > 0 then if s_matchCount.standard > 0 then table.insert(s_winrateText, p.roundedPct(s_matchWinCount.standard,s_matchCount.standard) .. "% (standard)" ) end end --[[ Begin rendering ]] -- Section Heading infobox:node( p.subheading( (isSuper), "Base Career", "Career ") ) :node( (isSuper) and p.s_subheading( "Super Career") ) -- Debuted :node( p.row( (isSuper), "Debut", frame.args["Debut"] ) ) :node( (isSuper) and p.s_row("Debut", frame.args["SUPER Debut"]) ) -- Games played :node( p.row( (isSuper), "Games played", (#gamesPlayedText > 0) and table.concat(gamesPlayedText, "<br>") or "<i>Not enough data...</i>" ) ) :node( (isSuper) and p.s_row( "Games played", (#s_gamesPlayedText > 0) and table.concat(s_gamesPlayedText, "<br>") or "<i>Not enough data...</i>" ) ) -- Winrate :node( p.row( (isSuper), "Winrate", (#winrateText > 0) and table.concat(winrateText, "<br>") or "<i>Not enough data...</i>" ) ) :node( (isSuper) and p.s_row( "Winrate", (#s_winrateText > 0) and table.concat(s_winrateText, "<br>") or "<i>Not enough data...</i>" ) ) return tostring(infobox) end function p.referenceTest() local element = mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( "mw-collapsible" ) :css( "text-align","left" ) local bigElement = mw.html.create( "div" ) :node( mw.clone(element) :attr( "colspan", "2" ) :node( "shitface") ) :node( mw.clone(element) :attr( "colspan", "2" ) :node( "shitface2") ) return tostring(element) .. "\n" .. tostring(bigElement) .. "\n" end function p.roundedPct(num, den) return (num/den % 0.01 < 0.005) and math.floor(num/den * 100) or math.ceil(num/den * 100) end function p.title() --[[local grammatical_cases = { ablative = 1, inessive = { ANCOVA = "ANCOVA" } } local cases2 = "ba" local cases3 = "ba" -- if grammatical_cases.inessive[frame:getParent():getTitle()] then cases2 = "true" else cases2 = "false" end -- if "ANCOVA" == frame:getParent():getTitle() then cases3 = "true" else cases3 = "false" end local detected = false detected = detected or true]] return mw.title.getCurrentTitle() end function p.ifexist() return tonumber(frame:expandTemplate{ title = "User:Helpme2222/Sandbox", args = {frame.args[1]} }) end function p.performance() for i = 1,5000000 do p.tableMake() end return end function p.performance1() local var = "" for i = 1,100000000 do if var[1] then end end return end function p.performance2() local var = "" for i = 1,100000000 do if type(var) == "table" then end end return end p.counter = 0 function p.tableBake() p.counter = p.counter + 1 return p.counter end function p.tableMake() p.counter = 0 local var = { keyword = {p.tableBake()}, kljuczslovo = {p.tableBake()}, yaoshiwenzi = {p.tableBake()}, llavepalabra = {p.tableBake()}, } return var end function p.expand() return frame:expandTemplate{ title = "User:Helpme2222/Sandbox" } end function p.title3() return mw.title.getCurrentTitle().fullText end function p.getBallAttribute() return p.getBallAttributeInternal(frame.args[1], frame.args[2], frame.args[3], frame.args[4]) end function p.getBallAttributeInternal(arg1_table, arg2_ball, arg3_att, arg4_iteration) local _, ballData = pcall( p.getBallAttributeInternalInternal, arg1_table, arg2_ball, arg3_att, arg4_iteration ) if _ then return mw.text.nowiki(ballData) else return "" end end function p.getBallAttributeInternalInternal(arg1_table, arg2_ball, arg3_att, arg4_iteration) local ballData = mw.loadData(arg1_table)[arg2_ball][arg3_att] if ballData[1] then return ballData[tonumber(arg4_iteration) or p.listCountInternal(ballData)] end return ballData end function p.emojiCodepointInternal( emoji ) emoji = mw.text.trim( emoji ) local i,v = mw.ustring.codepoint( emoji, 1, mw.ustring.len(emoji) ) if v then return "U+" .. string.format("%X", i ) .. " U+" .. string.format("%X", v ) else return "U+" .. string.format("%X", i ) end end function p.emojiCodepoint() local emoji = mw.text.trim( mw.getCurrentFrame().args[1] ) local i,v = mw.ustring.codepoint( emoji, 1, mw.ustring.len(emoji) ) if v then return "U+" .. string.format("%X", i ) .. " U+" .. string.format("%X", v ) else return "U+" .. string.format("%X", i ) end end function p.title2() local grammatical_cases = { ablative = 1, inessive = { ANCOVA = "ANCOVA", ["Module:Sandbox/22"] = "Module:Sandbox/22" } } local concepts = { grammatical_cases, } local PAGENAME = tostring(mw.title.getCurrentTitle()) -- local detected = false local out = {} local debugger = {} for i, group in ipairs(concepts) do if group.inessive[PAGENAME] then table.insert(debugger,"Okay, managed TRUE on "..i..":"..group.ablative) -- detected = detected or true local formattedGroup = {} for memberKey, memberRendervalue in pairs(group.inessive) do table.insert(formattedGroup, "<li>" .. memberRendervalue .. "</li>") end table.insert(out, "<h3>" .. group.ablative .. "</h3><ul>" .. table.concat( formattedGroup ) .. "</ul>" ) table.insert(out, "this sucks ass") return "this sucks ass" else table.insert(debugger,"Managed FALSE on "..i..":"..group.ablative..". Comparator: "..PAGENAME..", ") end end return debugger --[[ if detected then return tostring(detected) .. table.concat(out) end return --]] end function p.sanitizeChar(capture) -- If the set of likely illegal characters to appear in title expands, a rewrite of this as a table is merited if capture == "?" then return "" elseif capture == "#" then return "No. " end end function p.sanitizeTitle() local title = frame.args[1] return mw.ustring.gsub( title, "(?:\\?|\\#)", p.sanitizeChar) end function p.sanitizeTitletest2() return mw.ustring.gsub( "Ki vagy? (🌡️🌾⭐🗡️ VS 🪐 🪨 💣 🧿)", "(?:\\?|\\#)", p.sanitizeChar()) end function p.safetyTest() if string.len(frame.args[1]) < 500 then return frame.args[1] else return "" end end --[[ function array_iter(t) local i = 0 return function () i = i + 1 return t[i] end end --]] function p.listInline() --[[ This function is a godsend! https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#mw.text.listToText --]] local spritedTable = {} for i,entry in ipairs(balls[tonumber(frame.args[1])]) do spritedTable[i] = "{{Sprite|named=1|linked=1|"..entry.."}}" end return mw.text.listToText( spritedTable , ", ", ", and " ) end function p.listNavbox() -- https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#table.concat local spritedTable = {} for i,entry in ipairs(balls[tonumber(frame.args[1])]) do spritedTable[i] = "{{Sprite|named=1|linked=1|"..entry.."}}" end return table.concat( spritedTable , " • ") end function p.listCountInternal(table) local count = 0 for index,value in ipairs( table ) do count = count + 1 end return count end function p.listCount() return table.maxn(balls[tonumber(frame.args[1])]) end -- https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#table.maxn function p.tableTest() return balls[1][1] end function p.todaysBall() --[[ https://www.lua.org/pil/3.6.html The use of explicit indexing here is not strictly semantic; it's just to emphasize the rotation order. ]] local unixDay = math.floor(os.time()/86400) local ballTotalCount = 0 local ballCounts = {} for whichTable,subtable in ipairs(balls) do ballCounts[whichTable] = #subtable ballTotalCount = ballTotalCount + ballCounts[whichTable] end local cycleDayIndex, cycleStartingBall = unixDay % ballTotalCount, math.floor(unixDay/ballTotalCount) % ballTotalCount local cycleTodaysBall if ballTotalCount % 7 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*7) % ballTotalCount elseif ballTotalCount % 11 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*11) % ballTotalCount elseif ballTotalCount % 13 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*13) % ballTotalCount else cycleTodaysBall = (cycleStartingBall + cycleDayIndex*(ballTotalCount - 1)) % ballTotalCount end --[[ debug return cycleTodaysBall .. " " .. ballTotalCount .. " " .. os.time() .. " " .. math.floor(os.time()/86400) .. " " .. cycleDayIndex .. " " .. cycleStartingBall ]] for whichTable = 1, #balls do if ballCounts[whichTable] > cycleTodaysBall then return balls[whichTable][cycleTodaysBall + 1] else cycleTodaysBall = cycleTodaysBall - ballCounts[whichTable] end end --]] end return p; hbr32eg3e090dg3fftgt9mv8m5f284c 2835236 2835235 2026-09-30T23:37:48Z Helpme2222 3106525 2835236 Scribunto text/plain -- My function for teaching grammar local p = {}; local frame = mw.getCurrentFrame() local grammatical_moods = { "Jelen ido", "Mult ido", "Felszolito mod", "Felteteles mod" } local balls = { grammatical_moods } function p.teamfightSource() local frame = mw.getCurrentFrame() local pageContent = mw.html.create(nil) local i = 1 while (frame.args["team"..i.."_ball1"]) do local teamTable = mw.html.create("table") :addClass("wikitable sortable") :node( mw.html.create( 'tr' ) :node( mw.html.create( 'th' ):node("Participant") ) :node( mw.html.create( 'th' ):node("Contribution") ) :node( mw.html.create( 'th' ):node("Final scaling value") ) :node( mw.html.create( 'th' ):node("Final health") ) ) local j = 1 while (frame.args["team"..i.."_ball"..j]) do teamTable:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j]) ) -- ball also needs to have form and stuff. :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_score"] --[[..]] --[[get contribution type]]) ) -- test: see wordpad comment :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_scaledTo"] --[[..]] --[[get scaling feature]]) ) :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_health"]) ) ) end pageContent:node( mw.html.create("h3"):node("Team "..i) ) :node( teamTable ) end pageContent:node( mw.html.create("h2"):node("Outcome") ) local j = 1 while (frame.args["team"..frame.args.winningTeam.."_ball"..j]) do pageContent:node( --[[sprite of ball, linked to team section]] ) end pageContent:node( "Team" ) end local toggleButton = mw.html.create( 'span' ) :css({ float = "right", ["margin-right"] = "0", ["font-weight"] = "normal" }) :addClass("mw-customtoggle-Infobox") :node("[Click to toggle]") function p.subheading( discrim, b_content, content ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( (discrim) and "mw-collapsible" ) :node( mw.html.create( 'th' ) :attr( "colspan", "2" ) :css( "text-align","left" ) :node((discrim) and b_content or content) :node((discrim) and toggleButton) ) end function p.s_subheading( s_content ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( "mw-collapsible mw-collapsed" ) :node( mw.html.create( 'th' ) :attr( "colspan", "2" ) :css( "text-align","left" ) :node(s_content) :node(toggleButton) ) end function p.row( discrim, name, data ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( (discrim) and "mw-collapsible" ) :node( mw.html.create( 'td' ) :css( "font-weight","bold" ) :node(name) ) :node( mw.html.create( 'td' ) :node(data) ) end function p.s_row( s_name, s_data ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass("mw-collapsible mw-collapsed") :node( mw.html.create( 'td' ) :css( "font-weight","bold" ) :node(s_name) ) :node( mw.html.create( 'td' ) :node(s_data) ) end function p.var(symbol) return frame:expandTemplate{ title = "Template:Var", args = {symbol} } end function p.iseq() return table.concat({ frame.args[1] .. ( (frame.args[1] == "User:Helpme2222/Sandbox/'") and " is equal to User:Helpme2222/Sandbox/'" or " is not equal to User:Helpme2222/Sandbox/'"), frame.args[1] .. ( (frame.args[1] == "User:Helpme2222/Sandbox/&#039;") and " is equal to User:Helpme2222/Sandbox/&#039;" or " is not equal to User:Helpme2222/Sandbox/&#039;"), frame.args[1] .. ( (frame.args[1] == "Helpme2222/Sandbox/'") and " is equal to Helpme2222/Sandbox/'" or " is not equal to Helpme2222/Sandbox/'"), frame.args[1] .. ( (frame.args[1] == "Helpme2222/Sandbox/&#039;") and " is equal to Helpme2222/Sandbox/&#039;" or " is not equal to Helpme2222/Sandbox/&#039;"), }, "<br>") end function p.iseqNamed() return table.concat({ frame.args.arg .. ( (frame.args.arg == "User:Helpme2222/Sandbox/'") and " is equal to User:Helpme2222/Sandbox/'" or " is not equal to User:Helpme2222/Sandbox/'"), frame.args.arg .. ( (frame.args.arg == "User:Helpme2222/Sandbox/&#039;") and " is equal to User:Helpme2222/Sandbox/&#039;" or " is not equal to User:Helpme2222/Sandbox/&#039;"), frame.args.arg .. ( (frame.args.arg == "Helpme2222/Sandbox/'") and " is equal to Helpme2222/Sandbox/'" or " is not equal to Helpme2222/Sandbox/'"), frame.args.arg .. ( (frame.args.arg == "Helpme2222/Sandbox/&#039;") and " is equal to Helpme2222/Sandbox/&#039;" or " is not equal to Helpme2222/Sandbox/&#039;"), }, "<br>") end function p.infoboxWBB() -- Passing expressions of conditional value: https://www.lua.org/pil/3.3.html --[[ https://www.mediawiki.org/wiki/LUAREF#mw.html:node Thankfully, these operations interpret passed nils as no-ops (I'm technically using false though. Somehow that works anyways?)]] local frame = mw.getCurrentFrame() local ballname = frame.args["Title"] or tostring(mw.title.getCurrentTitle()) local Entities = p -- require("Module:Entities") local featureCount = tonumber(frame.args["Feature count"]) or 1 local s_featureCount = tonumber(frame.args["SUPER Feature count"]) or featureCount local matchCount = { total = mw.site.stats.pagesInCategory( ballname .."'s Match History", "pages" ), standard = mw.site.stats.pagesInCategory( ballname .."'s Match History/Weapon Ball Battles/Standard", "pages" ), } local matchWinCount = { standard = mw.site.stats.pagesInCategory( ballname.."'s Match History/Weapon Ball Battles/Standard/Won", "pages" ), } local s_matchCount = { total = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History", "pages" ), standard = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History/Weapon Ball Battles/Standard", "pages" ), } local s_matchWinCount = { standard = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History/Weapon Ball Battles/Standard/Won", "pages" ), } local isSuper = frame.args["SUPER Feature count"] or frame.args["SUPER Type"] or frame.args["SUPER Debuted"] or (s_matchCount.total > 0) or nil -- for some reason, html:node interprets false-valued parameters as no-op signals, while html:addClass does not. The extra "or nil" had to be added since this is used in :addClass calls. -- TITLE local infobox = mw.html.create( 'table' ) :addClass("wikitable") :css({ float = "right"; ["margin-left"] = "10px" }) :node( mw.html.create( 'tr' ) :node( mw.html.create( 'th' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass((isSuper) and "mw-collapsible" or nil) :node("<big>" .. ballname .. "</big>") ) ) :node((isSuper) and mw.html.create( 'tr' ) :node( mw.html.create( 'th' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass("mw-collapsible mw-collapsed") :node("<big>" .. (frame.args["SUPER Title"] or ("Super " .. ballname)) .. "</big>") ) ) -- IMAGES :node((frame.args["Images"]) and mw.html.create( 'tr' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass((frame.args["SUPER Images"]) and "mw-collapsible") :node( mw.html.create( 'td' ) :node(frame.args["Images"]) ) ) :node((frame.args["SUPER Images"]) and mw.html.create( 'tr' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass("mw-collapsible mw-collapsed") :node( mw.html.create( 'td' ) :node(frame.args["SUPER Images"]) ) ) -- SECTION: Identification -- Section Heading :node( p.subheading( (frame.args["SUPER Type"]), "Base Identification", "Basic Info" ) ) :node( (frame.args["SUPER Type"]) and p.s_subheading( "Super Identification" ) ) -- Type :node( p.row( (frame.args["SUPER Type"]), "Type", frame.args["Type"] ) ) :node( (frame.args["SUPER Type"]) and p.s_row( "Type", frame.args["SUPER Type"] ) ) -- Color local color = frame.args["Color"] or Entities.getBallAttribute( "Entities/Weapon Ball Battles/Balls/Data", ballname, "color" ) infobox:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :css("font-weight", "bold") :node("Color") ) :node( mw.html.create( 'td' ) :node( (color ~= "") and frame:expandTemplate{ title = "Color", args = {color} } or "[[Module:Entities/Weapon Ball Battles/Balls/Data|<i>Add color...</i>]]" ) ) ) -- Emoji local emoji = frame.args["Emoji"] or Entities.getBallAttribute( "Entities/Weapon Ball Battles/Balls/Data", ballname, "emoji" ) infobox:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :css("font-weight", "bold") :node("Emoji") ) :node( mw.html.create( 'td' ) :node( (emoji ~= "") and ( emoji .. " <code>" .. p.emojiCodepointInternal(emoji) .. "</code>") or "[[Module:Entities/Weapon Ball Battles/Balls/Data|<i>Add emoji...</i>]]" ) ) ) -- SECTION: Scaling Characteristics --[[ Some data will be collected first. ]] -- (Base) Behavior local features = {} local starts = {} local scalings = {} if (featureCount > 1) then for i = 1, featureCount do table.insert(features, { frame.args["Feature "..i], " (" .. p.var(frame.args["Var "..i]) .. ")" }) table.insert(starts, { p.var( frame.args["Var0 "..i] or (frame.args["Var "..i].."₀") ) .. ": ", frame.args["Starting value "..i] }) table.insert(scalings, { p.var( "Δ"..(frame.args["Var "..i]) ) .. ": ", frame.args["Scaling "..i] }) end else -- These weird ass tables are meant to be compatible with the clone-and-overwrite operation the supers may undergo if the SUPER feature count, unlike the hypothetical base feature count, is greater than 1 features[1] = {frame.args["Feature"],""} starts[1] = {"",frame.args["Starting value"]} scalings[1] = {"",frame.args["Scaling"]} end -- Super Behavior local s_features local s_starts local s_scalings -- for some reason, html:node interprets false-valued parameters as no-op signals, while html:addClass does not. These booleans below are therefore left undefined (nil) as default. local has_s_features; local has_s_starts; local has_s_scalings; if (frame.args["SUPER Feature count"]) then if s_featureCount > 1 then -- Deep copy base characteristics, i.e. use them as default, overwrite what is explicitly specified as new super data s_features = mw.clone(features) s_starts = mw.clone(starts) s_scalings = mw.clone(scalings) -- If # of super features != # of base features, trim or expand the deep-copied tables accordingly. Avoid index errors. if s_featureCount > featureCount then for i = featureCount + 1, s_featureCount do table.insert( s_features, {"",""} ) table.insert( s_starts, {"",""} ) table.insert( s_scalings, {"",""} ) end elseif s_featureCount < featureCount then for i = s_featureCount + 1, featureCount do s_features[i] = nil s_starts[i] = nil s_scalings[i] = nil end end -- Parse super data, set the has_s_... flags if triggered for i = 1,s_featureCount do if frame.args["SUPER Feature "..i] then s_features[i][1] = frame.args["SUPER Feature "..i] if (not has_s_features) then has_s_features = true end end if frame.args["SUPER Starting value "..i] then s_starts[i][2] = frame.args["SUPER Starting value "..i] if (not has_s_starts) then has_s_starts = true end end if frame.args["SUPER Scaling "..i] then s_scalings[i][2] = frame.args["SUPER Scaling "..i] if (not has_s_scalings) then has_s_scalings = true end end if frame.args["SUPER Var "..i] then s_features[i][2] = " (" .. p.var(frame.args["SUPER Var "..i]) .. ")" s_starts[i][1] = p.var( frame.args["SUPER Var0 "..i] or (frame.args["SUPER Var "..i].."₀") ) .. ": " s_scalings[i][1] = p.var( '<span style="font-style:normal">Δ</span>'..(frame.args["SUPER Var "..i]) ) .. ": " if (not has_s_features) then has_s_features = true end if (not has_s_starts) then has_s_starts = true end if (not has_s_scalings) then has_s_scalings = true end end s_features[i] = table.concat(s_features[i]) s_starts[i] = table.concat(s_starts[i]) s_scalings[i] = table.concat(s_scalings[i]) end s_features = table.concat(s_features,"<br>") s_starts = table.concat(s_starts,"<br>") s_scalings = table.concat(s_scalings,"<br>") else -- # of super features = 1? just write directly to the variable if frame.args["SUPER Var"] or frame.args["SUPER Feature"] then has_s_features = true s_features = frame.args["SUPER Feature"] end if frame.args["SUPER Var0"] or frame.args["SUPER Var"] or frame.args["SUPER Starting value"] then has_s_starts = true s_starts = frame.args["SUPER Starting value"] end if frame.args["SUPER Scaling"] then has_s_scalings = true s_scalings = frame.args["SUPER Scaling"] end end end -- finalize base data as strings now that work is otherwise complete if (featureCount > 1) then for i = 1, featureCount do features[i] = table.concat(features[i]) starts[i] = table.concat(starts[i]) scalings[i] = table.concat(scalings[i]) end features = table.concat(features,"<br>") starts = table.concat(starts,"<br>") scalings = table.concat(scalings,"<br>") else features = features[1][1] starts = starts[1][2] scalings = scalings[1][2] end --[[ Begin rendering ]] -- Section Heading infobox:node( p.subheading( (frame.args["SUPER Feature count"]), "Base Scaling Characteristics", "Scaling Characteristics" ) ) :node( (frame.args["SUPER Feature count"]) and p.s_subheading( "Super Scaling Characteristics" ) ) -- Features :node( p.row( (has_s_features), (featureCount > 1) and "Features" or ( (frame.args["Var"]) and ("Feature (" .. p.var(frame.args["Var"]) .. ")") or "Feature" ), features ) ) :node( (has_s_features) and p.s_row( (s_featureCount > 1) and "Features" or ( (frame.args["SUPER Var"]) and ("Feature (" .. p.var(frame.args["SUPER Var"]) .. ")") or "Feature" ), s_features ) ) -- Starting values :node( p.row( (has_s_starts), (featureCount > 1) and "Starting values" or ( (frame.args["Var"]) and ("Starting value (" .. ( p.var(frame.args["Var0"] or (frame.args["Var"].."₀") ) ) .. ")") or "Starting value" ), starts ) ) :node( (has_s_starts) and p.s_row( (s_featureCount > 1) and "Starting values" or ( (frame.args["SUPER Var"]) and ("Starting value (" .. ( p.var(frame.args["SUPER Var0"] or (frame.args["SUPER Var"].."₀") ) ) .. ")") or "Starting value" ), s_starts ) ) -- Scaling :node( p.row( (has_s_scalings), "Scaling", scalings) ) :node( (has_s_scalings) and p.s_row("Scaling", s_scalings) ) -- SECTION: Career --[[ Some data will be collected first. ]] -- (Base) Games played local gamesPlayedText = {} if matchCount.total > 0 then table.insert(gamesPlayedText, matchCount.total .. " (total)") if matchCount.standard > 0 then table.insert(gamesPlayedText, matchCount.standard .. " (standard)") end end -- (Base) Winrate local winrateText = {} if matchCount.total > 0 then if matchCount.standard > 0 then table.insert(winrateText, p.roundedPct(matchWinCount.standard,matchCount.standard) .. "% (standard)" ) end end -- Super Games played local s_gamesPlayedText = {} if s_matchCount.total > 0 then table.insert(s_gamesPlayedText, s_matchCount.total .. " (total)") if s_matchCount.standard > 0 then table.insert(s_gamesPlayedText, s_matchCount.standard .. " (standard)") end end -- Super Winrate local s_winrateText = {} if s_matchCount.total > 0 then if s_matchCount.standard > 0 then table.insert(s_winrateText, p.roundedPct(s_matchWinCount.standard,s_matchCount.standard) .. "% (standard)" ) end end --[[ Begin rendering ]] -- Section Heading infobox:node( p.subheading( (isSuper), "Base Career", "Career ") ) :node( (isSuper) and p.s_subheading( "Super Career") ) -- Debuted :node( p.row( (isSuper), "Debut", frame.args["Debut"] ) ) :node( (isSuper) and p.s_row("Debut", frame.args["SUPER Debut"]) ) -- Games played :node( p.row( (isSuper), "Games played", (#gamesPlayedText > 0) and table.concat(gamesPlayedText, "<br>") or "<i>Not enough data...</i>" ) ) :node( (isSuper) and p.s_row( "Games played", (#s_gamesPlayedText > 0) and table.concat(s_gamesPlayedText, "<br>") or "<i>Not enough data...</i>" ) ) -- Winrate :node( p.row( (isSuper), "Winrate", (#winrateText > 0) and table.concat(winrateText, "<br>") or "<i>Not enough data...</i>" ) ) :node( (isSuper) and p.s_row( "Winrate", (#s_winrateText > 0) and table.concat(s_winrateText, "<br>") or "<i>Not enough data...</i>" ) ) return tostring(infobox) end function p.referenceTest() local element = mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( "mw-collapsible" ) :css( "text-align","left" ) local bigElement = mw.html.create( "div" ) :node( mw.clone(element) :attr( "colspan", "2" ) :node( "shitface") ) :node( mw.clone(element) :attr( "colspan", "2" ) :node( "shitface2") ) return tostring(element) .. "\n" .. tostring(bigElement) .. "\n" end function p.roundedPct(num, den) return (num/den % 0.01 < 0.005) and math.floor(num/den * 100) or math.ceil(num/den * 100) end function p.title() --[[local grammatical_cases = { ablative = 1, inessive = { ANCOVA = "ANCOVA" } } local cases2 = "ba" local cases3 = "ba" -- if grammatical_cases.inessive[frame:getParent():getTitle()] then cases2 = "true" else cases2 = "false" end -- if "ANCOVA" == frame:getParent():getTitle() then cases3 = "true" else cases3 = "false" end local detected = false detected = detected or true]] return mw.title.getCurrentTitle() end function p.ifexist() return tonumber(frame:expandTemplate{ title = "User:Helpme2222/Sandbox", args = {frame.args[1]} }) end function p.performance() for i = 1,5000000 do p.tableMake() end return end function p.performance1() local var = "" for i = 1,100000000 do if var[1] then end end return end function p.performance2() local var = "" for i = 1,100000000 do if type(var) == "table" then end end return end p.counter = 0 function p.tableBake() p.counter = p.counter + 1 return p.counter end function p.tableMake() p.counter = 0 local var = { keyword = {p.tableBake()}, kljuczslovo = {p.tableBake()}, yaoshiwenzi = {p.tableBake()}, llavepalabra = {p.tableBake()}, } return var end function p.expand() return frame:expandTemplate{ title = "User:Helpme2222/Sandbox" } end function p.title3() return mw.title.getCurrentTitle().fullText end function p.getBallAttribute() return p.getBallAttributeInternal(frame.args[1], frame.args[2], frame.args[3], frame.args[4]) end function p.getBallAttributeInternal(arg1_table, arg2_ball, arg3_att, arg4_iteration) local _, ballData = pcall( p.getBallAttributeInternalInternal, arg1_table, arg2_ball, arg3_att, arg4_iteration ) if _ then return mw.text.nowiki(ballData) else return "" end end function p.getBallAttributeInternalInternal(arg1_table, arg2_ball, arg3_att, arg4_iteration) local ballData = mw.loadData(arg1_table)[arg2_ball][arg3_att] if ballData[1] then return ballData[tonumber(arg4_iteration) or p.listCountInternal(ballData)] end return ballData end function p.emojiCodepointInternal( emoji ) emoji = mw.text.trim( emoji ) local i,v = mw.ustring.codepoint( emoji, 1, mw.ustring.len(emoji) ) if v then return "U+" .. string.format("%X", i ) .. " U+" .. string.format("%X", v ) else return "U+" .. string.format("%X", i ) end end function p.emojiCodepoint() local emoji = mw.text.trim( mw.getCurrentFrame().args[1] ) local i,v = mw.ustring.codepoint( emoji, 1, mw.ustring.len(emoji) ) if v then return "U+" .. string.format("%X", i ) .. " U+" .. string.format("%X", v ) else return "U+" .. string.format("%X", i ) end end function p.title2() local grammatical_cases = { ablative = 1, inessive = { ANCOVA = "ANCOVA", ["Module:Sandbox/22"] = "Module:Sandbox/22" } } local concepts = { grammatical_cases, } local PAGENAME = tostring(mw.title.getCurrentTitle()) -- local detected = false local out = {} local debugger = {} for i, group in ipairs(concepts) do if group.inessive[PAGENAME] then table.insert(debugger,"Okay, managed TRUE on "..i..":"..group.ablative) -- detected = detected or true local formattedGroup = {} for memberKey, memberRendervalue in pairs(group.inessive) do table.insert(formattedGroup, "<li>" .. memberRendervalue .. "</li>") end table.insert(out, "<h3>" .. group.ablative .. "</h3><ul>" .. table.concat( formattedGroup ) .. "</ul>" ) table.insert(out, "this sucks ass") return "this sucks ass" else table.insert(debugger,"Managed FALSE on "..i..":"..group.ablative..". Comparator: "..PAGENAME..", ") end end return debugger --[[ if detected then return tostring(detected) .. table.concat(out) end return --]] end function p.sanitizeChar(capture) -- If the set of likely illegal characters to appear in title expands, a rewrite of this as a table is merited if capture == "?" then return "" elseif capture == "#" then return "No. " end end function p.sanitizeTitle() local title = frame.args[1] return mw.ustring.gsub( title, "(?:\\?|\\#)", p.sanitizeChar) end function p.sanitizeTitletest2() return mw.ustring.gsub( "Ki vagy? (🌡️🌾⭐🗡️ VS 🪐 🪨 💣 🧿)", "(?:\\?|\\#)", p.sanitizeChar()) end function p.safetyTest() if string.len(frame.args[1]) < 500 then return frame.args[1] else return "" end end --[[ function array_iter(t) local i = 0 return function () i = i + 1 return t[i] end end --]] function p.listInline() --[[ This function is a godsend! https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#mw.text.listToText --]] local spritedTable = {} for i,entry in ipairs(balls[tonumber(frame.args[1])]) do spritedTable[i] = "{{Sprite|named=1|linked=1|"..entry.."}}" end return mw.text.listToText( spritedTable , ", ", ", and " ) end function p.listNavbox() -- https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#table.concat local spritedTable = {} for i,entry in ipairs(balls[tonumber(frame.args[1])]) do spritedTable[i] = "{{Sprite|named=1|linked=1|"..entry.."}}" end return table.concat( spritedTable , " • ") end function p.listCountInternal(table) local count = 0 for index,value in ipairs( table ) do count = count + 1 end return count end function p.listCount() return table.maxn(balls[tonumber(frame.args[1])]) end -- https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#table.maxn function p.tableTest() return balls[1][1] end function p.todaysBall() --[[ https://www.lua.org/pil/3.6.html The use of explicit indexing here is not strictly semantic; it's just to emphasize the rotation order. ]] local unixDay = math.floor(os.time()/86400) local ballTotalCount = 0 local ballCounts = {} for whichTable,subtable in ipairs(balls) do ballCounts[whichTable] = #subtable ballTotalCount = ballTotalCount + ballCounts[whichTable] end local cycleDayIndex, cycleStartingBall = unixDay % ballTotalCount, math.floor(unixDay/ballTotalCount) % ballTotalCount local cycleTodaysBall if ballTotalCount % 7 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*7) % ballTotalCount elseif ballTotalCount % 11 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*11) % ballTotalCount elseif ballTotalCount % 13 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*13) % ballTotalCount else cycleTodaysBall = (cycleStartingBall + cycleDayIndex*(ballTotalCount - 1)) % ballTotalCount end --[[ debug return cycleTodaysBall .. " " .. ballTotalCount .. " " .. os.time() .. " " .. math.floor(os.time()/86400) .. " " .. cycleDayIndex .. " " .. cycleStartingBall ]] for whichTable = 1, #balls do if ballCounts[whichTable] > cycleTodaysBall then return balls[whichTable][cycleTodaysBall + 1] else cycleTodaysBall = cycleTodaysBall - ballCounts[whichTable] end end --]] end return p; 6aawk21hlte08e1zn0lhphophwk8ayi 2835237 2835236 2026-09-30T23:39:07Z Helpme2222 3106525 2835237 Scribunto text/plain -- My function for teaching grammar local p = {}; local frame = mw.getCurrentFrame() local grammatical_moods = { "Jelen ido", "Mult ido", "Felszolito mod", "Felteteles mod" } local balls = { grammatical_moods } function p.teamfightSource() local frame = mw.getCurrentFrame() local pageContent = mw.html.create(nil) local i = 1 while (frame.args["team"..i.."_ball1"]) do local teamTable = mw.html.create("table") :addClass("wikitable sortable") :node( mw.html.create( 'tr' ) :node( mw.html.create( 'th' ):node("Participant") ) :node( mw.html.create( 'th' ):node("Contribution") ) :node( mw.html.create( 'th' ):node("Final scaling value") ) :node( mw.html.create( 'th' ):node("Final health") ) ) local j = 1 while (frame.args["team"..i.."_ball"..j]) do teamTable:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j]) ) -- ball also needs to have form and stuff. :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_score"] --[[..]] --[[get contribution type]]) ) -- test: see wordpad comment :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_scaledTo"] --[[..]] --[[get scaling feature]]) ) :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_health"]) ) ) end pageContent:node( mw.html.create("h3"):node("Team "..i) ) :node( teamTable ) end pageContent:node( mw.html.create("h2"):node("Outcome") ) local j = 1 while (frame.args["team"..frame.args.winningTeam.."_ball"..j]) do pageContent:node( --[[sprite of ball, linked to team section]] ) end pageContent:node( "Team" ) end local toggleButton = mw.html.create( 'span' ) :css({ float = "right", ["margin-right"] = "0", ["font-weight"] = "normal" }) :addClass("mw-customtoggle-Infobox") :node("[Click to toggle]") function p.subheading( discrim, b_content, content ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( (discrim) and "mw-collapsible" ) :node( mw.html.create( 'th' ) :attr( "colspan", "2" ) :css( "text-align","left" ) :node((discrim) and b_content or content) :node((discrim) and toggleButton) ) end function p.s_subheading( s_content ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( "mw-collapsible mw-collapsed" ) :node( mw.html.create( 'th' ) :attr( "colspan", "2" ) :css( "text-align","left" ) :node(s_content) :node(toggleButton) ) end function p.row( discrim, name, data ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( (discrim) and "mw-collapsible" ) :node( mw.html.create( 'td' ) :css( "font-weight","bold" ) :node(name) ) :node( mw.html.create( 'td' ) :node(data) ) end function p.s_row( s_name, s_data ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass("mw-collapsible mw-collapsed") :node( mw.html.create( 'td' ) :css( "font-weight","bold" ) :node(s_name) ) :node( mw.html.create( 'td' ) :node(s_data) ) end function p.var(symbol) return frame:expandTemplate{ title = "Template:Var", args = {symbol} } end function p.iseq() return table.concat({ frame.args[1] .. ( (frame.args[1] == "User:Helpme2222/Sandbox/'") and " is equal to User:Helpme2222/Sandbox/'" or " is not equal to User:Helpme2222/Sandbox/'"), frame.args[1] .. ( (frame.args[1] == "User:Helpme2222/Sandbox/&#039;") and " is equal to User:Helpme2222/Sandbox/&#039;" or " is not equal to User:Helpme2222/Sandbox/&#039;"), frame.args[1] .. ( (frame.args[1] == "Helpme2222/Sandbox/'") and " is equal to Helpme2222/Sandbox/'" or " is not equal to Helpme2222/Sandbox/'"), frame.args[1] .. ( (frame.args[1] == "Helpme2222/Sandbox/&#039;") and " is equal to Helpme2222/Sandbox/&#039;" or " is not equal to Helpme2222/Sandbox/&#039;"), }, "<br>") end function p.iseqNamed() return table.concat({ frame.args.arg .. ( (frame.args.arg == "User:Helpme2222/Sandbox/'") and " is equal to User:Helpme2222/Sandbox/'" or " is not equal to User:Helpme2222/Sandbox/'"), frame.args.arg .. ( (frame.args.arg == "User:Helpme2222/Sandbox/&#039;") and " is equal to User:Helpme2222/Sandbox/&#039;" or " is not equal to User:Helpme2222/Sandbox/&#039;"), frame.args.arg .. ( (frame.args.arg == "Helpme2222/Sandbox/'") and " is equal to Helpme2222/Sandbox/'" or " is not equal to Helpme2222/Sandbox/'"), frame.args.arg .. ( (frame.args.arg == "Helpme2222/Sandbox/&#039;") and " is equal to Helpme2222/Sandbox/&#039;" or " is not equal to Helpme2222/Sandbox/&#039;"), }, "<br>") end function p.infoboxWBB() -- Passing expressions of conditional value: https://www.lua.org/pil/3.3.html --[[ https://www.mediawiki.org/wiki/LUAREF#mw.html:node Thankfully, these operations interpret passed nils as no-ops (I'm technically using false though. Somehow that works anyways?)]] local frame = mw.getCurrentFrame() local ballname = frame.args["Title"] or tostring(mw.title.getCurrentTitle()) local Entities = p -- require("Module:Entities") local featureCount = tonumber(frame.args["Feature count"]) or 1 local s_featureCount = tonumber(frame.args["SUPER Feature count"]) or featureCount local matchCount = { total = mw.site.stats.pagesInCategory( ballname .."'s Match History", "pages" ), standard = mw.site.stats.pagesInCategory( ballname .."'s Match History/Weapon Ball Battles/Standard", "pages" ), } local matchWinCount = { standard = mw.site.stats.pagesInCategory( ballname.."'s Match History/Weapon Ball Battles/Standard/Won", "pages" ), } local s_matchCount = { total = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History", "pages" ), standard = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History/Weapon Ball Battles/Standard", "pages" ), } local s_matchWinCount = { standard = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History/Weapon Ball Battles/Standard/Won", "pages" ), } local isSuper = frame.args["SUPER Feature count"] or frame.args["SUPER Type"] or frame.args["SUPER Debuted"] or (s_matchCount.total > 0) or nil -- for some reason, html:node interprets false-valued parameters as no-op signals, while html:addClass does not. The extra "or nil" had to be added since this is used in :addClass calls. -- TITLE local infobox = mw.html.create( 'table' ) :addClass("wikitable") :css({ float = "right"; ["margin-left"] = "10px" }) :node( mw.html.create( 'tr' ) :node( mw.html.create( 'th' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass((isSuper) and "mw-collapsible" or nil) :node("<big>" .. ballname .. "</big>") ) ) :node((isSuper) and mw.html.create( 'tr' ) :node( mw.html.create( 'th' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass("mw-collapsible mw-collapsed") :node("<big>" .. (frame.args["SUPER Title"] or ("Super " .. ballname)) .. "</big>") ) ) -- IMAGES :node((frame.args["Images"]) and (mw.html.create( 'tr' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass((frame.args["SUPER Images"]) and "mw-collapsible") :node( mw.html.create( 'td' ) :node(frame.args["Images"]) )) ) :node((frame.args["SUPER Images"]) and (mw.html.create( 'tr' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass("mw-collapsible mw-collapsed") :node( mw.html.create( 'td' ) :node(frame.args["SUPER Images"]) )) ) -- SECTION: Identification -- Section Heading :node( p.subheading( (frame.args["SUPER Type"]), "Base Identification", "Basic Info" ) ) :node( (frame.args["SUPER Type"]) and p.s_subheading( "Super Identification" ) ) -- Type :node( p.row( (frame.args["SUPER Type"]), "Type", frame.args["Type"] ) ) :node( (frame.args["SUPER Type"]) and p.s_row( "Type", frame.args["SUPER Type"] ) ) -- Color local color = frame.args["Color"] or Entities.getBallAttribute( "Entities/Weapon Ball Battles/Balls/Data", ballname, "color" ) infobox:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :css("font-weight", "bold") :node("Color") ) :node( mw.html.create( 'td' ) :node( (color ~= "") and frame:expandTemplate{ title = "Color", args = {color} } or "[[Module:Entities/Weapon Ball Battles/Balls/Data|<i>Add color...</i>]]" ) ) ) -- Emoji local emoji = frame.args["Emoji"] or Entities.getBallAttribute( "Entities/Weapon Ball Battles/Balls/Data", ballname, "emoji" ) infobox:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :css("font-weight", "bold") :node("Emoji") ) :node( mw.html.create( 'td' ) :node( (emoji ~= "") and ( emoji .. " <code>" .. p.emojiCodepointInternal(emoji) .. "</code>") or "[[Module:Entities/Weapon Ball Battles/Balls/Data|<i>Add emoji...</i>]]" ) ) ) -- SECTION: Scaling Characteristics --[[ Some data will be collected first. ]] -- (Base) Behavior local features = {} local starts = {} local scalings = {} if (featureCount > 1) then for i = 1, featureCount do table.insert(features, { frame.args["Feature "..i], " (" .. p.var(frame.args["Var "..i]) .. ")" }) table.insert(starts, { p.var( frame.args["Var0 "..i] or (frame.args["Var "..i].."₀") ) .. ": ", frame.args["Starting value "..i] }) table.insert(scalings, { p.var( "Δ"..(frame.args["Var "..i]) ) .. ": ", frame.args["Scaling "..i] }) end else -- These weird ass tables are meant to be compatible with the clone-and-overwrite operation the supers may undergo if the SUPER feature count, unlike the hypothetical base feature count, is greater than 1 features[1] = {frame.args["Feature"],""} starts[1] = {"",frame.args["Starting value"]} scalings[1] = {"",frame.args["Scaling"]} end -- Super Behavior local s_features local s_starts local s_scalings -- for some reason, html:node interprets false-valued parameters as no-op signals, while html:addClass does not. These booleans below are therefore left undefined (nil) as default. local has_s_features; local has_s_starts; local has_s_scalings; if (frame.args["SUPER Feature count"]) then if s_featureCount > 1 then -- Deep copy base characteristics, i.e. use them as default, overwrite what is explicitly specified as new super data s_features = mw.clone(features) s_starts = mw.clone(starts) s_scalings = mw.clone(scalings) -- If # of super features != # of base features, trim or expand the deep-copied tables accordingly. Avoid index errors. if s_featureCount > featureCount then for i = featureCount + 1, s_featureCount do table.insert( s_features, {"",""} ) table.insert( s_starts, {"",""} ) table.insert( s_scalings, {"",""} ) end elseif s_featureCount < featureCount then for i = s_featureCount + 1, featureCount do s_features[i] = nil s_starts[i] = nil s_scalings[i] = nil end end -- Parse super data, set the has_s_... flags if triggered for i = 1,s_featureCount do if frame.args["SUPER Feature "..i] then s_features[i][1] = frame.args["SUPER Feature "..i] if (not has_s_features) then has_s_features = true end end if frame.args["SUPER Starting value "..i] then s_starts[i][2] = frame.args["SUPER Starting value "..i] if (not has_s_starts) then has_s_starts = true end end if frame.args["SUPER Scaling "..i] then s_scalings[i][2] = frame.args["SUPER Scaling "..i] if (not has_s_scalings) then has_s_scalings = true end end if frame.args["SUPER Var "..i] then s_features[i][2] = " (" .. p.var(frame.args["SUPER Var "..i]) .. ")" s_starts[i][1] = p.var( frame.args["SUPER Var0 "..i] or (frame.args["SUPER Var "..i].."₀") ) .. ": " s_scalings[i][1] = p.var( '<span style="font-style:normal">Δ</span>'..(frame.args["SUPER Var "..i]) ) .. ": " if (not has_s_features) then has_s_features = true end if (not has_s_starts) then has_s_starts = true end if (not has_s_scalings) then has_s_scalings = true end end s_features[i] = table.concat(s_features[i]) s_starts[i] = table.concat(s_starts[i]) s_scalings[i] = table.concat(s_scalings[i]) end s_features = table.concat(s_features,"<br>") s_starts = table.concat(s_starts,"<br>") s_scalings = table.concat(s_scalings,"<br>") else -- # of super features = 1? just write directly to the variable if frame.args["SUPER Var"] or frame.args["SUPER Feature"] then has_s_features = true s_features = frame.args["SUPER Feature"] end if frame.args["SUPER Var0"] or frame.args["SUPER Var"] or frame.args["SUPER Starting value"] then has_s_starts = true s_starts = frame.args["SUPER Starting value"] end if frame.args["SUPER Scaling"] then has_s_scalings = true s_scalings = frame.args["SUPER Scaling"] end end end -- finalize base data as strings now that work is otherwise complete if (featureCount > 1) then for i = 1, featureCount do features[i] = table.concat(features[i]) starts[i] = table.concat(starts[i]) scalings[i] = table.concat(scalings[i]) end features = table.concat(features,"<br>") starts = table.concat(starts,"<br>") scalings = table.concat(scalings,"<br>") else features = features[1][1] starts = starts[1][2] scalings = scalings[1][2] end --[[ Begin rendering ]] -- Section Heading infobox:node( p.subheading( (frame.args["SUPER Feature count"]), "Base Scaling Characteristics", "Scaling Characteristics" ) ) :node( (frame.args["SUPER Feature count"]) and p.s_subheading( "Super Scaling Characteristics" ) ) -- Features :node( p.row( (has_s_features), (featureCount > 1) and "Features" or ( (frame.args["Var"]) and ("Feature (" .. p.var(frame.args["Var"]) .. ")") or "Feature" ), features ) ) :node( (has_s_features) and p.s_row( (s_featureCount > 1) and "Features" or ( (frame.args["SUPER Var"]) and ("Feature (" .. p.var(frame.args["SUPER Var"]) .. ")") or "Feature" ), s_features ) ) -- Starting values :node( p.row( (has_s_starts), (featureCount > 1) and "Starting values" or ( (frame.args["Var"]) and ("Starting value (" .. ( p.var(frame.args["Var0"] or (frame.args["Var"].."₀") ) ) .. ")") or "Starting value" ), starts ) ) :node( (has_s_starts) and p.s_row( (s_featureCount > 1) and "Starting values" or ( (frame.args["SUPER Var"]) and ("Starting value (" .. ( p.var(frame.args["SUPER Var0"] or (frame.args["SUPER Var"].."₀") ) ) .. ")") or "Starting value" ), s_starts ) ) -- Scaling :node( p.row( (has_s_scalings), "Scaling", scalings) ) :node( (has_s_scalings) and p.s_row("Scaling", s_scalings) ) -- SECTION: Career --[[ Some data will be collected first. ]] -- (Base) Games played local gamesPlayedText = {} if matchCount.total > 0 then table.insert(gamesPlayedText, matchCount.total .. " (total)") if matchCount.standard > 0 then table.insert(gamesPlayedText, matchCount.standard .. " (standard)") end end -- (Base) Winrate local winrateText = {} if matchCount.total > 0 then if matchCount.standard > 0 then table.insert(winrateText, p.roundedPct(matchWinCount.standard,matchCount.standard) .. "% (standard)" ) end end -- Super Games played local s_gamesPlayedText = {} if s_matchCount.total > 0 then table.insert(s_gamesPlayedText, s_matchCount.total .. " (total)") if s_matchCount.standard > 0 then table.insert(s_gamesPlayedText, s_matchCount.standard .. " (standard)") end end -- Super Winrate local s_winrateText = {} if s_matchCount.total > 0 then if s_matchCount.standard > 0 then table.insert(s_winrateText, p.roundedPct(s_matchWinCount.standard,s_matchCount.standard) .. "% (standard)" ) end end --[[ Begin rendering ]] -- Section Heading infobox:node( p.subheading( (isSuper), "Base Career", "Career ") ) :node( (isSuper) and p.s_subheading( "Super Career") ) -- Debuted :node( p.row( (isSuper), "Debut", frame.args["Debut"] ) ) :node( (isSuper) and p.s_row("Debut", frame.args["SUPER Debut"]) ) -- Games played :node( p.row( (isSuper), "Games played", (#gamesPlayedText > 0) and table.concat(gamesPlayedText, "<br>") or "<i>Not enough data...</i>" ) ) :node( (isSuper) and p.s_row( "Games played", (#s_gamesPlayedText > 0) and table.concat(s_gamesPlayedText, "<br>") or "<i>Not enough data...</i>" ) ) -- Winrate :node( p.row( (isSuper), "Winrate", (#winrateText > 0) and table.concat(winrateText, "<br>") or "<i>Not enough data...</i>" ) ) :node( (isSuper) and p.s_row( "Winrate", (#s_winrateText > 0) and table.concat(s_winrateText, "<br>") or "<i>Not enough data...</i>" ) ) return tostring(infobox) end function p.referenceTest() local element = mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( "mw-collapsible" ) :css( "text-align","left" ) local bigElement = mw.html.create( "div" ) :node( mw.clone(element) :attr( "colspan", "2" ) :node( "shitface") ) :node( mw.clone(element) :attr( "colspan", "2" ) :node( "shitface2") ) return tostring(element) .. "\n" .. tostring(bigElement) .. "\n" end function p.roundedPct(num, den) return (num/den % 0.01 < 0.005) and math.floor(num/den * 100) or math.ceil(num/den * 100) end function p.title() --[[local grammatical_cases = { ablative = 1, inessive = { ANCOVA = "ANCOVA" } } local cases2 = "ba" local cases3 = "ba" -- if grammatical_cases.inessive[frame:getParent():getTitle()] then cases2 = "true" else cases2 = "false" end -- if "ANCOVA" == frame:getParent():getTitle() then cases3 = "true" else cases3 = "false" end local detected = false detected = detected or true]] return mw.title.getCurrentTitle() end function p.ifexist() return tonumber(frame:expandTemplate{ title = "User:Helpme2222/Sandbox", args = {frame.args[1]} }) end function p.performance() for i = 1,5000000 do p.tableMake() end return end function p.performance1() local var = "" for i = 1,100000000 do if var[1] then end end return end function p.performance2() local var = "" for i = 1,100000000 do if type(var) == "table" then end end return end p.counter = 0 function p.tableBake() p.counter = p.counter + 1 return p.counter end function p.tableMake() p.counter = 0 local var = { keyword = {p.tableBake()}, kljuczslovo = {p.tableBake()}, yaoshiwenzi = {p.tableBake()}, llavepalabra = {p.tableBake()}, } return var end function p.expand() return frame:expandTemplate{ title = "User:Helpme2222/Sandbox" } end function p.title3() return mw.title.getCurrentTitle().fullText end function p.getBallAttribute() return p.getBallAttributeInternal(frame.args[1], frame.args[2], frame.args[3], frame.args[4]) end function p.getBallAttributeInternal(arg1_table, arg2_ball, arg3_att, arg4_iteration) local _, ballData = pcall( p.getBallAttributeInternalInternal, arg1_table, arg2_ball, arg3_att, arg4_iteration ) if _ then return mw.text.nowiki(ballData) else return "" end end function p.getBallAttributeInternalInternal(arg1_table, arg2_ball, arg3_att, arg4_iteration) local ballData = mw.loadData(arg1_table)[arg2_ball][arg3_att] if ballData[1] then return ballData[tonumber(arg4_iteration) or p.listCountInternal(ballData)] end return ballData end function p.emojiCodepointInternal( emoji ) emoji = mw.text.trim( emoji ) local i,v = mw.ustring.codepoint( emoji, 1, mw.ustring.len(emoji) ) if v then return "U+" .. string.format("%X", i ) .. " U+" .. string.format("%X", v ) else return "U+" .. string.format("%X", i ) end end function p.emojiCodepoint() local emoji = mw.text.trim( mw.getCurrentFrame().args[1] ) local i,v = mw.ustring.codepoint( emoji, 1, mw.ustring.len(emoji) ) if v then return "U+" .. string.format("%X", i ) .. " U+" .. string.format("%X", v ) else return "U+" .. string.format("%X", i ) end end function p.title2() local grammatical_cases = { ablative = 1, inessive = { ANCOVA = "ANCOVA", ["Module:Sandbox/22"] = "Module:Sandbox/22" } } local concepts = { grammatical_cases, } local PAGENAME = tostring(mw.title.getCurrentTitle()) -- local detected = false local out = {} local debugger = {} for i, group in ipairs(concepts) do if group.inessive[PAGENAME] then table.insert(debugger,"Okay, managed TRUE on "..i..":"..group.ablative) -- detected = detected or true local formattedGroup = {} for memberKey, memberRendervalue in pairs(group.inessive) do table.insert(formattedGroup, "<li>" .. memberRendervalue .. "</li>") end table.insert(out, "<h3>" .. group.ablative .. "</h3><ul>" .. table.concat( formattedGroup ) .. "</ul>" ) table.insert(out, "this sucks ass") return "this sucks ass" else table.insert(debugger,"Managed FALSE on "..i..":"..group.ablative..". Comparator: "..PAGENAME..", ") end end return debugger --[[ if detected then return tostring(detected) .. table.concat(out) end return --]] end function p.sanitizeChar(capture) -- If the set of likely illegal characters to appear in title expands, a rewrite of this as a table is merited if capture == "?" then return "" elseif capture == "#" then return "No. " end end function p.sanitizeTitle() local title = frame.args[1] return mw.ustring.gsub( title, "(?:\\?|\\#)", p.sanitizeChar) end function p.sanitizeTitletest2() return mw.ustring.gsub( "Ki vagy? (🌡️🌾⭐🗡️ VS 🪐 🪨 💣 🧿)", "(?:\\?|\\#)", p.sanitizeChar()) end function p.safetyTest() if string.len(frame.args[1]) < 500 then return frame.args[1] else return "" end end --[[ function array_iter(t) local i = 0 return function () i = i + 1 return t[i] end end --]] function p.listInline() --[[ This function is a godsend! https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#mw.text.listToText --]] local spritedTable = {} for i,entry in ipairs(balls[tonumber(frame.args[1])]) do spritedTable[i] = "{{Sprite|named=1|linked=1|"..entry.."}}" end return mw.text.listToText( spritedTable , ", ", ", and " ) end function p.listNavbox() -- https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#table.concat local spritedTable = {} for i,entry in ipairs(balls[tonumber(frame.args[1])]) do spritedTable[i] = "{{Sprite|named=1|linked=1|"..entry.."}}" end return table.concat( spritedTable , " • ") end function p.listCountInternal(table) local count = 0 for index,value in ipairs( table ) do count = count + 1 end return count end function p.listCount() return table.maxn(balls[tonumber(frame.args[1])]) end -- https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#table.maxn function p.tableTest() return balls[1][1] end function p.todaysBall() --[[ https://www.lua.org/pil/3.6.html The use of explicit indexing here is not strictly semantic; it's just to emphasize the rotation order. ]] local unixDay = math.floor(os.time()/86400) local ballTotalCount = 0 local ballCounts = {} for whichTable,subtable in ipairs(balls) do ballCounts[whichTable] = #subtable ballTotalCount = ballTotalCount + ballCounts[whichTable] end local cycleDayIndex, cycleStartingBall = unixDay % ballTotalCount, math.floor(unixDay/ballTotalCount) % ballTotalCount local cycleTodaysBall if ballTotalCount % 7 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*7) % ballTotalCount elseif ballTotalCount % 11 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*11) % ballTotalCount elseif ballTotalCount % 13 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*13) % ballTotalCount else cycleTodaysBall = (cycleStartingBall + cycleDayIndex*(ballTotalCount - 1)) % ballTotalCount end --[[ debug return cycleTodaysBall .. " " .. ballTotalCount .. " " .. os.time() .. " " .. math.floor(os.time()/86400) .. " " .. cycleDayIndex .. " " .. cycleStartingBall ]] for whichTable = 1, #balls do if ballCounts[whichTable] > cycleTodaysBall then return balls[whichTable][cycleTodaysBall + 1] else cycleTodaysBall = cycleTodaysBall - ballCounts[whichTable] end end --]] end return p; 8y1lugwd12r4lzpmjmhmzj5s0ihzrgt 2835238 2835237 2026-09-30T23:40:16Z Helpme2222 3106525 2835238 Scribunto text/plain -- My function for teaching grammar local p = {}; local frame = mw.getCurrentFrame() local grammatical_moods = { "Jelen ido", "Mult ido", "Felszolito mod", "Felteteles mod" } local balls = { grammatical_moods } function p.teamfightSource() local frame = mw.getCurrentFrame() local pageContent = mw.html.create(nil) local i = 1 while (frame.args["team"..i.."_ball1"]) do local teamTable = mw.html.create("table") :addClass("wikitable sortable") :node( mw.html.create( 'tr' ) :node( mw.html.create( 'th' ):node("Participant") ) :node( mw.html.create( 'th' ):node("Contribution") ) :node( mw.html.create( 'th' ):node("Final scaling value") ) :node( mw.html.create( 'th' ):node("Final health") ) ) local j = 1 while (frame.args["team"..i.."_ball"..j]) do teamTable:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j]) ) -- ball also needs to have form and stuff. :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_score"] --[[..]] --[[get contribution type]]) ) -- test: see wordpad comment :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_scaledTo"] --[[..]] --[[get scaling feature]]) ) :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_health"]) ) ) end pageContent:node( mw.html.create("h3"):node("Team "..i) ) :node( teamTable ) end pageContent:node( mw.html.create("h2"):node("Outcome") ) local j = 1 while (frame.args["team"..frame.args.winningTeam.."_ball"..j]) do pageContent:node( --[[sprite of ball, linked to team section]] ) end pageContent:node( "Team" ) end local toggleButton = mw.html.create( 'span' ) :css({ float = "right", ["margin-right"] = "0", ["font-weight"] = "normal" }) :addClass("mw-customtoggle-Infobox") :node("[Click to toggle]") function p.subheading( discrim, b_content, content ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( (discrim) and "mw-collapsible" ) :node( mw.html.create( 'th' ) :attr( "colspan", "2" ) :css( "text-align","left" ) :node((discrim) and b_content or content) :node((discrim) and toggleButton) ) end function p.s_subheading( s_content ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( "mw-collapsible mw-collapsed" ) :node( mw.html.create( 'th' ) :attr( "colspan", "2" ) :css( "text-align","left" ) :node(s_content) :node(toggleButton) ) end function p.row( discrim, name, data ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( (discrim) and "mw-collapsible" ) :node( mw.html.create( 'td' ) :css( "font-weight","bold" ) :node(name) ) :node( mw.html.create( 'td' ) :node(data) ) end function p.s_row( s_name, s_data ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass("mw-collapsible mw-collapsed") :node( mw.html.create( 'td' ) :css( "font-weight","bold" ) :node(s_name) ) :node( mw.html.create( 'td' ) :node(s_data) ) end function p.var(symbol) return frame:expandTemplate{ title = "Template:Var", args = {symbol} } end function p.iseq() return table.concat({ frame.args[1] .. ( (frame.args[1] == "User:Helpme2222/Sandbox/'") and " is equal to User:Helpme2222/Sandbox/'" or " is not equal to User:Helpme2222/Sandbox/'"), frame.args[1] .. ( (frame.args[1] == "User:Helpme2222/Sandbox/&#039;") and " is equal to User:Helpme2222/Sandbox/&#039;" or " is not equal to User:Helpme2222/Sandbox/&#039;"), frame.args[1] .. ( (frame.args[1] == "Helpme2222/Sandbox/'") and " is equal to Helpme2222/Sandbox/'" or " is not equal to Helpme2222/Sandbox/'"), frame.args[1] .. ( (frame.args[1] == "Helpme2222/Sandbox/&#039;") and " is equal to Helpme2222/Sandbox/&#039;" or " is not equal to Helpme2222/Sandbox/&#039;"), }, "<br>") end function p.iseqNamed() return table.concat({ frame.args.arg .. ( (frame.args.arg == "User:Helpme2222/Sandbox/'") and " is equal to User:Helpme2222/Sandbox/'" or " is not equal to User:Helpme2222/Sandbox/'"), frame.args.arg .. ( (frame.args.arg == "User:Helpme2222/Sandbox/&#039;") and " is equal to User:Helpme2222/Sandbox/&#039;" or " is not equal to User:Helpme2222/Sandbox/&#039;"), frame.args.arg .. ( (frame.args.arg == "Helpme2222/Sandbox/'") and " is equal to Helpme2222/Sandbox/'" or " is not equal to Helpme2222/Sandbox/'"), frame.args.arg .. ( (frame.args.arg == "Helpme2222/Sandbox/&#039;") and " is equal to Helpme2222/Sandbox/&#039;" or " is not equal to Helpme2222/Sandbox/&#039;"), }, "<br>") end function p.infoboxWBB() -- Passing expressions of conditional value: https://www.lua.org/pil/3.3.html --[[ https://www.mediawiki.org/wiki/LUAREF#mw.html:node Thankfully, these operations interpret passed nils as no-ops (I'm technically using false though. Somehow that works anyways?)]] local frame = mw.getCurrentFrame() local ballname = frame.args["Title"] or tostring(mw.title.getCurrentTitle()) local Entities = p -- require("Module:Entities") local featureCount = tonumber(frame.args["Feature count"]) or 1 local s_featureCount = tonumber(frame.args["SUPER Feature count"]) or featureCount local matchCount = { total = mw.site.stats.pagesInCategory( ballname .."'s Match History", "pages" ), standard = mw.site.stats.pagesInCategory( ballname .."'s Match History/Weapon Ball Battles/Standard", "pages" ), } local matchWinCount = { standard = mw.site.stats.pagesInCategory( ballname.."'s Match History/Weapon Ball Battles/Standard/Won", "pages" ), } local s_matchCount = { total = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History", "pages" ), standard = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History/Weapon Ball Battles/Standard", "pages" ), } local s_matchWinCount = { standard = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History/Weapon Ball Battles/Standard/Won", "pages" ), } local isSuper = frame.args["SUPER Feature count"] or frame.args["SUPER Type"] or frame.args["SUPER Debuted"] or (s_matchCount.total > 0) or nil -- for some reason, html:node interprets false-valued parameters as no-op signals, while html:addClass does not. The extra "or nil" had to be added since this is used in :addClass calls. -- TITLE local infobox = mw.html.create( 'table' ) :addClass("wikitable") :css({ float = "right"; ["margin-left"] = "10px" }) :node( mw.html.create( 'tr' ) :node( mw.html.create( 'th' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass((isSuper) and "mw-collapsible" or nil) :node("<big>" .. ballname .. "</big>") ) ) :node((isSuper) and mw.html.create( 'tr' ) :node( mw.html.create( 'th' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass("mw-collapsible mw-collapsed") :node("<big>" .. (frame.args["SUPER Title"] or ("Super " .. ballname)) .. "</big>") ) ) -- IMAGES :node((frame.args["Images"]) and (mw.html.create( 'tr' ) :attr("id","mw-customcollapsible-Infobox") :addClass((frame.args["SUPER Images"]) and "mw-collapsible") :node( mw.html.create( 'td' ) :attr("colspan","2") :node(frame.args["Images"]) )) ) :node((frame.args["SUPER Images"]) and (mw.html.create( 'tr' ) :attr("id","mw-customcollapsible-Infobox") :addClass("mw-collapsible mw-collapsed") :node( mw.html.create( 'td' ) :attr("colspan","2") :node(frame.args["SUPER Images"]) )) ) -- SECTION: Identification -- Section Heading :node( p.subheading( (frame.args["SUPER Type"]), "Base Identification", "Basic Info" ) ) :node( (frame.args["SUPER Type"]) and p.s_subheading( "Super Identification" ) ) -- Type :node( p.row( (frame.args["SUPER Type"]), "Type", frame.args["Type"] ) ) :node( (frame.args["SUPER Type"]) and p.s_row( "Type", frame.args["SUPER Type"] ) ) -- Color local color = frame.args["Color"] or Entities.getBallAttribute( "Entities/Weapon Ball Battles/Balls/Data", ballname, "color" ) infobox:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :css("font-weight", "bold") :node("Color") ) :node( mw.html.create( 'td' ) :node( (color ~= "") and frame:expandTemplate{ title = "Color", args = {color} } or "[[Module:Entities/Weapon Ball Battles/Balls/Data|<i>Add color...</i>]]" ) ) ) -- Emoji local emoji = frame.args["Emoji"] or Entities.getBallAttribute( "Entities/Weapon Ball Battles/Balls/Data", ballname, "emoji" ) infobox:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :css("font-weight", "bold") :node("Emoji") ) :node( mw.html.create( 'td' ) :node( (emoji ~= "") and ( emoji .. " <code>" .. p.emojiCodepointInternal(emoji) .. "</code>") or "[[Module:Entities/Weapon Ball Battles/Balls/Data|<i>Add emoji...</i>]]" ) ) ) -- SECTION: Scaling Characteristics --[[ Some data will be collected first. ]] -- (Base) Behavior local features = {} local starts = {} local scalings = {} if (featureCount > 1) then for i = 1, featureCount do table.insert(features, { frame.args["Feature "..i], " (" .. p.var(frame.args["Var "..i]) .. ")" }) table.insert(starts, { p.var( frame.args["Var0 "..i] or (frame.args["Var "..i].."₀") ) .. ": ", frame.args["Starting value "..i] }) table.insert(scalings, { p.var( "Δ"..(frame.args["Var "..i]) ) .. ": ", frame.args["Scaling "..i] }) end else -- These weird ass tables are meant to be compatible with the clone-and-overwrite operation the supers may undergo if the SUPER feature count, unlike the hypothetical base feature count, is greater than 1 features[1] = {frame.args["Feature"],""} starts[1] = {"",frame.args["Starting value"]} scalings[1] = {"",frame.args["Scaling"]} end -- Super Behavior local s_features local s_starts local s_scalings -- for some reason, html:node interprets false-valued parameters as no-op signals, while html:addClass does not. These booleans below are therefore left undefined (nil) as default. local has_s_features; local has_s_starts; local has_s_scalings; if (frame.args["SUPER Feature count"]) then if s_featureCount > 1 then -- Deep copy base characteristics, i.e. use them as default, overwrite what is explicitly specified as new super data s_features = mw.clone(features) s_starts = mw.clone(starts) s_scalings = mw.clone(scalings) -- If # of super features != # of base features, trim or expand the deep-copied tables accordingly. Avoid index errors. if s_featureCount > featureCount then for i = featureCount + 1, s_featureCount do table.insert( s_features, {"",""} ) table.insert( s_starts, {"",""} ) table.insert( s_scalings, {"",""} ) end elseif s_featureCount < featureCount then for i = s_featureCount + 1, featureCount do s_features[i] = nil s_starts[i] = nil s_scalings[i] = nil end end -- Parse super data, set the has_s_... flags if triggered for i = 1,s_featureCount do if frame.args["SUPER Feature "..i] then s_features[i][1] = frame.args["SUPER Feature "..i] if (not has_s_features) then has_s_features = true end end if frame.args["SUPER Starting value "..i] then s_starts[i][2] = frame.args["SUPER Starting value "..i] if (not has_s_starts) then has_s_starts = true end end if frame.args["SUPER Scaling "..i] then s_scalings[i][2] = frame.args["SUPER Scaling "..i] if (not has_s_scalings) then has_s_scalings = true end end if frame.args["SUPER Var "..i] then s_features[i][2] = " (" .. p.var(frame.args["SUPER Var "..i]) .. ")" s_starts[i][1] = p.var( frame.args["SUPER Var0 "..i] or (frame.args["SUPER Var "..i].."₀") ) .. ": " s_scalings[i][1] = p.var( '<span style="font-style:normal">Δ</span>'..(frame.args["SUPER Var "..i]) ) .. ": " if (not has_s_features) then has_s_features = true end if (not has_s_starts) then has_s_starts = true end if (not has_s_scalings) then has_s_scalings = true end end s_features[i] = table.concat(s_features[i]) s_starts[i] = table.concat(s_starts[i]) s_scalings[i] = table.concat(s_scalings[i]) end s_features = table.concat(s_features,"<br>") s_starts = table.concat(s_starts,"<br>") s_scalings = table.concat(s_scalings,"<br>") else -- # of super features = 1? just write directly to the variable if frame.args["SUPER Var"] or frame.args["SUPER Feature"] then has_s_features = true s_features = frame.args["SUPER Feature"] end if frame.args["SUPER Var0"] or frame.args["SUPER Var"] or frame.args["SUPER Starting value"] then has_s_starts = true s_starts = frame.args["SUPER Starting value"] end if frame.args["SUPER Scaling"] then has_s_scalings = true s_scalings = frame.args["SUPER Scaling"] end end end -- finalize base data as strings now that work is otherwise complete if (featureCount > 1) then for i = 1, featureCount do features[i] = table.concat(features[i]) starts[i] = table.concat(starts[i]) scalings[i] = table.concat(scalings[i]) end features = table.concat(features,"<br>") starts = table.concat(starts,"<br>") scalings = table.concat(scalings,"<br>") else features = features[1][1] starts = starts[1][2] scalings = scalings[1][2] end --[[ Begin rendering ]] -- Section Heading infobox:node( p.subheading( (frame.args["SUPER Feature count"]), "Base Scaling Characteristics", "Scaling Characteristics" ) ) :node( (frame.args["SUPER Feature count"]) and p.s_subheading( "Super Scaling Characteristics" ) ) -- Features :node( p.row( (has_s_features), (featureCount > 1) and "Features" or ( (frame.args["Var"]) and ("Feature (" .. p.var(frame.args["Var"]) .. ")") or "Feature" ), features ) ) :node( (has_s_features) and p.s_row( (s_featureCount > 1) and "Features" or ( (frame.args["SUPER Var"]) and ("Feature (" .. p.var(frame.args["SUPER Var"]) .. ")") or "Feature" ), s_features ) ) -- Starting values :node( p.row( (has_s_starts), (featureCount > 1) and "Starting values" or ( (frame.args["Var"]) and ("Starting value (" .. ( p.var(frame.args["Var0"] or (frame.args["Var"].."₀") ) ) .. ")") or "Starting value" ), starts ) ) :node( (has_s_starts) and p.s_row( (s_featureCount > 1) and "Starting values" or ( (frame.args["SUPER Var"]) and ("Starting value (" .. ( p.var(frame.args["SUPER Var0"] or (frame.args["SUPER Var"].."₀") ) ) .. ")") or "Starting value" ), s_starts ) ) -- Scaling :node( p.row( (has_s_scalings), "Scaling", scalings) ) :node( (has_s_scalings) and p.s_row("Scaling", s_scalings) ) -- SECTION: Career --[[ Some data will be collected first. ]] -- (Base) Games played local gamesPlayedText = {} if matchCount.total > 0 then table.insert(gamesPlayedText, matchCount.total .. " (total)") if matchCount.standard > 0 then table.insert(gamesPlayedText, matchCount.standard .. " (standard)") end end -- (Base) Winrate local winrateText = {} if matchCount.total > 0 then if matchCount.standard > 0 then table.insert(winrateText, p.roundedPct(matchWinCount.standard,matchCount.standard) .. "% (standard)" ) end end -- Super Games played local s_gamesPlayedText = {} if s_matchCount.total > 0 then table.insert(s_gamesPlayedText, s_matchCount.total .. " (total)") if s_matchCount.standard > 0 then table.insert(s_gamesPlayedText, s_matchCount.standard .. " (standard)") end end -- Super Winrate local s_winrateText = {} if s_matchCount.total > 0 then if s_matchCount.standard > 0 then table.insert(s_winrateText, p.roundedPct(s_matchWinCount.standard,s_matchCount.standard) .. "% (standard)" ) end end --[[ Begin rendering ]] -- Section Heading infobox:node( p.subheading( (isSuper), "Base Career", "Career ") ) :node( (isSuper) and p.s_subheading( "Super Career") ) -- Debuted :node( p.row( (isSuper), "Debut", frame.args["Debut"] ) ) :node( (isSuper) and p.s_row("Debut", frame.args["SUPER Debut"]) ) -- Games played :node( p.row( (isSuper), "Games played", (#gamesPlayedText > 0) and table.concat(gamesPlayedText, "<br>") or "<i>Not enough data...</i>" ) ) :node( (isSuper) and p.s_row( "Games played", (#s_gamesPlayedText > 0) and table.concat(s_gamesPlayedText, "<br>") or "<i>Not enough data...</i>" ) ) -- Winrate :node( p.row( (isSuper), "Winrate", (#winrateText > 0) and table.concat(winrateText, "<br>") or "<i>Not enough data...</i>" ) ) :node( (isSuper) and p.s_row( "Winrate", (#s_winrateText > 0) and table.concat(s_winrateText, "<br>") or "<i>Not enough data...</i>" ) ) return tostring(infobox) end function p.referenceTest() local element = mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( "mw-collapsible" ) :css( "text-align","left" ) local bigElement = mw.html.create( "div" ) :node( mw.clone(element) :attr( "colspan", "2" ) :node( "shitface") ) :node( mw.clone(element) :attr( "colspan", "2" ) :node( "shitface2") ) return tostring(element) .. "\n" .. tostring(bigElement) .. "\n" end function p.roundedPct(num, den) return (num/den % 0.01 < 0.005) and math.floor(num/den * 100) or math.ceil(num/den * 100) end function p.title() --[[local grammatical_cases = { ablative = 1, inessive = { ANCOVA = "ANCOVA" } } local cases2 = "ba" local cases3 = "ba" -- if grammatical_cases.inessive[frame:getParent():getTitle()] then cases2 = "true" else cases2 = "false" end -- if "ANCOVA" == frame:getParent():getTitle() then cases3 = "true" else cases3 = "false" end local detected = false detected = detected or true]] return mw.title.getCurrentTitle() end function p.ifexist() return tonumber(frame:expandTemplate{ title = "User:Helpme2222/Sandbox", args = {frame.args[1]} }) end function p.performance() for i = 1,5000000 do p.tableMake() end return end function p.performance1() local var = "" for i = 1,100000000 do if var[1] then end end return end function p.performance2() local var = "" for i = 1,100000000 do if type(var) == "table" then end end return end p.counter = 0 function p.tableBake() p.counter = p.counter + 1 return p.counter end function p.tableMake() p.counter = 0 local var = { keyword = {p.tableBake()}, kljuczslovo = {p.tableBake()}, yaoshiwenzi = {p.tableBake()}, llavepalabra = {p.tableBake()}, } return var end function p.expand() return frame:expandTemplate{ title = "User:Helpme2222/Sandbox" } end function p.title3() return mw.title.getCurrentTitle().fullText end function p.getBallAttribute() return p.getBallAttributeInternal(frame.args[1], frame.args[2], frame.args[3], frame.args[4]) end function p.getBallAttributeInternal(arg1_table, arg2_ball, arg3_att, arg4_iteration) local _, ballData = pcall( p.getBallAttributeInternalInternal, arg1_table, arg2_ball, arg3_att, arg4_iteration ) if _ then return mw.text.nowiki(ballData) else return "" end end function p.getBallAttributeInternalInternal(arg1_table, arg2_ball, arg3_att, arg4_iteration) local ballData = mw.loadData(arg1_table)[arg2_ball][arg3_att] if ballData[1] then return ballData[tonumber(arg4_iteration) or p.listCountInternal(ballData)] end return ballData end function p.emojiCodepointInternal( emoji ) emoji = mw.text.trim( emoji ) local i,v = mw.ustring.codepoint( emoji, 1, mw.ustring.len(emoji) ) if v then return "U+" .. string.format("%X", i ) .. " U+" .. string.format("%X", v ) else return "U+" .. string.format("%X", i ) end end function p.emojiCodepoint() local emoji = mw.text.trim( mw.getCurrentFrame().args[1] ) local i,v = mw.ustring.codepoint( emoji, 1, mw.ustring.len(emoji) ) if v then return "U+" .. string.format("%X", i ) .. " U+" .. string.format("%X", v ) else return "U+" .. string.format("%X", i ) end end function p.title2() local grammatical_cases = { ablative = 1, inessive = { ANCOVA = "ANCOVA", ["Module:Sandbox/22"] = "Module:Sandbox/22" } } local concepts = { grammatical_cases, } local PAGENAME = tostring(mw.title.getCurrentTitle()) -- local detected = false local out = {} local debugger = {} for i, group in ipairs(concepts) do if group.inessive[PAGENAME] then table.insert(debugger,"Okay, managed TRUE on "..i..":"..group.ablative) -- detected = detected or true local formattedGroup = {} for memberKey, memberRendervalue in pairs(group.inessive) do table.insert(formattedGroup, "<li>" .. memberRendervalue .. "</li>") end table.insert(out, "<h3>" .. group.ablative .. "</h3><ul>" .. table.concat( formattedGroup ) .. "</ul>" ) table.insert(out, "this sucks ass") return "this sucks ass" else table.insert(debugger,"Managed FALSE on "..i..":"..group.ablative..". Comparator: "..PAGENAME..", ") end end return debugger --[[ if detected then return tostring(detected) .. table.concat(out) end return --]] end function p.sanitizeChar(capture) -- If the set of likely illegal characters to appear in title expands, a rewrite of this as a table is merited if capture == "?" then return "" elseif capture == "#" then return "No. " end end function p.sanitizeTitle() local title = frame.args[1] return mw.ustring.gsub( title, "(?:\\?|\\#)", p.sanitizeChar) end function p.sanitizeTitletest2() return mw.ustring.gsub( "Ki vagy? (🌡️🌾⭐🗡️ VS 🪐 🪨 💣 🧿)", "(?:\\?|\\#)", p.sanitizeChar()) end function p.safetyTest() if string.len(frame.args[1]) < 500 then return frame.args[1] else return "" end end --[[ function array_iter(t) local i = 0 return function () i = i + 1 return t[i] end end --]] function p.listInline() --[[ This function is a godsend! https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#mw.text.listToText --]] local spritedTable = {} for i,entry in ipairs(balls[tonumber(frame.args[1])]) do spritedTable[i] = "{{Sprite|named=1|linked=1|"..entry.."}}" end return mw.text.listToText( spritedTable , ", ", ", and " ) end function p.listNavbox() -- https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#table.concat local spritedTable = {} for i,entry in ipairs(balls[tonumber(frame.args[1])]) do spritedTable[i] = "{{Sprite|named=1|linked=1|"..entry.."}}" end return table.concat( spritedTable , " • ") end function p.listCountInternal(table) local count = 0 for index,value in ipairs( table ) do count = count + 1 end return count end function p.listCount() return table.maxn(balls[tonumber(frame.args[1])]) end -- https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#table.maxn function p.tableTest() return balls[1][1] end function p.todaysBall() --[[ https://www.lua.org/pil/3.6.html The use of explicit indexing here is not strictly semantic; it's just to emphasize the rotation order. ]] local unixDay = math.floor(os.time()/86400) local ballTotalCount = 0 local ballCounts = {} for whichTable,subtable in ipairs(balls) do ballCounts[whichTable] = #subtable ballTotalCount = ballTotalCount + ballCounts[whichTable] end local cycleDayIndex, cycleStartingBall = unixDay % ballTotalCount, math.floor(unixDay/ballTotalCount) % ballTotalCount local cycleTodaysBall if ballTotalCount % 7 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*7) % ballTotalCount elseif ballTotalCount % 11 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*11) % ballTotalCount elseif ballTotalCount % 13 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*13) % ballTotalCount else cycleTodaysBall = (cycleStartingBall + cycleDayIndex*(ballTotalCount - 1)) % ballTotalCount end --[[ debug return cycleTodaysBall .. " " .. ballTotalCount .. " " .. os.time() .. " " .. math.floor(os.time()/86400) .. " " .. cycleDayIndex .. " " .. cycleStartingBall ]] for whichTable = 1, #balls do if ballCounts[whichTable] > cycleTodaysBall then return balls[whichTable][cycleTodaysBall + 1] else cycleTodaysBall = cycleTodaysBall - ballCounts[whichTable] end end --]] end return p; ncpirye6dqkjbqxxghsir7omjnyhx1q 2835239 2835238 2026-09-30T23:43:51Z Helpme2222 3106525 2835239 Scribunto text/plain -- My function for teaching grammar local p = {}; local frame = mw.getCurrentFrame() local grammatical_moods = { "Jelen ido", "Mult ido", "Felszolito mod", "Felteteles mod" } local balls = { grammatical_moods } function p.teamfightSource() local frame = mw.getCurrentFrame() local pageContent = mw.html.create(nil) local i = 1 while (frame.args["team"..i.."_ball1"]) do local teamTable = mw.html.create("table") :addClass("wikitable sortable") :node( mw.html.create( 'tr' ) :node( mw.html.create( 'th' ):node("Participant") ) :node( mw.html.create( 'th' ):node("Contribution") ) :node( mw.html.create( 'th' ):node("Final scaling value") ) :node( mw.html.create( 'th' ):node("Final health") ) ) local j = 1 while (frame.args["team"..i.."_ball"..j]) do teamTable:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j]) ) -- ball also needs to have form and stuff. :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_score"] --[[..]] --[[get contribution type]]) ) -- test: see wordpad comment :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_scaledTo"] --[[..]] --[[get scaling feature]]) ) :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_health"]) ) ) end pageContent:node( mw.html.create("h3"):node("Team "..i) ) :node( teamTable ) end pageContent:node( mw.html.create("h2"):node("Outcome") ) local j = 1 while (frame.args["team"..frame.args.winningTeam.."_ball"..j]) do pageContent:node( --[[sprite of ball, linked to team section]] ) end pageContent:node( "Team" ) end local toggleButton = mw.html.create( 'span' ) :css({ float = "right", ["margin-right"] = "0", ["font-weight"] = "normal" }) :addClass("mw-customtoggle-Infobox") :node("[Click to toggle]") function p.subheading( discrim, b_content, content ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( (discrim) and "mw-collapsible" ) :node( mw.html.create( 'th' ) :attr( "colspan", "2" ) :css( "text-align","left" ) :node((discrim) and b_content or content) :node((discrim) and toggleButton) ) end function p.s_subheading( s_content ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( "mw-collapsible mw-collapsed" ) :node( mw.html.create( 'th' ) :attr( "colspan", "2" ) :css( "text-align","left" ) :node(s_content) :node(toggleButton) ) end function p.row( discrim, name, data ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( (discrim) and "mw-collapsible" ) :node( mw.html.create( 'td' ) :css( "font-weight","bold" ) :node(name) ) :node( mw.html.create( 'td' ) :node(data) ) end function p.s_row( s_name, s_data ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass("mw-collapsible mw-collapsed") :node( mw.html.create( 'td' ) :css( "font-weight","bold" ) :node(s_name) ) :node( mw.html.create( 'td' ) :node(s_data) ) end function p.var(symbol) return frame:expandTemplate{ title = "Template:Var", args = {symbol} } end function p.iseq() return table.concat({ frame.args[1] .. ( (frame.args[1] == "User:Helpme2222/Sandbox/'") and " is equal to User:Helpme2222/Sandbox/'" or " is not equal to User:Helpme2222/Sandbox/'"), frame.args[1] .. ( (frame.args[1] == "User:Helpme2222/Sandbox/&#039;") and " is equal to User:Helpme2222/Sandbox/&#039;" or " is not equal to User:Helpme2222/Sandbox/&#039;"), frame.args[1] .. ( (frame.args[1] == "Helpme2222/Sandbox/'") and " is equal to Helpme2222/Sandbox/'" or " is not equal to Helpme2222/Sandbox/'"), frame.args[1] .. ( (frame.args[1] == "Helpme2222/Sandbox/&#039;") and " is equal to Helpme2222/Sandbox/&#039;" or " is not equal to Helpme2222/Sandbox/&#039;"), }, "<br>") end function p.iseqNamed() return table.concat({ frame.args.arg .. ( (frame.args.arg == "User:Helpme2222/Sandbox/'") and " is equal to User:Helpme2222/Sandbox/'" or " is not equal to User:Helpme2222/Sandbox/'"), frame.args.arg .. ( (frame.args.arg == "User:Helpme2222/Sandbox/&#039;") and " is equal to User:Helpme2222/Sandbox/&#039;" or " is not equal to User:Helpme2222/Sandbox/&#039;"), frame.args.arg .. ( (frame.args.arg == "Helpme2222/Sandbox/'") and " is equal to Helpme2222/Sandbox/'" or " is not equal to Helpme2222/Sandbox/'"), frame.args.arg .. ( (frame.args.arg == "Helpme2222/Sandbox/&#039;") and " is equal to Helpme2222/Sandbox/&#039;" or " is not equal to Helpme2222/Sandbox/&#039;"), }, "<br>") end function p.infoboxWBB() -- Passing expressions of conditional value: https://www.lua.org/pil/3.3.html --[[ https://www.mediawiki.org/wiki/LUAREF#mw.html:node Thankfully, these operations interpret passed nils as no-ops (I'm technically using false though. Somehow that works anyways?)]] local frame = mw.getCurrentFrame() local ballname = frame.args["Title"] or tostring(mw.title.getCurrentTitle()) local Entities = p -- require("Module:Entities") local featureCount = tonumber(frame.args["Feature count"]) or 1 local s_featureCount = tonumber(frame.args["SUPER Feature count"]) or featureCount local matchCount = { total = mw.site.stats.pagesInCategory( ballname .."'s Match History", "pages" ), standard = mw.site.stats.pagesInCategory( ballname .."'s Match History/Weapon Ball Battles/Standard", "pages" ), } local matchWinCount = { standard = mw.site.stats.pagesInCategory( ballname.."'s Match History/Weapon Ball Battles/Standard/Won", "pages" ), } local s_matchCount = { total = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History", "pages" ), standard = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History/Weapon Ball Battles/Standard", "pages" ), } local s_matchWinCount = { standard = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History/Weapon Ball Battles/Standard/Won", "pages" ), } local isSuper = frame.args["SUPER Feature count"] or frame.args["SUPER Type"] or frame.args["SUPER Debuted"] or (s_matchCount.total > 0) or nil -- for some reason, html:node interprets false-valued parameters as no-op signals, while html:addClass does not. The extra "or nil" had to be added since this is used in :addClass calls. -- TITLE local infobox = mw.html.create( 'table' ) :addClass("wikitable") :css({ float = "right"; ["margin-left"] = "10px" }) :node( mw.html.create( 'tr' ) :node( mw.html.create( 'th' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass((isSuper) and "mw-collapsible" or nil) :node("<big>" .. ballname .. "</big>") ) ) :node((isSuper) and mw.html.create( 'tr' ) :node( mw.html.create( 'th' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass("mw-collapsible mw-collapsed") :node("<big>" .. (frame.args["SUPER Title"] or ("Super " .. ballname)) .. "</big>") ) ) -- IMAGES :node((frame.args["Images"]) and (mw.html.create( 'tr' ) :attr("id","mw-customcollapsible-Infobox") :node( mw.html.create( 'td' ) :attr("colspan","2") :node(frame.args["Images"]) )) ) :node((frame.args["SUPER Images"]) and (mw.html.create( 'tr' ) :attr("id","mw-customcollapsible-Infobox") :node( mw.html.create( 'td' ) :attr("colspan","2") :node(frame.args["SUPER Images"]) )) ) -- SECTION: Identification -- Section Heading :node( p.subheading( (frame.args["SUPER Type"]), "Base Identification", "Basic Info" ) ) :node( (frame.args["SUPER Type"]) and p.s_subheading( "Super Identification" ) ) -- Type :node( p.row( (frame.args["SUPER Type"]), "Type", frame.args["Type"] ) ) :node( (frame.args["SUPER Type"]) and p.s_row( "Type", frame.args["SUPER Type"] ) ) -- Color local color = frame.args["Color"] or Entities.getBallAttribute( "Entities/Weapon Ball Battles/Balls/Data", ballname, "color" ) infobox:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :css("font-weight", "bold") :node("Color") ) :node( mw.html.create( 'td' ) :node( (color ~= "") and frame:expandTemplate{ title = "Color", args = {color} } or "[[Module:Entities/Weapon Ball Battles/Balls/Data|<i>Add color...</i>]]" ) ) ) -- Emoji local emoji = frame.args["Emoji"] or Entities.getBallAttribute( "Entities/Weapon Ball Battles/Balls/Data", ballname, "emoji" ) infobox:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :css("font-weight", "bold") :node("Emoji") ) :node( mw.html.create( 'td' ) :node( (emoji ~= "") and ( emoji .. " <code>" .. p.emojiCodepointInternal(emoji) .. "</code>") or "[[Module:Entities/Weapon Ball Battles/Balls/Data|<i>Add emoji...</i>]]" ) ) ) -- SECTION: Scaling Characteristics --[[ Some data will be collected first. ]] -- (Base) Behavior local features = {} local starts = {} local scalings = {} if (featureCount > 1) then for i = 1, featureCount do table.insert(features, { frame.args["Feature "..i], " (" .. p.var(frame.args["Var "..i]) .. ")" }) table.insert(starts, { p.var( frame.args["Var0 "..i] or (frame.args["Var "..i].."₀") ) .. ": ", frame.args["Starting value "..i] }) table.insert(scalings, { p.var( "Δ"..(frame.args["Var "..i]) ) .. ": ", frame.args["Scaling "..i] }) end else -- These weird ass tables are meant to be compatible with the clone-and-overwrite operation the supers may undergo if the SUPER feature count, unlike the hypothetical base feature count, is greater than 1 features[1] = {frame.args["Feature"],""} starts[1] = {"",frame.args["Starting value"]} scalings[1] = {"",frame.args["Scaling"]} end -- Super Behavior local s_features local s_starts local s_scalings -- for some reason, html:node interprets false-valued parameters as no-op signals, while html:addClass does not. These booleans below are therefore left undefined (nil) as default. local has_s_features; local has_s_starts; local has_s_scalings; if (frame.args["SUPER Feature count"]) then if s_featureCount > 1 then -- Deep copy base characteristics, i.e. use them as default, overwrite what is explicitly specified as new super data s_features = mw.clone(features) s_starts = mw.clone(starts) s_scalings = mw.clone(scalings) -- If # of super features != # of base features, trim or expand the deep-copied tables accordingly. Avoid index errors. if s_featureCount > featureCount then for i = featureCount + 1, s_featureCount do table.insert( s_features, {"",""} ) table.insert( s_starts, {"",""} ) table.insert( s_scalings, {"",""} ) end elseif s_featureCount < featureCount then for i = s_featureCount + 1, featureCount do s_features[i] = nil s_starts[i] = nil s_scalings[i] = nil end end -- Parse super data, set the has_s_... flags if triggered for i = 1,s_featureCount do if frame.args["SUPER Feature "..i] then s_features[i][1] = frame.args["SUPER Feature "..i] if (not has_s_features) then has_s_features = true end end if frame.args["SUPER Starting value "..i] then s_starts[i][2] = frame.args["SUPER Starting value "..i] if (not has_s_starts) then has_s_starts = true end end if frame.args["SUPER Scaling "..i] then s_scalings[i][2] = frame.args["SUPER Scaling "..i] if (not has_s_scalings) then has_s_scalings = true end end if frame.args["SUPER Var "..i] then s_features[i][2] = " (" .. p.var(frame.args["SUPER Var "..i]) .. ")" s_starts[i][1] = p.var( frame.args["SUPER Var0 "..i] or (frame.args["SUPER Var "..i].."₀") ) .. ": " s_scalings[i][1] = p.var( '<span style="font-style:normal">Δ</span>'..(frame.args["SUPER Var "..i]) ) .. ": " if (not has_s_features) then has_s_features = true end if (not has_s_starts) then has_s_starts = true end if (not has_s_scalings) then has_s_scalings = true end end s_features[i] = table.concat(s_features[i]) s_starts[i] = table.concat(s_starts[i]) s_scalings[i] = table.concat(s_scalings[i]) end s_features = table.concat(s_features,"<br>") s_starts = table.concat(s_starts,"<br>") s_scalings = table.concat(s_scalings,"<br>") else -- # of super features = 1? just write directly to the variable if frame.args["SUPER Var"] or frame.args["SUPER Feature"] then has_s_features = true s_features = frame.args["SUPER Feature"] end if frame.args["SUPER Var0"] or frame.args["SUPER Var"] or frame.args["SUPER Starting value"] then has_s_starts = true s_starts = frame.args["SUPER Starting value"] end if frame.args["SUPER Scaling"] then has_s_scalings = true s_scalings = frame.args["SUPER Scaling"] end end end -- finalize base data as strings now that work is otherwise complete if (featureCount > 1) then for i = 1, featureCount do features[i] = table.concat(features[i]) starts[i] = table.concat(starts[i]) scalings[i] = table.concat(scalings[i]) end features = table.concat(features,"<br>") starts = table.concat(starts,"<br>") scalings = table.concat(scalings,"<br>") else features = features[1][1] starts = starts[1][2] scalings = scalings[1][2] end --[[ Begin rendering ]] -- Section Heading infobox:node( p.subheading( (frame.args["SUPER Feature count"]), "Base Scaling Characteristics", "Scaling Characteristics" ) ) :node( (frame.args["SUPER Feature count"]) and p.s_subheading( "Super Scaling Characteristics" ) ) -- Features :node( p.row( (has_s_features), (featureCount > 1) and "Features" or ( (frame.args["Var"]) and ("Feature (" .. p.var(frame.args["Var"]) .. ")") or "Feature" ), features ) ) :node( (has_s_features) and p.s_row( (s_featureCount > 1) and "Features" or ( (frame.args["SUPER Var"]) and ("Feature (" .. p.var(frame.args["SUPER Var"]) .. ")") or "Feature" ), s_features ) ) -- Starting values :node( p.row( (has_s_starts), (featureCount > 1) and "Starting values" or ( (frame.args["Var"]) and ("Starting value (" .. ( p.var(frame.args["Var0"] or (frame.args["Var"].."₀") ) ) .. ")") or "Starting value" ), starts ) ) :node( (has_s_starts) and p.s_row( (s_featureCount > 1) and "Starting values" or ( (frame.args["SUPER Var"]) and ("Starting value (" .. ( p.var(frame.args["SUPER Var0"] or (frame.args["SUPER Var"].."₀") ) ) .. ")") or "Starting value" ), s_starts ) ) -- Scaling :node( p.row( (has_s_scalings), "Scaling", scalings) ) :node( (has_s_scalings) and p.s_row("Scaling", s_scalings) ) -- SECTION: Career --[[ Some data will be collected first. ]] -- (Base) Games played local gamesPlayedText = {} if matchCount.total > 0 then table.insert(gamesPlayedText, matchCount.total .. " (total)") if matchCount.standard > 0 then table.insert(gamesPlayedText, matchCount.standard .. " (standard)") end end -- (Base) Winrate local winrateText = {} if matchCount.total > 0 then if matchCount.standard > 0 then table.insert(winrateText, p.roundedPct(matchWinCount.standard,matchCount.standard) .. "% (standard)" ) end end -- Super Games played local s_gamesPlayedText = {} if s_matchCount.total > 0 then table.insert(s_gamesPlayedText, s_matchCount.total .. " (total)") if s_matchCount.standard > 0 then table.insert(s_gamesPlayedText, s_matchCount.standard .. " (standard)") end end -- Super Winrate local s_winrateText = {} if s_matchCount.total > 0 then if s_matchCount.standard > 0 then table.insert(s_winrateText, p.roundedPct(s_matchWinCount.standard,s_matchCount.standard) .. "% (standard)" ) end end --[[ Begin rendering ]] -- Section Heading infobox:node( p.subheading( (isSuper), "Base Career", "Career ") ) :node( (isSuper) and p.s_subheading( "Super Career") ) -- Debuted :node( p.row( (isSuper), "Debut", frame.args["Debut"] ) ) :node( (isSuper) and p.s_row("Debut", frame.args["SUPER Debut"]) ) -- Games played :node( p.row( (isSuper), "Games played", (#gamesPlayedText > 0) and table.concat(gamesPlayedText, "<br>") or "<i>Not enough data...</i>" ) ) :node( (isSuper) and p.s_row( "Games played", (#s_gamesPlayedText > 0) and table.concat(s_gamesPlayedText, "<br>") or "<i>Not enough data...</i>" ) ) -- Winrate :node( p.row( (isSuper), "Winrate", (#winrateText > 0) and table.concat(winrateText, "<br>") or "<i>Not enough data...</i>" ) ) :node( (isSuper) and p.s_row( "Winrate", (#s_winrateText > 0) and table.concat(s_winrateText, "<br>") or "<i>Not enough data...</i>" ) ) return tostring(infobox) end function p.referenceTest() local element = mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( "mw-collapsible" ) :css( "text-align","left" ) local bigElement = mw.html.create( "div" ) :node( mw.clone(element) :attr( "colspan", "2" ) :node( "shitface") ) :node( mw.clone(element) :attr( "colspan", "2" ) :node( "shitface2") ) return tostring(element) .. "\n" .. tostring(bigElement) .. "\n" end function p.roundedPct(num, den) return (num/den % 0.01 < 0.005) and math.floor(num/den * 100) or math.ceil(num/den * 100) end function p.title() --[[local grammatical_cases = { ablative = 1, inessive = { ANCOVA = "ANCOVA" } } local cases2 = "ba" local cases3 = "ba" -- if grammatical_cases.inessive[frame:getParent():getTitle()] then cases2 = "true" else cases2 = "false" end -- if "ANCOVA" == frame:getParent():getTitle() then cases3 = "true" else cases3 = "false" end local detected = false detected = detected or true]] return mw.title.getCurrentTitle() end function p.ifexist() return tonumber(frame:expandTemplate{ title = "User:Helpme2222/Sandbox", args = {frame.args[1]} }) end function p.performance() for i = 1,5000000 do p.tableMake() end return end function p.performance1() local var = "" for i = 1,100000000 do if var[1] then end end return end function p.performance2() local var = "" for i = 1,100000000 do if type(var) == "table" then end end return end p.counter = 0 function p.tableBake() p.counter = p.counter + 1 return p.counter end function p.tableMake() p.counter = 0 local var = { keyword = {p.tableBake()}, kljuczslovo = {p.tableBake()}, yaoshiwenzi = {p.tableBake()}, llavepalabra = {p.tableBake()}, } return var end function p.expand() return frame:expandTemplate{ title = "User:Helpme2222/Sandbox" } end function p.title3() return mw.title.getCurrentTitle().fullText end function p.getBallAttribute() return p.getBallAttributeInternal(frame.args[1], frame.args[2], frame.args[3], frame.args[4]) end function p.getBallAttributeInternal(arg1_table, arg2_ball, arg3_att, arg4_iteration) local _, ballData = pcall( p.getBallAttributeInternalInternal, arg1_table, arg2_ball, arg3_att, arg4_iteration ) if _ then return mw.text.nowiki(ballData) else return "" end end function p.getBallAttributeInternalInternal(arg1_table, arg2_ball, arg3_att, arg4_iteration) local ballData = mw.loadData(arg1_table)[arg2_ball][arg3_att] if ballData[1] then return ballData[tonumber(arg4_iteration) or p.listCountInternal(ballData)] end return ballData end function p.emojiCodepointInternal( emoji ) emoji = mw.text.trim( emoji ) local i,v = mw.ustring.codepoint( emoji, 1, mw.ustring.len(emoji) ) if v then return "U+" .. string.format("%X", i ) .. " U+" .. string.format("%X", v ) else return "U+" .. string.format("%X", i ) end end function p.emojiCodepoint() local emoji = mw.text.trim( mw.getCurrentFrame().args[1] ) local i,v = mw.ustring.codepoint( emoji, 1, mw.ustring.len(emoji) ) if v then return "U+" .. string.format("%X", i ) .. " U+" .. string.format("%X", v ) else return "U+" .. string.format("%X", i ) end end function p.title2() local grammatical_cases = { ablative = 1, inessive = { ANCOVA = "ANCOVA", ["Module:Sandbox/22"] = "Module:Sandbox/22" } } local concepts = { grammatical_cases, } local PAGENAME = tostring(mw.title.getCurrentTitle()) -- local detected = false local out = {} local debugger = {} for i, group in ipairs(concepts) do if group.inessive[PAGENAME] then table.insert(debugger,"Okay, managed TRUE on "..i..":"..group.ablative) -- detected = detected or true local formattedGroup = {} for memberKey, memberRendervalue in pairs(group.inessive) do table.insert(formattedGroup, "<li>" .. memberRendervalue .. "</li>") end table.insert(out, "<h3>" .. group.ablative .. "</h3><ul>" .. table.concat( formattedGroup ) .. "</ul>" ) table.insert(out, "this sucks ass") return "this sucks ass" else table.insert(debugger,"Managed FALSE on "..i..":"..group.ablative..". Comparator: "..PAGENAME..", ") end end return debugger --[[ if detected then return tostring(detected) .. table.concat(out) end return --]] end function p.sanitizeChar(capture) -- If the set of likely illegal characters to appear in title expands, a rewrite of this as a table is merited if capture == "?" then return "" elseif capture == "#" then return "No. " end end function p.sanitizeTitle() local title = frame.args[1] return mw.ustring.gsub( title, "(?:\\?|\\#)", p.sanitizeChar) end function p.sanitizeTitletest2() return mw.ustring.gsub( "Ki vagy? (🌡️🌾⭐🗡️ VS 🪐 🪨 💣 🧿)", "(?:\\?|\\#)", p.sanitizeChar()) end function p.safetyTest() if string.len(frame.args[1]) < 500 then return frame.args[1] else return "" end end --[[ function array_iter(t) local i = 0 return function () i = i + 1 return t[i] end end --]] function p.listInline() --[[ This function is a godsend! https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#mw.text.listToText --]] local spritedTable = {} for i,entry in ipairs(balls[tonumber(frame.args[1])]) do spritedTable[i] = "{{Sprite|named=1|linked=1|"..entry.."}}" end return mw.text.listToText( spritedTable , ", ", ", and " ) end function p.listNavbox() -- https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#table.concat local spritedTable = {} for i,entry in ipairs(balls[tonumber(frame.args[1])]) do spritedTable[i] = "{{Sprite|named=1|linked=1|"..entry.."}}" end return table.concat( spritedTable , " • ") end function p.listCountInternal(table) local count = 0 for index,value in ipairs( table ) do count = count + 1 end return count end function p.listCount() return table.maxn(balls[tonumber(frame.args[1])]) end -- https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#table.maxn function p.tableTest() return balls[1][1] end function p.todaysBall() --[[ https://www.lua.org/pil/3.6.html The use of explicit indexing here is not strictly semantic; it's just to emphasize the rotation order. ]] local unixDay = math.floor(os.time()/86400) local ballTotalCount = 0 local ballCounts = {} for whichTable,subtable in ipairs(balls) do ballCounts[whichTable] = #subtable ballTotalCount = ballTotalCount + ballCounts[whichTable] end local cycleDayIndex, cycleStartingBall = unixDay % ballTotalCount, math.floor(unixDay/ballTotalCount) % ballTotalCount local cycleTodaysBall if ballTotalCount % 7 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*7) % ballTotalCount elseif ballTotalCount % 11 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*11) % ballTotalCount elseif ballTotalCount % 13 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*13) % ballTotalCount else cycleTodaysBall = (cycleStartingBall + cycleDayIndex*(ballTotalCount - 1)) % ballTotalCount end --[[ debug return cycleTodaysBall .. " " .. ballTotalCount .. " " .. os.time() .. " " .. math.floor(os.time()/86400) .. " " .. cycleDayIndex .. " " .. cycleStartingBall ]] for whichTable = 1, #balls do if ballCounts[whichTable] > cycleTodaysBall then return balls[whichTable][cycleTodaysBall + 1] else cycleTodaysBall = cycleTodaysBall - ballCounts[whichTable] end end --]] end return p; 9z6er7st9jirw0vtspf7enwxcnjj8jc 2835240 2835239 2026-09-30T23:44:40Z Helpme2222 3106525 Undid revision [[Special:Diff/2835239|2835239]] by [[Special:Contributions/Helpme2222|Helpme2222]] ([[User talk:Helpme2222|talk]]) 2835240 Scribunto text/plain -- My function for teaching grammar local p = {}; local frame = mw.getCurrentFrame() local grammatical_moods = { "Jelen ido", "Mult ido", "Felszolito mod", "Felteteles mod" } local balls = { grammatical_moods } function p.teamfightSource() local frame = mw.getCurrentFrame() local pageContent = mw.html.create(nil) local i = 1 while (frame.args["team"..i.."_ball1"]) do local teamTable = mw.html.create("table") :addClass("wikitable sortable") :node( mw.html.create( 'tr' ) :node( mw.html.create( 'th' ):node("Participant") ) :node( mw.html.create( 'th' ):node("Contribution") ) :node( mw.html.create( 'th' ):node("Final scaling value") ) :node( mw.html.create( 'th' ):node("Final health") ) ) local j = 1 while (frame.args["team"..i.."_ball"..j]) do teamTable:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j]) ) -- ball also needs to have form and stuff. :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_score"] --[[..]] --[[get contribution type]]) ) -- test: see wordpad comment :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_scaledTo"] --[[..]] --[[get scaling feature]]) ) :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_health"]) ) ) end pageContent:node( mw.html.create("h3"):node("Team "..i) ) :node( teamTable ) end pageContent:node( mw.html.create("h2"):node("Outcome") ) local j = 1 while (frame.args["team"..frame.args.winningTeam.."_ball"..j]) do pageContent:node( --[[sprite of ball, linked to team section]] ) end pageContent:node( "Team" ) end local toggleButton = mw.html.create( 'span' ) :css({ float = "right", ["margin-right"] = "0", ["font-weight"] = "normal" }) :addClass("mw-customtoggle-Infobox") :node("[Click to toggle]") function p.subheading( discrim, b_content, content ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( (discrim) and "mw-collapsible" ) :node( mw.html.create( 'th' ) :attr( "colspan", "2" ) :css( "text-align","left" ) :node((discrim) and b_content or content) :node((discrim) and toggleButton) ) end function p.s_subheading( s_content ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( "mw-collapsible mw-collapsed" ) :node( mw.html.create( 'th' ) :attr( "colspan", "2" ) :css( "text-align","left" ) :node(s_content) :node(toggleButton) ) end function p.row( discrim, name, data ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( (discrim) and "mw-collapsible" ) :node( mw.html.create( 'td' ) :css( "font-weight","bold" ) :node(name) ) :node( mw.html.create( 'td' ) :node(data) ) end function p.s_row( s_name, s_data ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass("mw-collapsible mw-collapsed") :node( mw.html.create( 'td' ) :css( "font-weight","bold" ) :node(s_name) ) :node( mw.html.create( 'td' ) :node(s_data) ) end function p.var(symbol) return frame:expandTemplate{ title = "Template:Var", args = {symbol} } end function p.iseq() return table.concat({ frame.args[1] .. ( (frame.args[1] == "User:Helpme2222/Sandbox/'") and " is equal to User:Helpme2222/Sandbox/'" or " is not equal to User:Helpme2222/Sandbox/'"), frame.args[1] .. ( (frame.args[1] == "User:Helpme2222/Sandbox/&#039;") and " is equal to User:Helpme2222/Sandbox/&#039;" or " is not equal to User:Helpme2222/Sandbox/&#039;"), frame.args[1] .. ( (frame.args[1] == "Helpme2222/Sandbox/'") and " is equal to Helpme2222/Sandbox/'" or " is not equal to Helpme2222/Sandbox/'"), frame.args[1] .. ( (frame.args[1] == "Helpme2222/Sandbox/&#039;") and " is equal to Helpme2222/Sandbox/&#039;" or " is not equal to Helpme2222/Sandbox/&#039;"), }, "<br>") end function p.iseqNamed() return table.concat({ frame.args.arg .. ( (frame.args.arg == "User:Helpme2222/Sandbox/'") and " is equal to User:Helpme2222/Sandbox/'" or " is not equal to User:Helpme2222/Sandbox/'"), frame.args.arg .. ( (frame.args.arg == "User:Helpme2222/Sandbox/&#039;") and " is equal to User:Helpme2222/Sandbox/&#039;" or " is not equal to User:Helpme2222/Sandbox/&#039;"), frame.args.arg .. ( (frame.args.arg == "Helpme2222/Sandbox/'") and " is equal to Helpme2222/Sandbox/'" or " is not equal to Helpme2222/Sandbox/'"), frame.args.arg .. ( (frame.args.arg == "Helpme2222/Sandbox/&#039;") and " is equal to Helpme2222/Sandbox/&#039;" or " is not equal to Helpme2222/Sandbox/&#039;"), }, "<br>") end function p.infoboxWBB() -- Passing expressions of conditional value: https://www.lua.org/pil/3.3.html --[[ https://www.mediawiki.org/wiki/LUAREF#mw.html:node Thankfully, these operations interpret passed nils as no-ops (I'm technically using false though. Somehow that works anyways?)]] local frame = mw.getCurrentFrame() local ballname = frame.args["Title"] or tostring(mw.title.getCurrentTitle()) local Entities = p -- require("Module:Entities") local featureCount = tonumber(frame.args["Feature count"]) or 1 local s_featureCount = tonumber(frame.args["SUPER Feature count"]) or featureCount local matchCount = { total = mw.site.stats.pagesInCategory( ballname .."'s Match History", "pages" ), standard = mw.site.stats.pagesInCategory( ballname .."'s Match History/Weapon Ball Battles/Standard", "pages" ), } local matchWinCount = { standard = mw.site.stats.pagesInCategory( ballname.."'s Match History/Weapon Ball Battles/Standard/Won", "pages" ), } local s_matchCount = { total = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History", "pages" ), standard = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History/Weapon Ball Battles/Standard", "pages" ), } local s_matchWinCount = { standard = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History/Weapon Ball Battles/Standard/Won", "pages" ), } local isSuper = frame.args["SUPER Feature count"] or frame.args["SUPER Type"] or frame.args["SUPER Debuted"] or (s_matchCount.total > 0) or nil -- for some reason, html:node interprets false-valued parameters as no-op signals, while html:addClass does not. The extra "or nil" had to be added since this is used in :addClass calls. -- TITLE local infobox = mw.html.create( 'table' ) :addClass("wikitable") :css({ float = "right"; ["margin-left"] = "10px" }) :node( mw.html.create( 'tr' ) :node( mw.html.create( 'th' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass((isSuper) and "mw-collapsible" or nil) :node("<big>" .. ballname .. "</big>") ) ) :node((isSuper) and mw.html.create( 'tr' ) :node( mw.html.create( 'th' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass("mw-collapsible mw-collapsed") :node("<big>" .. (frame.args["SUPER Title"] or ("Super " .. ballname)) .. "</big>") ) ) -- IMAGES :node((frame.args["Images"]) and (mw.html.create( 'tr' ) :attr("id","mw-customcollapsible-Infobox") :addClass((frame.args["SUPER Images"]) and "mw-collapsible") :node( mw.html.create( 'td' ) :attr("colspan","2") :node(frame.args["Images"]) )) ) :node((frame.args["SUPER Images"]) and (mw.html.create( 'tr' ) :attr("id","mw-customcollapsible-Infobox") :addClass("mw-collapsible mw-collapsed") :node( mw.html.create( 'td' ) :attr("colspan","2") :node(frame.args["SUPER Images"]) )) ) -- SECTION: Identification -- Section Heading :node( p.subheading( (frame.args["SUPER Type"]), "Base Identification", "Basic Info" ) ) :node( (frame.args["SUPER Type"]) and p.s_subheading( "Super Identification" ) ) -- Type :node( p.row( (frame.args["SUPER Type"]), "Type", frame.args["Type"] ) ) :node( (frame.args["SUPER Type"]) and p.s_row( "Type", frame.args["SUPER Type"] ) ) -- Color local color = frame.args["Color"] or Entities.getBallAttribute( "Entities/Weapon Ball Battles/Balls/Data", ballname, "color" ) infobox:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :css("font-weight", "bold") :node("Color") ) :node( mw.html.create( 'td' ) :node( (color ~= "") and frame:expandTemplate{ title = "Color", args = {color} } or "[[Module:Entities/Weapon Ball Battles/Balls/Data|<i>Add color...</i>]]" ) ) ) -- Emoji local emoji = frame.args["Emoji"] or Entities.getBallAttribute( "Entities/Weapon Ball Battles/Balls/Data", ballname, "emoji" ) infobox:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :css("font-weight", "bold") :node("Emoji") ) :node( mw.html.create( 'td' ) :node( (emoji ~= "") and ( emoji .. " <code>" .. p.emojiCodepointInternal(emoji) .. "</code>") or "[[Module:Entities/Weapon Ball Battles/Balls/Data|<i>Add emoji...</i>]]" ) ) ) -- SECTION: Scaling Characteristics --[[ Some data will be collected first. ]] -- (Base) Behavior local features = {} local starts = {} local scalings = {} if (featureCount > 1) then for i = 1, featureCount do table.insert(features, { frame.args["Feature "..i], " (" .. p.var(frame.args["Var "..i]) .. ")" }) table.insert(starts, { p.var( frame.args["Var0 "..i] or (frame.args["Var "..i].."₀") ) .. ": ", frame.args["Starting value "..i] }) table.insert(scalings, { p.var( "Δ"..(frame.args["Var "..i]) ) .. ": ", frame.args["Scaling "..i] }) end else -- These weird ass tables are meant to be compatible with the clone-and-overwrite operation the supers may undergo if the SUPER feature count, unlike the hypothetical base feature count, is greater than 1 features[1] = {frame.args["Feature"],""} starts[1] = {"",frame.args["Starting value"]} scalings[1] = {"",frame.args["Scaling"]} end -- Super Behavior local s_features local s_starts local s_scalings -- for some reason, html:node interprets false-valued parameters as no-op signals, while html:addClass does not. These booleans below are therefore left undefined (nil) as default. local has_s_features; local has_s_starts; local has_s_scalings; if (frame.args["SUPER Feature count"]) then if s_featureCount > 1 then -- Deep copy base characteristics, i.e. use them as default, overwrite what is explicitly specified as new super data s_features = mw.clone(features) s_starts = mw.clone(starts) s_scalings = mw.clone(scalings) -- If # of super features != # of base features, trim or expand the deep-copied tables accordingly. Avoid index errors. if s_featureCount > featureCount then for i = featureCount + 1, s_featureCount do table.insert( s_features, {"",""} ) table.insert( s_starts, {"",""} ) table.insert( s_scalings, {"",""} ) end elseif s_featureCount < featureCount then for i = s_featureCount + 1, featureCount do s_features[i] = nil s_starts[i] = nil s_scalings[i] = nil end end -- Parse super data, set the has_s_... flags if triggered for i = 1,s_featureCount do if frame.args["SUPER Feature "..i] then s_features[i][1] = frame.args["SUPER Feature "..i] if (not has_s_features) then has_s_features = true end end if frame.args["SUPER Starting value "..i] then s_starts[i][2] = frame.args["SUPER Starting value "..i] if (not has_s_starts) then has_s_starts = true end end if frame.args["SUPER Scaling "..i] then s_scalings[i][2] = frame.args["SUPER Scaling "..i] if (not has_s_scalings) then has_s_scalings = true end end if frame.args["SUPER Var "..i] then s_features[i][2] = " (" .. p.var(frame.args["SUPER Var "..i]) .. ")" s_starts[i][1] = p.var( frame.args["SUPER Var0 "..i] or (frame.args["SUPER Var "..i].."₀") ) .. ": " s_scalings[i][1] = p.var( '<span style="font-style:normal">Δ</span>'..(frame.args["SUPER Var "..i]) ) .. ": " if (not has_s_features) then has_s_features = true end if (not has_s_starts) then has_s_starts = true end if (not has_s_scalings) then has_s_scalings = true end end s_features[i] = table.concat(s_features[i]) s_starts[i] = table.concat(s_starts[i]) s_scalings[i] = table.concat(s_scalings[i]) end s_features = table.concat(s_features,"<br>") s_starts = table.concat(s_starts,"<br>") s_scalings = table.concat(s_scalings,"<br>") else -- # of super features = 1? just write directly to the variable if frame.args["SUPER Var"] or frame.args["SUPER Feature"] then has_s_features = true s_features = frame.args["SUPER Feature"] end if frame.args["SUPER Var0"] or frame.args["SUPER Var"] or frame.args["SUPER Starting value"] then has_s_starts = true s_starts = frame.args["SUPER Starting value"] end if frame.args["SUPER Scaling"] then has_s_scalings = true s_scalings = frame.args["SUPER Scaling"] end end end -- finalize base data as strings now that work is otherwise complete if (featureCount > 1) then for i = 1, featureCount do features[i] = table.concat(features[i]) starts[i] = table.concat(starts[i]) scalings[i] = table.concat(scalings[i]) end features = table.concat(features,"<br>") starts = table.concat(starts,"<br>") scalings = table.concat(scalings,"<br>") else features = features[1][1] starts = starts[1][2] scalings = scalings[1][2] end --[[ Begin rendering ]] -- Section Heading infobox:node( p.subheading( (frame.args["SUPER Feature count"]), "Base Scaling Characteristics", "Scaling Characteristics" ) ) :node( (frame.args["SUPER Feature count"]) and p.s_subheading( "Super Scaling Characteristics" ) ) -- Features :node( p.row( (has_s_features), (featureCount > 1) and "Features" or ( (frame.args["Var"]) and ("Feature (" .. p.var(frame.args["Var"]) .. ")") or "Feature" ), features ) ) :node( (has_s_features) and p.s_row( (s_featureCount > 1) and "Features" or ( (frame.args["SUPER Var"]) and ("Feature (" .. p.var(frame.args["SUPER Var"]) .. ")") or "Feature" ), s_features ) ) -- Starting values :node( p.row( (has_s_starts), (featureCount > 1) and "Starting values" or ( (frame.args["Var"]) and ("Starting value (" .. ( p.var(frame.args["Var0"] or (frame.args["Var"].."₀") ) ) .. ")") or "Starting value" ), starts ) ) :node( (has_s_starts) and p.s_row( (s_featureCount > 1) and "Starting values" or ( (frame.args["SUPER Var"]) and ("Starting value (" .. ( p.var(frame.args["SUPER Var0"] or (frame.args["SUPER Var"].."₀") ) ) .. ")") or "Starting value" ), s_starts ) ) -- Scaling :node( p.row( (has_s_scalings), "Scaling", scalings) ) :node( (has_s_scalings) and p.s_row("Scaling", s_scalings) ) -- SECTION: Career --[[ Some data will be collected first. ]] -- (Base) Games played local gamesPlayedText = {} if matchCount.total > 0 then table.insert(gamesPlayedText, matchCount.total .. " (total)") if matchCount.standard > 0 then table.insert(gamesPlayedText, matchCount.standard .. " (standard)") end end -- (Base) Winrate local winrateText = {} if matchCount.total > 0 then if matchCount.standard > 0 then table.insert(winrateText, p.roundedPct(matchWinCount.standard,matchCount.standard) .. "% (standard)" ) end end -- Super Games played local s_gamesPlayedText = {} if s_matchCount.total > 0 then table.insert(s_gamesPlayedText, s_matchCount.total .. " (total)") if s_matchCount.standard > 0 then table.insert(s_gamesPlayedText, s_matchCount.standard .. " (standard)") end end -- Super Winrate local s_winrateText = {} if s_matchCount.total > 0 then if s_matchCount.standard > 0 then table.insert(s_winrateText, p.roundedPct(s_matchWinCount.standard,s_matchCount.standard) .. "% (standard)" ) end end --[[ Begin rendering ]] -- Section Heading infobox:node( p.subheading( (isSuper), "Base Career", "Career ") ) :node( (isSuper) and p.s_subheading( "Super Career") ) -- Debuted :node( p.row( (isSuper), "Debut", frame.args["Debut"] ) ) :node( (isSuper) and p.s_row("Debut", frame.args["SUPER Debut"]) ) -- Games played :node( p.row( (isSuper), "Games played", (#gamesPlayedText > 0) and table.concat(gamesPlayedText, "<br>") or "<i>Not enough data...</i>" ) ) :node( (isSuper) and p.s_row( "Games played", (#s_gamesPlayedText > 0) and table.concat(s_gamesPlayedText, "<br>") or "<i>Not enough data...</i>" ) ) -- Winrate :node( p.row( (isSuper), "Winrate", (#winrateText > 0) and table.concat(winrateText, "<br>") or "<i>Not enough data...</i>" ) ) :node( (isSuper) and p.s_row( "Winrate", (#s_winrateText > 0) and table.concat(s_winrateText, "<br>") or "<i>Not enough data...</i>" ) ) return tostring(infobox) end function p.referenceTest() local element = mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( "mw-collapsible" ) :css( "text-align","left" ) local bigElement = mw.html.create( "div" ) :node( mw.clone(element) :attr( "colspan", "2" ) :node( "shitface") ) :node( mw.clone(element) :attr( "colspan", "2" ) :node( "shitface2") ) return tostring(element) .. "\n" .. tostring(bigElement) .. "\n" end function p.roundedPct(num, den) return (num/den % 0.01 < 0.005) and math.floor(num/den * 100) or math.ceil(num/den * 100) end function p.title() --[[local grammatical_cases = { ablative = 1, inessive = { ANCOVA = "ANCOVA" } } local cases2 = "ba" local cases3 = "ba" -- if grammatical_cases.inessive[frame:getParent():getTitle()] then cases2 = "true" else cases2 = "false" end -- if "ANCOVA" == frame:getParent():getTitle() then cases3 = "true" else cases3 = "false" end local detected = false detected = detected or true]] return mw.title.getCurrentTitle() end function p.ifexist() return tonumber(frame:expandTemplate{ title = "User:Helpme2222/Sandbox", args = {frame.args[1]} }) end function p.performance() for i = 1,5000000 do p.tableMake() end return end function p.performance1() local var = "" for i = 1,100000000 do if var[1] then end end return end function p.performance2() local var = "" for i = 1,100000000 do if type(var) == "table" then end end return end p.counter = 0 function p.tableBake() p.counter = p.counter + 1 return p.counter end function p.tableMake() p.counter = 0 local var = { keyword = {p.tableBake()}, kljuczslovo = {p.tableBake()}, yaoshiwenzi = {p.tableBake()}, llavepalabra = {p.tableBake()}, } return var end function p.expand() return frame:expandTemplate{ title = "User:Helpme2222/Sandbox" } end function p.title3() return mw.title.getCurrentTitle().fullText end function p.getBallAttribute() return p.getBallAttributeInternal(frame.args[1], frame.args[2], frame.args[3], frame.args[4]) end function p.getBallAttributeInternal(arg1_table, arg2_ball, arg3_att, arg4_iteration) local _, ballData = pcall( p.getBallAttributeInternalInternal, arg1_table, arg2_ball, arg3_att, arg4_iteration ) if _ then return mw.text.nowiki(ballData) else return "" end end function p.getBallAttributeInternalInternal(arg1_table, arg2_ball, arg3_att, arg4_iteration) local ballData = mw.loadData(arg1_table)[arg2_ball][arg3_att] if ballData[1] then return ballData[tonumber(arg4_iteration) or p.listCountInternal(ballData)] end return ballData end function p.emojiCodepointInternal( emoji ) emoji = mw.text.trim( emoji ) local i,v = mw.ustring.codepoint( emoji, 1, mw.ustring.len(emoji) ) if v then return "U+" .. string.format("%X", i ) .. " U+" .. string.format("%X", v ) else return "U+" .. string.format("%X", i ) end end function p.emojiCodepoint() local emoji = mw.text.trim( mw.getCurrentFrame().args[1] ) local i,v = mw.ustring.codepoint( emoji, 1, mw.ustring.len(emoji) ) if v then return "U+" .. string.format("%X", i ) .. " U+" .. string.format("%X", v ) else return "U+" .. string.format("%X", i ) end end function p.title2() local grammatical_cases = { ablative = 1, inessive = { ANCOVA = "ANCOVA", ["Module:Sandbox/22"] = "Module:Sandbox/22" } } local concepts = { grammatical_cases, } local PAGENAME = tostring(mw.title.getCurrentTitle()) -- local detected = false local out = {} local debugger = {} for i, group in ipairs(concepts) do if group.inessive[PAGENAME] then table.insert(debugger,"Okay, managed TRUE on "..i..":"..group.ablative) -- detected = detected or true local formattedGroup = {} for memberKey, memberRendervalue in pairs(group.inessive) do table.insert(formattedGroup, "<li>" .. memberRendervalue .. "</li>") end table.insert(out, "<h3>" .. group.ablative .. "</h3><ul>" .. table.concat( formattedGroup ) .. "</ul>" ) table.insert(out, "this sucks ass") return "this sucks ass" else table.insert(debugger,"Managed FALSE on "..i..":"..group.ablative..". Comparator: "..PAGENAME..", ") end end return debugger --[[ if detected then return tostring(detected) .. table.concat(out) end return --]] end function p.sanitizeChar(capture) -- If the set of likely illegal characters to appear in title expands, a rewrite of this as a table is merited if capture == "?" then return "" elseif capture == "#" then return "No. " end end function p.sanitizeTitle() local title = frame.args[1] return mw.ustring.gsub( title, "(?:\\?|\\#)", p.sanitizeChar) end function p.sanitizeTitletest2() return mw.ustring.gsub( "Ki vagy? (🌡️🌾⭐🗡️ VS 🪐 🪨 💣 🧿)", "(?:\\?|\\#)", p.sanitizeChar()) end function p.safetyTest() if string.len(frame.args[1]) < 500 then return frame.args[1] else return "" end end --[[ function array_iter(t) local i = 0 return function () i = i + 1 return t[i] end end --]] function p.listInline() --[[ This function is a godsend! https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#mw.text.listToText --]] local spritedTable = {} for i,entry in ipairs(balls[tonumber(frame.args[1])]) do spritedTable[i] = "{{Sprite|named=1|linked=1|"..entry.."}}" end return mw.text.listToText( spritedTable , ", ", ", and " ) end function p.listNavbox() -- https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#table.concat local spritedTable = {} for i,entry in ipairs(balls[tonumber(frame.args[1])]) do spritedTable[i] = "{{Sprite|named=1|linked=1|"..entry.."}}" end return table.concat( spritedTable , " • ") end function p.listCountInternal(table) local count = 0 for index,value in ipairs( table ) do count = count + 1 end return count end function p.listCount() return table.maxn(balls[tonumber(frame.args[1])]) end -- https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#table.maxn function p.tableTest() return balls[1][1] end function p.todaysBall() --[[ https://www.lua.org/pil/3.6.html The use of explicit indexing here is not strictly semantic; it's just to emphasize the rotation order. ]] local unixDay = math.floor(os.time()/86400) local ballTotalCount = 0 local ballCounts = {} for whichTable,subtable in ipairs(balls) do ballCounts[whichTable] = #subtable ballTotalCount = ballTotalCount + ballCounts[whichTable] end local cycleDayIndex, cycleStartingBall = unixDay % ballTotalCount, math.floor(unixDay/ballTotalCount) % ballTotalCount local cycleTodaysBall if ballTotalCount % 7 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*7) % ballTotalCount elseif ballTotalCount % 11 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*11) % ballTotalCount elseif ballTotalCount % 13 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*13) % ballTotalCount else cycleTodaysBall = (cycleStartingBall + cycleDayIndex*(ballTotalCount - 1)) % ballTotalCount end --[[ debug return cycleTodaysBall .. " " .. ballTotalCount .. " " .. os.time() .. " " .. math.floor(os.time()/86400) .. " " .. cycleDayIndex .. " " .. cycleStartingBall ]] for whichTable = 1, #balls do if ballCounts[whichTable] > cycleTodaysBall then return balls[whichTable][cycleTodaysBall + 1] else cycleTodaysBall = cycleTodaysBall - ballCounts[whichTable] end end --]] end return p; ncpirye6dqkjbqxxghsir7omjnyhx1q 2835241 2835240 2026-09-30T23:48:08Z Helpme2222 3106525 2835241 Scribunto text/plain -- My function for teaching grammar local p = {}; local frame = mw.getCurrentFrame() local grammatical_moods = { "Jelen ido", "Mult ido", "Felszolito mod", "Felteteles mod" } local balls = { grammatical_moods } function p.teamfightSource() local frame = mw.getCurrentFrame() local pageContent = mw.html.create(nil) local i = 1 while (frame.args["team"..i.."_ball1"]) do local teamTable = mw.html.create("table") :addClass("wikitable sortable") :node( mw.html.create( 'tr' ) :node( mw.html.create( 'th' ):node("Participant") ) :node( mw.html.create( 'th' ):node("Contribution") ) :node( mw.html.create( 'th' ):node("Final scaling value") ) :node( mw.html.create( 'th' ):node("Final health") ) ) local j = 1 while (frame.args["team"..i.."_ball"..j]) do teamTable:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j]) ) -- ball also needs to have form and stuff. :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_score"] --[[..]] --[[get contribution type]]) ) -- test: see wordpad comment :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_scaledTo"] --[[..]] --[[get scaling feature]]) ) :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_health"]) ) ) end pageContent:node( mw.html.create("h3"):node("Team "..i) ) :node( teamTable ) end pageContent:node( mw.html.create("h2"):node("Outcome") ) local j = 1 while (frame.args["team"..frame.args.winningTeam.."_ball"..j]) do pageContent:node( --[[sprite of ball, linked to team section]] ) end pageContent:node( "Team" ) end local toggleButton = mw.html.create( 'span' ) :css({ float = "right", ["margin-right"] = "0", ["font-weight"] = "normal" }) :addClass("mw-customtoggle-Infobox") :node("[Click to toggle]") function p.subheading( discrim, b_content, content ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( (discrim) and "mw-collapsible" ) :node( mw.html.create( 'th' ) :attr( "colspan", "2" ) :css( "text-align","left" ) :node((discrim) and b_content or content) :node((discrim) and toggleButton) ) end function p.s_subheading( s_content ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( "mw-collapsible mw-collapsed" ) :node( mw.html.create( 'th' ) :attr( "colspan", "2" ) :css( "text-align","left" ) :node(s_content) :node(toggleButton) ) end function p.row( discrim, name, data ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( (discrim) and "mw-collapsible" ) :node( mw.html.create( 'td' ) :css( "font-weight","bold" ) :node(name) ) :node( mw.html.create( 'td' ) :node(data) ) end function p.s_row( s_name, s_data ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass("mw-collapsible mw-collapsed") :node( mw.html.create( 'td' ) :css( "font-weight","bold" ) :node(s_name) ) :node( mw.html.create( 'td' ) :node(s_data) ) end function p.var(symbol) return frame:expandTemplate{ title = "Template:Var", args = {symbol} } end function p.iseq() return table.concat({ frame.args[1] .. ( (frame.args[1] == "User:Helpme2222/Sandbox/'") and " is equal to User:Helpme2222/Sandbox/'" or " is not equal to User:Helpme2222/Sandbox/'"), frame.args[1] .. ( (frame.args[1] == "User:Helpme2222/Sandbox/&#039;") and " is equal to User:Helpme2222/Sandbox/&#039;" or " is not equal to User:Helpme2222/Sandbox/&#039;"), frame.args[1] .. ( (frame.args[1] == "Helpme2222/Sandbox/'") and " is equal to Helpme2222/Sandbox/'" or " is not equal to Helpme2222/Sandbox/'"), frame.args[1] .. ( (frame.args[1] == "Helpme2222/Sandbox/&#039;") and " is equal to Helpme2222/Sandbox/&#039;" or " is not equal to Helpme2222/Sandbox/&#039;"), }, "<br>") end function p.iseqNamed() return table.concat({ frame.args.arg .. ( (frame.args.arg == "User:Helpme2222/Sandbox/'") and " is equal to User:Helpme2222/Sandbox/'" or " is not equal to User:Helpme2222/Sandbox/'"), frame.args.arg .. ( (frame.args.arg == "User:Helpme2222/Sandbox/&#039;") and " is equal to User:Helpme2222/Sandbox/&#039;" or " is not equal to User:Helpme2222/Sandbox/&#039;"), frame.args.arg .. ( (frame.args.arg == "Helpme2222/Sandbox/'") and " is equal to Helpme2222/Sandbox/'" or " is not equal to Helpme2222/Sandbox/'"), frame.args.arg .. ( (frame.args.arg == "Helpme2222/Sandbox/&#039;") and " is equal to Helpme2222/Sandbox/&#039;" or " is not equal to Helpme2222/Sandbox/&#039;"), }, "<br>") end function p.infoboxWBB() -- Passing expressions of conditional value: https://www.lua.org/pil/3.3.html --[[ https://www.mediawiki.org/wiki/LUAREF#mw.html:node Thankfully, these operations interpret passed nils as no-ops (I'm technically using false though. Somehow that works anyways?)]] local frame = mw.getCurrentFrame() local ballname = frame.args["Title"] or tostring(mw.title.getCurrentTitle()) local Entities = p -- require("Module:Entities") local featureCount = tonumber(frame.args["Feature count"]) or 1 local s_featureCount = tonumber(frame.args["SUPER Feature count"]) or featureCount local matchCount = { total = mw.site.stats.pagesInCategory( ballname .."'s Match History", "pages" ), standard = mw.site.stats.pagesInCategory( ballname .."'s Match History/Weapon Ball Battles/Standard", "pages" ), } local matchWinCount = { standard = mw.site.stats.pagesInCategory( ballname.."'s Match History/Weapon Ball Battles/Standard/Won", "pages" ), } local s_matchCount = { total = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History", "pages" ), standard = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History/Weapon Ball Battles/Standard", "pages" ), } local s_matchWinCount = { standard = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History/Weapon Ball Battles/Standard/Won", "pages" ), } local isSuper = frame.args["SUPER Feature count"] or frame.args["SUPER Type"] or frame.args["SUPER Debuted"] or (s_matchCount.total > 0) or nil -- for some reason, html:node interprets false-valued parameters as no-op signals, while html:addClass does not. The extra "or nil" had to be added since this is used in :addClass calls. -- TITLE local infobox = mw.html.create( 'table' ) :addClass("wikitable") :css({ float = "right"; ["margin-left"] = "10px" }) :node( mw.html.create( 'tr' ) :node( mw.html.create( 'th' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass((isSuper) and "mw-collapsible" or nil) :node("<big>" .. ballname .. "</big>") ) ) :node((isSuper) and mw.html.create( 'tr' ) :node( mw.html.create( 'th' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass("mw-collapsible mw-collapsed") :node("<big>" .. (frame.args["SUPER Title"] or ("Super " .. ballname)) .. "</big>") ) ) -- IMAGES :node((frame.args["Images"]) and (mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :attr("id","mw-customcollapsible-Infobox") :addClass((frame.args["SUPER Images"]) and "mw-collapsible") :attr("colspan","2") :node(frame.args["Images"]) )) ) :node((frame.args["SUPER Images"]) and (mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :attr("id","mw-customcollapsible-Infobox") :addClass("mw-collapsible mw-collapsed") :attr("colspan","2") :node(frame.args["SUPER Images"]) )) ) -- SECTION: Identification -- Section Heading :node( p.subheading( (frame.args["SUPER Type"]), "Base Identification", "Basic Info" ) ) :node( (frame.args["SUPER Type"]) and p.s_subheading( "Super Identification" ) ) -- Type :node( p.row( (frame.args["SUPER Type"]), "Type", frame.args["Type"] ) ) :node( (frame.args["SUPER Type"]) and p.s_row( "Type", frame.args["SUPER Type"] ) ) -- Color local color = frame.args["Color"] or Entities.getBallAttribute( "Entities/Weapon Ball Battles/Balls/Data", ballname, "color" ) infobox:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :css("font-weight", "bold") :node("Color") ) :node( mw.html.create( 'td' ) :node( (color ~= "") and frame:expandTemplate{ title = "Color", args = {color} } or "[[Module:Entities/Weapon Ball Battles/Balls/Data|<i>Add color...</i>]]" ) ) ) -- Emoji local emoji = frame.args["Emoji"] or Entities.getBallAttribute( "Entities/Weapon Ball Battles/Balls/Data", ballname, "emoji" ) infobox:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :css("font-weight", "bold") :node("Emoji") ) :node( mw.html.create( 'td' ) :node( (emoji ~= "") and ( emoji .. " <code>" .. p.emojiCodepointInternal(emoji) .. "</code>") or "[[Module:Entities/Weapon Ball Battles/Balls/Data|<i>Add emoji...</i>]]" ) ) ) -- SECTION: Scaling Characteristics --[[ Some data will be collected first. ]] -- (Base) Behavior local features = {} local starts = {} local scalings = {} if (featureCount > 1) then for i = 1, featureCount do table.insert(features, { frame.args["Feature "..i], " (" .. p.var(frame.args["Var "..i]) .. ")" }) table.insert(starts, { p.var( frame.args["Var0 "..i] or (frame.args["Var "..i].."₀") ) .. ": ", frame.args["Starting value "..i] }) table.insert(scalings, { p.var( "Δ"..(frame.args["Var "..i]) ) .. ": ", frame.args["Scaling "..i] }) end else -- These weird ass tables are meant to be compatible with the clone-and-overwrite operation the supers may undergo if the SUPER feature count, unlike the hypothetical base feature count, is greater than 1 features[1] = {frame.args["Feature"],""} starts[1] = {"",frame.args["Starting value"]} scalings[1] = {"",frame.args["Scaling"]} end -- Super Behavior local s_features local s_starts local s_scalings -- for some reason, html:node interprets false-valued parameters as no-op signals, while html:addClass does not. These booleans below are therefore left undefined (nil) as default. local has_s_features; local has_s_starts; local has_s_scalings; if (frame.args["SUPER Feature count"]) then if s_featureCount > 1 then -- Deep copy base characteristics, i.e. use them as default, overwrite what is explicitly specified as new super data s_features = mw.clone(features) s_starts = mw.clone(starts) s_scalings = mw.clone(scalings) -- If # of super features != # of base features, trim or expand the deep-copied tables accordingly. Avoid index errors. if s_featureCount > featureCount then for i = featureCount + 1, s_featureCount do table.insert( s_features, {"",""} ) table.insert( s_starts, {"",""} ) table.insert( s_scalings, {"",""} ) end elseif s_featureCount < featureCount then for i = s_featureCount + 1, featureCount do s_features[i] = nil s_starts[i] = nil s_scalings[i] = nil end end -- Parse super data, set the has_s_... flags if triggered for i = 1,s_featureCount do if frame.args["SUPER Feature "..i] then s_features[i][1] = frame.args["SUPER Feature "..i] if (not has_s_features) then has_s_features = true end end if frame.args["SUPER Starting value "..i] then s_starts[i][2] = frame.args["SUPER Starting value "..i] if (not has_s_starts) then has_s_starts = true end end if frame.args["SUPER Scaling "..i] then s_scalings[i][2] = frame.args["SUPER Scaling "..i] if (not has_s_scalings) then has_s_scalings = true end end if frame.args["SUPER Var "..i] then s_features[i][2] = " (" .. p.var(frame.args["SUPER Var "..i]) .. ")" s_starts[i][1] = p.var( frame.args["SUPER Var0 "..i] or (frame.args["SUPER Var "..i].."₀") ) .. ": " s_scalings[i][1] = p.var( '<span style="font-style:normal">Δ</span>'..(frame.args["SUPER Var "..i]) ) .. ": " if (not has_s_features) then has_s_features = true end if (not has_s_starts) then has_s_starts = true end if (not has_s_scalings) then has_s_scalings = true end end s_features[i] = table.concat(s_features[i]) s_starts[i] = table.concat(s_starts[i]) s_scalings[i] = table.concat(s_scalings[i]) end s_features = table.concat(s_features,"<br>") s_starts = table.concat(s_starts,"<br>") s_scalings = table.concat(s_scalings,"<br>") else -- # of super features = 1? just write directly to the variable if frame.args["SUPER Var"] or frame.args["SUPER Feature"] then has_s_features = true s_features = frame.args["SUPER Feature"] end if frame.args["SUPER Var0"] or frame.args["SUPER Var"] or frame.args["SUPER Starting value"] then has_s_starts = true s_starts = frame.args["SUPER Starting value"] end if frame.args["SUPER Scaling"] then has_s_scalings = true s_scalings = frame.args["SUPER Scaling"] end end end -- finalize base data as strings now that work is otherwise complete if (featureCount > 1) then for i = 1, featureCount do features[i] = table.concat(features[i]) starts[i] = table.concat(starts[i]) scalings[i] = table.concat(scalings[i]) end features = table.concat(features,"<br>") starts = table.concat(starts,"<br>") scalings = table.concat(scalings,"<br>") else features = features[1][1] starts = starts[1][2] scalings = scalings[1][2] end --[[ Begin rendering ]] -- Section Heading infobox:node( p.subheading( (frame.args["SUPER Feature count"]), "Base Scaling Characteristics", "Scaling Characteristics" ) ) :node( (frame.args["SUPER Feature count"]) and p.s_subheading( "Super Scaling Characteristics" ) ) -- Features :node( p.row( (has_s_features), (featureCount > 1) and "Features" or ( (frame.args["Var"]) and ("Feature (" .. p.var(frame.args["Var"]) .. ")") or "Feature" ), features ) ) :node( (has_s_features) and p.s_row( (s_featureCount > 1) and "Features" or ( (frame.args["SUPER Var"]) and ("Feature (" .. p.var(frame.args["SUPER Var"]) .. ")") or "Feature" ), s_features ) ) -- Starting values :node( p.row( (has_s_starts), (featureCount > 1) and "Starting values" or ( (frame.args["Var"]) and ("Starting value (" .. ( p.var(frame.args["Var0"] or (frame.args["Var"].."₀") ) ) .. ")") or "Starting value" ), starts ) ) :node( (has_s_starts) and p.s_row( (s_featureCount > 1) and "Starting values" or ( (frame.args["SUPER Var"]) and ("Starting value (" .. ( p.var(frame.args["SUPER Var0"] or (frame.args["SUPER Var"].."₀") ) ) .. ")") or "Starting value" ), s_starts ) ) -- Scaling :node( p.row( (has_s_scalings), "Scaling", scalings) ) :node( (has_s_scalings) and p.s_row("Scaling", s_scalings) ) -- SECTION: Career --[[ Some data will be collected first. ]] -- (Base) Games played local gamesPlayedText = {} if matchCount.total > 0 then table.insert(gamesPlayedText, matchCount.total .. " (total)") if matchCount.standard > 0 then table.insert(gamesPlayedText, matchCount.standard .. " (standard)") end end -- (Base) Winrate local winrateText = {} if matchCount.total > 0 then if matchCount.standard > 0 then table.insert(winrateText, p.roundedPct(matchWinCount.standard,matchCount.standard) .. "% (standard)" ) end end -- Super Games played local s_gamesPlayedText = {} if s_matchCount.total > 0 then table.insert(s_gamesPlayedText, s_matchCount.total .. " (total)") if s_matchCount.standard > 0 then table.insert(s_gamesPlayedText, s_matchCount.standard .. " (standard)") end end -- Super Winrate local s_winrateText = {} if s_matchCount.total > 0 then if s_matchCount.standard > 0 then table.insert(s_winrateText, p.roundedPct(s_matchWinCount.standard,s_matchCount.standard) .. "% (standard)" ) end end --[[ Begin rendering ]] -- Section Heading infobox:node( p.subheading( (isSuper), "Base Career", "Career ") ) :node( (isSuper) and p.s_subheading( "Super Career") ) -- Debuted :node( p.row( (isSuper), "Debut", frame.args["Debut"] ) ) :node( (isSuper) and p.s_row("Debut", frame.args["SUPER Debut"]) ) -- Games played :node( p.row( (isSuper), "Games played", (#gamesPlayedText > 0) and table.concat(gamesPlayedText, "<br>") or "<i>Not enough data...</i>" ) ) :node( (isSuper) and p.s_row( "Games played", (#s_gamesPlayedText > 0) and table.concat(s_gamesPlayedText, "<br>") or "<i>Not enough data...</i>" ) ) -- Winrate :node( p.row( (isSuper), "Winrate", (#winrateText > 0) and table.concat(winrateText, "<br>") or "<i>Not enough data...</i>" ) ) :node( (isSuper) and p.s_row( "Winrate", (#s_winrateText > 0) and table.concat(s_winrateText, "<br>") or "<i>Not enough data...</i>" ) ) return tostring(infobox) end function p.referenceTest() local element = mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( "mw-collapsible" ) :css( "text-align","left" ) local bigElement = mw.html.create( "div" ) :node( mw.clone(element) :attr( "colspan", "2" ) :node( "shitface") ) :node( mw.clone(element) :attr( "colspan", "2" ) :node( "shitface2") ) return tostring(element) .. "\n" .. tostring(bigElement) .. "\n" end function p.roundedPct(num, den) return (num/den % 0.01 < 0.005) and math.floor(num/den * 100) or math.ceil(num/den * 100) end function p.title() --[[local grammatical_cases = { ablative = 1, inessive = { ANCOVA = "ANCOVA" } } local cases2 = "ba" local cases3 = "ba" -- if grammatical_cases.inessive[frame:getParent():getTitle()] then cases2 = "true" else cases2 = "false" end -- if "ANCOVA" == frame:getParent():getTitle() then cases3 = "true" else cases3 = "false" end local detected = false detected = detected or true]] return mw.title.getCurrentTitle() end function p.ifexist() return tonumber(frame:expandTemplate{ title = "User:Helpme2222/Sandbox", args = {frame.args[1]} }) end function p.performance() for i = 1,5000000 do p.tableMake() end return end function p.performance1() local var = "" for i = 1,100000000 do if var[1] then end end return end function p.performance2() local var = "" for i = 1,100000000 do if type(var) == "table" then end end return end p.counter = 0 function p.tableBake() p.counter = p.counter + 1 return p.counter end function p.tableMake() p.counter = 0 local var = { keyword = {p.tableBake()}, kljuczslovo = {p.tableBake()}, yaoshiwenzi = {p.tableBake()}, llavepalabra = {p.tableBake()}, } return var end function p.expand() return frame:expandTemplate{ title = "User:Helpme2222/Sandbox" } end function p.title3() return mw.title.getCurrentTitle().fullText end function p.getBallAttribute() return p.getBallAttributeInternal(frame.args[1], frame.args[2], frame.args[3], frame.args[4]) end function p.getBallAttributeInternal(arg1_table, arg2_ball, arg3_att, arg4_iteration) local _, ballData = pcall( p.getBallAttributeInternalInternal, arg1_table, arg2_ball, arg3_att, arg4_iteration ) if _ then return mw.text.nowiki(ballData) else return "" end end function p.getBallAttributeInternalInternal(arg1_table, arg2_ball, arg3_att, arg4_iteration) local ballData = mw.loadData(arg1_table)[arg2_ball][arg3_att] if ballData[1] then return ballData[tonumber(arg4_iteration) or p.listCountInternal(ballData)] end return ballData end function p.emojiCodepointInternal( emoji ) emoji = mw.text.trim( emoji ) local i,v = mw.ustring.codepoint( emoji, 1, mw.ustring.len(emoji) ) if v then return "U+" .. string.format("%X", i ) .. " U+" .. string.format("%X", v ) else return "U+" .. string.format("%X", i ) end end function p.emojiCodepoint() local emoji = mw.text.trim( mw.getCurrentFrame().args[1] ) local i,v = mw.ustring.codepoint( emoji, 1, mw.ustring.len(emoji) ) if v then return "U+" .. string.format("%X", i ) .. " U+" .. string.format("%X", v ) else return "U+" .. string.format("%X", i ) end end function p.title2() local grammatical_cases = { ablative = 1, inessive = { ANCOVA = "ANCOVA", ["Module:Sandbox/22"] = "Module:Sandbox/22" } } local concepts = { grammatical_cases, } local PAGENAME = tostring(mw.title.getCurrentTitle()) -- local detected = false local out = {} local debugger = {} for i, group in ipairs(concepts) do if group.inessive[PAGENAME] then table.insert(debugger,"Okay, managed TRUE on "..i..":"..group.ablative) -- detected = detected or true local formattedGroup = {} for memberKey, memberRendervalue in pairs(group.inessive) do table.insert(formattedGroup, "<li>" .. memberRendervalue .. "</li>") end table.insert(out, "<h3>" .. group.ablative .. "</h3><ul>" .. table.concat( formattedGroup ) .. "</ul>" ) table.insert(out, "this sucks ass") return "this sucks ass" else table.insert(debugger,"Managed FALSE on "..i..":"..group.ablative..". Comparator: "..PAGENAME..", ") end end return debugger --[[ if detected then return tostring(detected) .. table.concat(out) end return --]] end function p.sanitizeChar(capture) -- If the set of likely illegal characters to appear in title expands, a rewrite of this as a table is merited if capture == "?" then return "" elseif capture == "#" then return "No. " end end function p.sanitizeTitle() local title = frame.args[1] return mw.ustring.gsub( title, "(?:\\?|\\#)", p.sanitizeChar) end function p.sanitizeTitletest2() return mw.ustring.gsub( "Ki vagy? (🌡️🌾⭐🗡️ VS 🪐 🪨 💣 🧿)", "(?:\\?|\\#)", p.sanitizeChar()) end function p.safetyTest() if string.len(frame.args[1]) < 500 then return frame.args[1] else return "" end end --[[ function array_iter(t) local i = 0 return function () i = i + 1 return t[i] end end --]] function p.listInline() --[[ This function is a godsend! https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#mw.text.listToText --]] local spritedTable = {} for i,entry in ipairs(balls[tonumber(frame.args[1])]) do spritedTable[i] = "{{Sprite|named=1|linked=1|"..entry.."}}" end return mw.text.listToText( spritedTable , ", ", ", and " ) end function p.listNavbox() -- https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#table.concat local spritedTable = {} for i,entry in ipairs(balls[tonumber(frame.args[1])]) do spritedTable[i] = "{{Sprite|named=1|linked=1|"..entry.."}}" end return table.concat( spritedTable , " • ") end function p.listCountInternal(table) local count = 0 for index,value in ipairs( table ) do count = count + 1 end return count end function p.listCount() return table.maxn(balls[tonumber(frame.args[1])]) end -- https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#table.maxn function p.tableTest() return balls[1][1] end function p.todaysBall() --[[ https://www.lua.org/pil/3.6.html The use of explicit indexing here is not strictly semantic; it's just to emphasize the rotation order. ]] local unixDay = math.floor(os.time()/86400) local ballTotalCount = 0 local ballCounts = {} for whichTable,subtable in ipairs(balls) do ballCounts[whichTable] = #subtable ballTotalCount = ballTotalCount + ballCounts[whichTable] end local cycleDayIndex, cycleStartingBall = unixDay % ballTotalCount, math.floor(unixDay/ballTotalCount) % ballTotalCount local cycleTodaysBall if ballTotalCount % 7 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*7) % ballTotalCount elseif ballTotalCount % 11 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*11) % ballTotalCount elseif ballTotalCount % 13 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*13) % ballTotalCount else cycleTodaysBall = (cycleStartingBall + cycleDayIndex*(ballTotalCount - 1)) % ballTotalCount end --[[ debug return cycleTodaysBall .. " " .. ballTotalCount .. " " .. os.time() .. " " .. math.floor(os.time()/86400) .. " " .. cycleDayIndex .. " " .. cycleStartingBall ]] for whichTable = 1, #balls do if ballCounts[whichTable] > cycleTodaysBall then return balls[whichTable][cycleTodaysBall + 1] else cycleTodaysBall = cycleTodaysBall - ballCounts[whichTable] end end --]] end return p; sv38d9kya55tr7fhj1cujxsij1rpzih 2835242 2835241 2026-09-30T23:49:02Z Helpme2222 3106525 2835242 Scribunto text/plain -- My function for teaching grammar local p = {}; local frame = mw.getCurrentFrame() local grammatical_moods = { "Jelen ido", "Mult ido", "Felszolito mod", "Felteteles mod" } local balls = { grammatical_moods } function p.teamfightSource() local frame = mw.getCurrentFrame() local pageContent = mw.html.create(nil) local i = 1 while (frame.args["team"..i.."_ball1"]) do local teamTable = mw.html.create("table") :addClass("wikitable sortable") :node( mw.html.create( 'tr' ) :node( mw.html.create( 'th' ):node("Participant") ) :node( mw.html.create( 'th' ):node("Contribution") ) :node( mw.html.create( 'th' ):node("Final scaling value") ) :node( mw.html.create( 'th' ):node("Final health") ) ) local j = 1 while (frame.args["team"..i.."_ball"..j]) do teamTable:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j]) ) -- ball also needs to have form and stuff. :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_score"] --[[..]] --[[get contribution type]]) ) -- test: see wordpad comment :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_scaledTo"] --[[..]] --[[get scaling feature]]) ) :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_health"]) ) ) end pageContent:node( mw.html.create("h3"):node("Team "..i) ) :node( teamTable ) end pageContent:node( mw.html.create("h2"):node("Outcome") ) local j = 1 while (frame.args["team"..frame.args.winningTeam.."_ball"..j]) do pageContent:node( --[[sprite of ball, linked to team section]] ) end pageContent:node( "Team" ) end local toggleButton = mw.html.create( 'span' ) :css({ float = "right", ["margin-right"] = "0", ["font-weight"] = "normal" }) :addClass("mw-customtoggle-Infobox") :node("[Click to toggle]") function p.subheading( discrim, b_content, content ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( (discrim) and "mw-collapsible" ) :node( mw.html.create( 'th' ) :attr( "colspan", "2" ) :css( "text-align","left" ) :node((discrim) and b_content or content) :node((discrim) and toggleButton) ) end function p.s_subheading( s_content ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( "mw-collapsible mw-collapsed" ) :node( mw.html.create( 'th' ) :attr( "colspan", "2" ) :css( "text-align","left" ) :node(s_content) :node(toggleButton) ) end function p.row( discrim, name, data ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( (discrim) and "mw-collapsible" ) :node( mw.html.create( 'td' ) :css( "font-weight","bold" ) :node(name) ) :node( mw.html.create( 'td' ) :node(data) ) end function p.s_row( s_name, s_data ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass("mw-collapsible mw-collapsed") :node( mw.html.create( 'td' ) :css( "font-weight","bold" ) :node(s_name) ) :node( mw.html.create( 'td' ) :node(s_data) ) end function p.var(symbol) return frame:expandTemplate{ title = "Template:Var", args = {symbol} } end function p.iseq() return table.concat({ frame.args[1] .. ( (frame.args[1] == "User:Helpme2222/Sandbox/'") and " is equal to User:Helpme2222/Sandbox/'" or " is not equal to User:Helpme2222/Sandbox/'"), frame.args[1] .. ( (frame.args[1] == "User:Helpme2222/Sandbox/&#039;") and " is equal to User:Helpme2222/Sandbox/&#039;" or " is not equal to User:Helpme2222/Sandbox/&#039;"), frame.args[1] .. ( (frame.args[1] == "Helpme2222/Sandbox/'") and " is equal to Helpme2222/Sandbox/'" or " is not equal to Helpme2222/Sandbox/'"), frame.args[1] .. ( (frame.args[1] == "Helpme2222/Sandbox/&#039;") and " is equal to Helpme2222/Sandbox/&#039;" or " is not equal to Helpme2222/Sandbox/&#039;"), }, "<br>") end function p.iseqNamed() return table.concat({ frame.args.arg .. ( (frame.args.arg == "User:Helpme2222/Sandbox/'") and " is equal to User:Helpme2222/Sandbox/'" or " is not equal to User:Helpme2222/Sandbox/'"), frame.args.arg .. ( (frame.args.arg == "User:Helpme2222/Sandbox/&#039;") and " is equal to User:Helpme2222/Sandbox/&#039;" or " is not equal to User:Helpme2222/Sandbox/&#039;"), frame.args.arg .. ( (frame.args.arg == "Helpme2222/Sandbox/'") and " is equal to Helpme2222/Sandbox/'" or " is not equal to Helpme2222/Sandbox/'"), frame.args.arg .. ( (frame.args.arg == "Helpme2222/Sandbox/&#039;") and " is equal to Helpme2222/Sandbox/&#039;" or " is not equal to Helpme2222/Sandbox/&#039;"), }, "<br>") end function p.infoboxWBB() -- Passing expressions of conditional value: https://www.lua.org/pil/3.3.html --[[ https://www.mediawiki.org/wiki/LUAREF#mw.html:node Thankfully, these operations interpret passed nils as no-ops (I'm technically using false though. Somehow that works anyways?)]] local frame = mw.getCurrentFrame() local ballname = frame.args["Title"] or tostring(mw.title.getCurrentTitle()) local Entities = p -- require("Module:Entities") local featureCount = tonumber(frame.args["Feature count"]) or 1 local s_featureCount = tonumber(frame.args["SUPER Feature count"]) or featureCount local matchCount = { total = mw.site.stats.pagesInCategory( ballname .."'s Match History", "pages" ), standard = mw.site.stats.pagesInCategory( ballname .."'s Match History/Weapon Ball Battles/Standard", "pages" ), } local matchWinCount = { standard = mw.site.stats.pagesInCategory( ballname.."'s Match History/Weapon Ball Battles/Standard/Won", "pages" ), } local s_matchCount = { total = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History", "pages" ), standard = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History/Weapon Ball Battles/Standard", "pages" ), } local s_matchWinCount = { standard = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History/Weapon Ball Battles/Standard/Won", "pages" ), } local isSuper = frame.args["SUPER Debuted"] or frame.args["SUPER Feature count"] or frame.args["SUPER Type"] or (s_matchCount.total > 0) or frame.args["SUPER Images"] or nil -- for some reason, html:node interprets false-valued parameters as no-op signals, while html:addClass does not. The extra "or nil" had to be added since this is used in :addClass calls. -- TITLE local infobox = mw.html.create( 'table' ) :addClass("wikitable") :css({ float = "right"; ["margin-left"] = "10px" }) :node( mw.html.create( 'tr' ) :node( mw.html.create( 'th' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass((isSuper) and "mw-collapsible" or nil) :node("<big>" .. ballname .. "</big>") ) ) :node((isSuper) and mw.html.create( 'tr' ) :node( mw.html.create( 'th' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass("mw-collapsible mw-collapsed") :node("<big>" .. (frame.args["SUPER Title"] or ("Super " .. ballname)) .. "</big>") ) ) -- IMAGES :node((frame.args["Images"]) and (mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :attr("id","mw-customcollapsible-Infobox") :addClass((frame.args["SUPER Images"]) and "mw-collapsible") :attr("colspan","2") :node(frame.args["Images"]) )) ) :node((frame.args["SUPER Images"]) and (mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :attr("id","mw-customcollapsible-Infobox") :addClass("mw-collapsible mw-collapsed") :attr("colspan","2") :node(frame.args["SUPER Images"]) )) ) -- SECTION: Identification -- Section Heading :node( p.subheading( (frame.args["SUPER Type"]), "Base Identification", "Basic Info" ) ) :node( (frame.args["SUPER Type"]) and p.s_subheading( "Super Identification" ) ) -- Type :node( p.row( (frame.args["SUPER Type"]), "Type", frame.args["Type"] ) ) :node( (frame.args["SUPER Type"]) and p.s_row( "Type", frame.args["SUPER Type"] ) ) -- Color local color = frame.args["Color"] or Entities.getBallAttribute( "Entities/Weapon Ball Battles/Balls/Data", ballname, "color" ) infobox:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :css("font-weight", "bold") :node("Color") ) :node( mw.html.create( 'td' ) :node( (color ~= "") and frame:expandTemplate{ title = "Color", args = {color} } or "[[Module:Entities/Weapon Ball Battles/Balls/Data|<i>Add color...</i>]]" ) ) ) -- Emoji local emoji = frame.args["Emoji"] or Entities.getBallAttribute( "Entities/Weapon Ball Battles/Balls/Data", ballname, "emoji" ) infobox:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :css("font-weight", "bold") :node("Emoji") ) :node( mw.html.create( 'td' ) :node( (emoji ~= "") and ( emoji .. " <code>" .. p.emojiCodepointInternal(emoji) .. "</code>") or "[[Module:Entities/Weapon Ball Battles/Balls/Data|<i>Add emoji...</i>]]" ) ) ) -- SECTION: Scaling Characteristics --[[ Some data will be collected first. ]] -- (Base) Behavior local features = {} local starts = {} local scalings = {} if (featureCount > 1) then for i = 1, featureCount do table.insert(features, { frame.args["Feature "..i], " (" .. p.var(frame.args["Var "..i]) .. ")" }) table.insert(starts, { p.var( frame.args["Var0 "..i] or (frame.args["Var "..i].."₀") ) .. ": ", frame.args["Starting value "..i] }) table.insert(scalings, { p.var( "Δ"..(frame.args["Var "..i]) ) .. ": ", frame.args["Scaling "..i] }) end else -- These weird ass tables are meant to be compatible with the clone-and-overwrite operation the supers may undergo if the SUPER feature count, unlike the hypothetical base feature count, is greater than 1 features[1] = {frame.args["Feature"],""} starts[1] = {"",frame.args["Starting value"]} scalings[1] = {"",frame.args["Scaling"]} end -- Super Behavior local s_features local s_starts local s_scalings -- for some reason, html:node interprets false-valued parameters as no-op signals, while html:addClass does not. These booleans below are therefore left undefined (nil) as default. local has_s_features; local has_s_starts; local has_s_scalings; if (frame.args["SUPER Feature count"]) then if s_featureCount > 1 then -- Deep copy base characteristics, i.e. use them as default, overwrite what is explicitly specified as new super data s_features = mw.clone(features) s_starts = mw.clone(starts) s_scalings = mw.clone(scalings) -- If # of super features != # of base features, trim or expand the deep-copied tables accordingly. Avoid index errors. if s_featureCount > featureCount then for i = featureCount + 1, s_featureCount do table.insert( s_features, {"",""} ) table.insert( s_starts, {"",""} ) table.insert( s_scalings, {"",""} ) end elseif s_featureCount < featureCount then for i = s_featureCount + 1, featureCount do s_features[i] = nil s_starts[i] = nil s_scalings[i] = nil end end -- Parse super data, set the has_s_... flags if triggered for i = 1,s_featureCount do if frame.args["SUPER Feature "..i] then s_features[i][1] = frame.args["SUPER Feature "..i] if (not has_s_features) then has_s_features = true end end if frame.args["SUPER Starting value "..i] then s_starts[i][2] = frame.args["SUPER Starting value "..i] if (not has_s_starts) then has_s_starts = true end end if frame.args["SUPER Scaling "..i] then s_scalings[i][2] = frame.args["SUPER Scaling "..i] if (not has_s_scalings) then has_s_scalings = true end end if frame.args["SUPER Var "..i] then s_features[i][2] = " (" .. p.var(frame.args["SUPER Var "..i]) .. ")" s_starts[i][1] = p.var( frame.args["SUPER Var0 "..i] or (frame.args["SUPER Var "..i].."₀") ) .. ": " s_scalings[i][1] = p.var( '<span style="font-style:normal">Δ</span>'..(frame.args["SUPER Var "..i]) ) .. ": " if (not has_s_features) then has_s_features = true end if (not has_s_starts) then has_s_starts = true end if (not has_s_scalings) then has_s_scalings = true end end s_features[i] = table.concat(s_features[i]) s_starts[i] = table.concat(s_starts[i]) s_scalings[i] = table.concat(s_scalings[i]) end s_features = table.concat(s_features,"<br>") s_starts = table.concat(s_starts,"<br>") s_scalings = table.concat(s_scalings,"<br>") else -- # of super features = 1? just write directly to the variable if frame.args["SUPER Var"] or frame.args["SUPER Feature"] then has_s_features = true s_features = frame.args["SUPER Feature"] end if frame.args["SUPER Var0"] or frame.args["SUPER Var"] or frame.args["SUPER Starting value"] then has_s_starts = true s_starts = frame.args["SUPER Starting value"] end if frame.args["SUPER Scaling"] then has_s_scalings = true s_scalings = frame.args["SUPER Scaling"] end end end -- finalize base data as strings now that work is otherwise complete if (featureCount > 1) then for i = 1, featureCount do features[i] = table.concat(features[i]) starts[i] = table.concat(starts[i]) scalings[i] = table.concat(scalings[i]) end features = table.concat(features,"<br>") starts = table.concat(starts,"<br>") scalings = table.concat(scalings,"<br>") else features = features[1][1] starts = starts[1][2] scalings = scalings[1][2] end --[[ Begin rendering ]] -- Section Heading infobox:node( p.subheading( (frame.args["SUPER Feature count"]), "Base Scaling Characteristics", "Scaling Characteristics" ) ) :node( (frame.args["SUPER Feature count"]) and p.s_subheading( "Super Scaling Characteristics" ) ) -- Features :node( p.row( (has_s_features), (featureCount > 1) and "Features" or ( (frame.args["Var"]) and ("Feature (" .. p.var(frame.args["Var"]) .. ")") or "Feature" ), features ) ) :node( (has_s_features) and p.s_row( (s_featureCount > 1) and "Features" or ( (frame.args["SUPER Var"]) and ("Feature (" .. p.var(frame.args["SUPER Var"]) .. ")") or "Feature" ), s_features ) ) -- Starting values :node( p.row( (has_s_starts), (featureCount > 1) and "Starting values" or ( (frame.args["Var"]) and ("Starting value (" .. ( p.var(frame.args["Var0"] or (frame.args["Var"].."₀") ) ) .. ")") or "Starting value" ), starts ) ) :node( (has_s_starts) and p.s_row( (s_featureCount > 1) and "Starting values" or ( (frame.args["SUPER Var"]) and ("Starting value (" .. ( p.var(frame.args["SUPER Var0"] or (frame.args["SUPER Var"].."₀") ) ) .. ")") or "Starting value" ), s_starts ) ) -- Scaling :node( p.row( (has_s_scalings), "Scaling", scalings) ) :node( (has_s_scalings) and p.s_row("Scaling", s_scalings) ) -- SECTION: Career --[[ Some data will be collected first. ]] -- (Base) Games played local gamesPlayedText = {} if matchCount.total > 0 then table.insert(gamesPlayedText, matchCount.total .. " (total)") if matchCount.standard > 0 then table.insert(gamesPlayedText, matchCount.standard .. " (standard)") end end -- (Base) Winrate local winrateText = {} if matchCount.total > 0 then if matchCount.standard > 0 then table.insert(winrateText, p.roundedPct(matchWinCount.standard,matchCount.standard) .. "% (standard)" ) end end -- Super Games played local s_gamesPlayedText = {} if s_matchCount.total > 0 then table.insert(s_gamesPlayedText, s_matchCount.total .. " (total)") if s_matchCount.standard > 0 then table.insert(s_gamesPlayedText, s_matchCount.standard .. " (standard)") end end -- Super Winrate local s_winrateText = {} if s_matchCount.total > 0 then if s_matchCount.standard > 0 then table.insert(s_winrateText, p.roundedPct(s_matchWinCount.standard,s_matchCount.standard) .. "% (standard)" ) end end --[[ Begin rendering ]] -- Section Heading infobox:node( p.subheading( (isSuper), "Base Career", "Career ") ) :node( (isSuper) and p.s_subheading( "Super Career") ) -- Debuted :node( p.row( (isSuper), "Debut", frame.args["Debut"] ) ) :node( (isSuper) and p.s_row("Debut", frame.args["SUPER Debut"]) ) -- Games played :node( p.row( (isSuper), "Games played", (#gamesPlayedText > 0) and table.concat(gamesPlayedText, "<br>") or "<i>Not enough data...</i>" ) ) :node( (isSuper) and p.s_row( "Games played", (#s_gamesPlayedText > 0) and table.concat(s_gamesPlayedText, "<br>") or "<i>Not enough data...</i>" ) ) -- Winrate :node( p.row( (isSuper), "Winrate", (#winrateText > 0) and table.concat(winrateText, "<br>") or "<i>Not enough data...</i>" ) ) :node( (isSuper) and p.s_row( "Winrate", (#s_winrateText > 0) and table.concat(s_winrateText, "<br>") or "<i>Not enough data...</i>" ) ) return tostring(infobox) end function p.referenceTest() local element = mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( "mw-collapsible" ) :css( "text-align","left" ) local bigElement = mw.html.create( "div" ) :node( mw.clone(element) :attr( "colspan", "2" ) :node( "shitface") ) :node( mw.clone(element) :attr( "colspan", "2" ) :node( "shitface2") ) return tostring(element) .. "\n" .. tostring(bigElement) .. "\n" end function p.roundedPct(num, den) return (num/den % 0.01 < 0.005) and math.floor(num/den * 100) or math.ceil(num/den * 100) end function p.title() --[[local grammatical_cases = { ablative = 1, inessive = { ANCOVA = "ANCOVA" } } local cases2 = "ba" local cases3 = "ba" -- if grammatical_cases.inessive[frame:getParent():getTitle()] then cases2 = "true" else cases2 = "false" end -- if "ANCOVA" == frame:getParent():getTitle() then cases3 = "true" else cases3 = "false" end local detected = false detected = detected or true]] return mw.title.getCurrentTitle() end function p.ifexist() return tonumber(frame:expandTemplate{ title = "User:Helpme2222/Sandbox", args = {frame.args[1]} }) end function p.performance() for i = 1,5000000 do p.tableMake() end return end function p.performance1() local var = "" for i = 1,100000000 do if var[1] then end end return end function p.performance2() local var = "" for i = 1,100000000 do if type(var) == "table" then end end return end p.counter = 0 function p.tableBake() p.counter = p.counter + 1 return p.counter end function p.tableMake() p.counter = 0 local var = { keyword = {p.tableBake()}, kljuczslovo = {p.tableBake()}, yaoshiwenzi = {p.tableBake()}, llavepalabra = {p.tableBake()}, } return var end function p.expand() return frame:expandTemplate{ title = "User:Helpme2222/Sandbox" } end function p.title3() return mw.title.getCurrentTitle().fullText end function p.getBallAttribute() return p.getBallAttributeInternal(frame.args[1], frame.args[2], frame.args[3], frame.args[4]) end function p.getBallAttributeInternal(arg1_table, arg2_ball, arg3_att, arg4_iteration) local _, ballData = pcall( p.getBallAttributeInternalInternal, arg1_table, arg2_ball, arg3_att, arg4_iteration ) if _ then return mw.text.nowiki(ballData) else return "" end end function p.getBallAttributeInternalInternal(arg1_table, arg2_ball, arg3_att, arg4_iteration) local ballData = mw.loadData(arg1_table)[arg2_ball][arg3_att] if ballData[1] then return ballData[tonumber(arg4_iteration) or p.listCountInternal(ballData)] end return ballData end function p.emojiCodepointInternal( emoji ) emoji = mw.text.trim( emoji ) local i,v = mw.ustring.codepoint( emoji, 1, mw.ustring.len(emoji) ) if v then return "U+" .. string.format("%X", i ) .. " U+" .. string.format("%X", v ) else return "U+" .. string.format("%X", i ) end end function p.emojiCodepoint() local emoji = mw.text.trim( mw.getCurrentFrame().args[1] ) local i,v = mw.ustring.codepoint( emoji, 1, mw.ustring.len(emoji) ) if v then return "U+" .. string.format("%X", i ) .. " U+" .. string.format("%X", v ) else return "U+" .. string.format("%X", i ) end end function p.title2() local grammatical_cases = { ablative = 1, inessive = { ANCOVA = "ANCOVA", ["Module:Sandbox/22"] = "Module:Sandbox/22" } } local concepts = { grammatical_cases, } local PAGENAME = tostring(mw.title.getCurrentTitle()) -- local detected = false local out = {} local debugger = {} for i, group in ipairs(concepts) do if group.inessive[PAGENAME] then table.insert(debugger,"Okay, managed TRUE on "..i..":"..group.ablative) -- detected = detected or true local formattedGroup = {} for memberKey, memberRendervalue in pairs(group.inessive) do table.insert(formattedGroup, "<li>" .. memberRendervalue .. "</li>") end table.insert(out, "<h3>" .. group.ablative .. "</h3><ul>" .. table.concat( formattedGroup ) .. "</ul>" ) table.insert(out, "this sucks ass") return "this sucks ass" else table.insert(debugger,"Managed FALSE on "..i..":"..group.ablative..". Comparator: "..PAGENAME..", ") end end return debugger --[[ if detected then return tostring(detected) .. table.concat(out) end return --]] end function p.sanitizeChar(capture) -- If the set of likely illegal characters to appear in title expands, a rewrite of this as a table is merited if capture == "?" then return "" elseif capture == "#" then return "No. " end end function p.sanitizeTitle() local title = frame.args[1] return mw.ustring.gsub( title, "(?:\\?|\\#)", p.sanitizeChar) end function p.sanitizeTitletest2() return mw.ustring.gsub( "Ki vagy? (🌡️🌾⭐🗡️ VS 🪐 🪨 💣 🧿)", "(?:\\?|\\#)", p.sanitizeChar()) end function p.safetyTest() if string.len(frame.args[1]) < 500 then return frame.args[1] else return "" end end --[[ function array_iter(t) local i = 0 return function () i = i + 1 return t[i] end end --]] function p.listInline() --[[ This function is a godsend! https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#mw.text.listToText --]] local spritedTable = {} for i,entry in ipairs(balls[tonumber(frame.args[1])]) do spritedTable[i] = "{{Sprite|named=1|linked=1|"..entry.."}}" end return mw.text.listToText( spritedTable , ", ", ", and " ) end function p.listNavbox() -- https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#table.concat local spritedTable = {} for i,entry in ipairs(balls[tonumber(frame.args[1])]) do spritedTable[i] = "{{Sprite|named=1|linked=1|"..entry.."}}" end return table.concat( spritedTable , " • ") end function p.listCountInternal(table) local count = 0 for index,value in ipairs( table ) do count = count + 1 end return count end function p.listCount() return table.maxn(balls[tonumber(frame.args[1])]) end -- https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#table.maxn function p.tableTest() return balls[1][1] end function p.todaysBall() --[[ https://www.lua.org/pil/3.6.html The use of explicit indexing here is not strictly semantic; it's just to emphasize the rotation order. ]] local unixDay = math.floor(os.time()/86400) local ballTotalCount = 0 local ballCounts = {} for whichTable,subtable in ipairs(balls) do ballCounts[whichTable] = #subtable ballTotalCount = ballTotalCount + ballCounts[whichTable] end local cycleDayIndex, cycleStartingBall = unixDay % ballTotalCount, math.floor(unixDay/ballTotalCount) % ballTotalCount local cycleTodaysBall if ballTotalCount % 7 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*7) % ballTotalCount elseif ballTotalCount % 11 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*11) % ballTotalCount elseif ballTotalCount % 13 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*13) % ballTotalCount else cycleTodaysBall = (cycleStartingBall + cycleDayIndex*(ballTotalCount - 1)) % ballTotalCount end --[[ debug return cycleTodaysBall .. " " .. ballTotalCount .. " " .. os.time() .. " " .. math.floor(os.time()/86400) .. " " .. cycleDayIndex .. " " .. cycleStartingBall ]] for whichTable = 1, #balls do if ballCounts[whichTable] > cycleTodaysBall then return balls[whichTable][cycleTodaysBall + 1] else cycleTodaysBall = cycleTodaysBall - ballCounts[whichTable] end end --]] end return p; e3kakopz0dnf8aznhzcw0e95gy082x6 2835243 2835242 2026-09-30T23:51:37Z Helpme2222 3106525 2835243 Scribunto text/plain -- My function for teaching grammar local p = {}; local frame = mw.getCurrentFrame() local grammatical_moods = { "Jelen ido", "Mult ido", "Felszolito mod", "Felteteles mod" } local balls = { grammatical_moods } function p.teamfightSource() local frame = mw.getCurrentFrame() local pageContent = mw.html.create(nil) local i = 1 while (frame.args["team"..i.."_ball1"]) do local teamTable = mw.html.create("table") :addClass("wikitable sortable") :node( mw.html.create( 'tr' ) :node( mw.html.create( 'th' ):node("Participant") ) :node( mw.html.create( 'th' ):node("Contribution") ) :node( mw.html.create( 'th' ):node("Final scaling value") ) :node( mw.html.create( 'th' ):node("Final health") ) ) local j = 1 while (frame.args["team"..i.."_ball"..j]) do teamTable:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j]) ) -- ball also needs to have form and stuff. :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_score"] --[[..]] --[[get contribution type]]) ) -- test: see wordpad comment :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_scaledTo"] --[[..]] --[[get scaling feature]]) ) :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_health"]) ) ) end pageContent:node( mw.html.create("h3"):node("Team "..i) ) :node( teamTable ) end pageContent:node( mw.html.create("h2"):node("Outcome") ) local j = 1 while (frame.args["team"..frame.args.winningTeam.."_ball"..j]) do pageContent:node( --[[sprite of ball, linked to team section]] ) end pageContent:node( "Team" ) end local toggleButton = mw.html.create( 'span' ) :css({ float = "right", ["margin-right"] = "0", ["font-weight"] = "normal" }) :addClass("mw-customtoggle-Infobox") :node("[Click to toggle]") function p.subheading( discrim, b_content, content ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( (discrim) and "mw-collapsible" ) :node( mw.html.create( 'th' ) :attr( "colspan", "2" ) :css( "text-align","left" ) :node((discrim) and b_content or content) :node((discrim) and toggleButton) ) end function p.s_subheading( s_content ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( "mw-collapsible mw-collapsed" ) :node( mw.html.create( 'th' ) :attr( "colspan", "2" ) :css( "text-align","left" ) :node(s_content) :node(toggleButton) ) end function p.row( discrim, name, data ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( (discrim) and "mw-collapsible" ) :node( mw.html.create( 'td' ) :css( "font-weight","bold" ) :node(name) ) :node( mw.html.create( 'td' ) :node(data) ) end function p.s_row( s_name, s_data ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass("mw-collapsible mw-collapsed") :node( mw.html.create( 'td' ) :css( "font-weight","bold" ) :node(s_name) ) :node( mw.html.create( 'td' ) :node(s_data) ) end function p.var(symbol) return frame:expandTemplate{ title = "Template:Var", args = {symbol} } end function p.iseq() return table.concat({ frame.args[1] .. ( (frame.args[1] == "User:Helpme2222/Sandbox/'") and " is equal to User:Helpme2222/Sandbox/'" or " is not equal to User:Helpme2222/Sandbox/'"), frame.args[1] .. ( (frame.args[1] == "User:Helpme2222/Sandbox/&#039;") and " is equal to User:Helpme2222/Sandbox/&#039;" or " is not equal to User:Helpme2222/Sandbox/&#039;"), frame.args[1] .. ( (frame.args[1] == "Helpme2222/Sandbox/'") and " is equal to Helpme2222/Sandbox/'" or " is not equal to Helpme2222/Sandbox/'"), frame.args[1] .. ( (frame.args[1] == "Helpme2222/Sandbox/&#039;") and " is equal to Helpme2222/Sandbox/&#039;" or " is not equal to Helpme2222/Sandbox/&#039;"), }, "<br>") end function p.iseqNamed() return table.concat({ frame.args.arg .. ( (frame.args.arg == "User:Helpme2222/Sandbox/'") and " is equal to User:Helpme2222/Sandbox/'" or " is not equal to User:Helpme2222/Sandbox/'"), frame.args.arg .. ( (frame.args.arg == "User:Helpme2222/Sandbox/&#039;") and " is equal to User:Helpme2222/Sandbox/&#039;" or " is not equal to User:Helpme2222/Sandbox/&#039;"), frame.args.arg .. ( (frame.args.arg == "Helpme2222/Sandbox/'") and " is equal to Helpme2222/Sandbox/'" or " is not equal to Helpme2222/Sandbox/'"), frame.args.arg .. ( (frame.args.arg == "Helpme2222/Sandbox/&#039;") and " is equal to Helpme2222/Sandbox/&#039;" or " is not equal to Helpme2222/Sandbox/&#039;"), }, "<br>") end function p.infoboxWBB() -- Passing expressions of conditional value: https://www.lua.org/pil/3.3.html --[[ https://www.mediawiki.org/wiki/LUAREF#mw.html:node Thankfully, these operations interpret passed nils as no-ops (I'm technically using false though. Somehow that works anyways?)]] local frame = mw.getCurrentFrame() local ballname = frame.args["Title"] or tostring(mw.title.getCurrentTitle()) local Entities = p -- require("Module:Entities") local featureCount = tonumber(frame.args["Feature count"]) or 1 local s_featureCount = tonumber(frame.args["SUPER Feature count"]) or featureCount local matchCount = { total = mw.site.stats.pagesInCategory( ballname .."'s Match History", "pages" ), standard = mw.site.stats.pagesInCategory( ballname .."'s Match History/Weapon Ball Battles/Standard", "pages" ), } local matchWinCount = { standard = mw.site.stats.pagesInCategory( ballname.."'s Match History/Weapon Ball Battles/Standard/Won", "pages" ), } local s_matchCount = { total = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History", "pages" ), standard = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History/Weapon Ball Battles/Standard", "pages" ), } local s_matchWinCount = { standard = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History/Weapon Ball Battles/Standard/Won", "pages" ), } local isSuper = frame.args["SUPER Debuted"] or frame.args["SUPER Feature count"] or frame.args["SUPER Type"] or (s_matchCount.total > 0) or frame.args["SUPER Images"] or nil -- for some reason, html:node interprets false-valued parameters as no-op signals, while html:addClass does not. The extra "or nil" had to be added since this is used in :addClass calls. -- TITLE local infobox = mw.html.create( 'table' ) :addClass("wikitable") :css({ float = "right"; ["margin-left"] = "10px" }) :node( mw.html.create( 'tr' ) :node( mw.html.create( 'th' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass((isSuper) and "mw-collapsible" or nil) :node("<big>" .. ballname .. "</big>") ) ) :node((isSuper) and mw.html.create( 'tr' ) :node( mw.html.create( 'th' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass("mw-collapsible mw-collapsed") :node("<big>" .. (frame.args["SUPER Title"] or ("Super " .. ballname)) .. "</big>") ) ) -- IMAGES :node((frame.args["Images"]) and (mw.html.create( 'tr' ) :attr("id","mw-customcollapsible-Infobox") :addClass((frame.args["SUPER Images"]) and "mw-collapsible") :node( mw.html.create( 'td' ) :attr("colspan","2") :node(frame.args["Images"]) )) ) :node((frame.args["SUPER Images"]) and (mw.html.create( 'tr' ) :attr("id","mw-customcollapsible-Infobox") :addClass("mw-collapsible mw-collapsed") :node( mw.html.create( 'td' ) :attr("colspan","2") :node(frame.args["SUPER Images"]) )) ) -- SECTION: Identification -- Section Heading :node( p.subheading( (frame.args["SUPER Type"]), "Base Identification", "Basic Info" ) ) :node( (frame.args["SUPER Type"]) and p.s_subheading( "Super Identification" ) ) -- Type :node( p.row( (frame.args["SUPER Type"]), "Type", frame.args["Type"] ) ) :node( (frame.args["SUPER Type"]) and p.s_row( "Type", frame.args["SUPER Type"] ) ) -- Color local color = frame.args["Color"] or Entities.getBallAttribute( "Entities/Weapon Ball Battles/Balls/Data", ballname, "color" ) infobox:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :css("font-weight", "bold") :node("Color") ) :node( mw.html.create( 'td' ) :node( (color ~= "") and frame:expandTemplate{ title = "Color", args = {color} } or "[[Module:Entities/Weapon Ball Battles/Balls/Data|<i>Add color...</i>]]" ) ) ) -- Emoji local emoji = frame.args["Emoji"] or Entities.getBallAttribute( "Entities/Weapon Ball Battles/Balls/Data", ballname, "emoji" ) infobox:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :css("font-weight", "bold") :node("Emoji") ) :node( mw.html.create( 'td' ) :node( (emoji ~= "") and ( emoji .. " <code>" .. p.emojiCodepointInternal(emoji) .. "</code>") or "[[Module:Entities/Weapon Ball Battles/Balls/Data|<i>Add emoji...</i>]]" ) ) ) -- SECTION: Scaling Characteristics --[[ Some data will be collected first. ]] -- (Base) Behavior local features = {} local starts = {} local scalings = {} if (featureCount > 1) then for i = 1, featureCount do table.insert(features, { frame.args["Feature "..i], " (" .. p.var(frame.args["Var "..i]) .. ")" }) table.insert(starts, { p.var( frame.args["Var0 "..i] or (frame.args["Var "..i].."₀") ) .. ": ", frame.args["Starting value "..i] }) table.insert(scalings, { p.var( "Δ"..(frame.args["Var "..i]) ) .. ": ", frame.args["Scaling "..i] }) end else -- These weird ass tables are meant to be compatible with the clone-and-overwrite operation the supers may undergo if the SUPER feature count, unlike the hypothetical base feature count, is greater than 1 features[1] = {frame.args["Feature"],""} starts[1] = {"",frame.args["Starting value"]} scalings[1] = {"",frame.args["Scaling"]} end -- Super Behavior local s_features local s_starts local s_scalings -- for some reason, html:node interprets false-valued parameters as no-op signals, while html:addClass does not. These booleans below are therefore left undefined (nil) as default. local has_s_features; local has_s_starts; local has_s_scalings; if (frame.args["SUPER Feature count"]) then if s_featureCount > 1 then -- Deep copy base characteristics, i.e. use them as default, overwrite what is explicitly specified as new super data s_features = mw.clone(features) s_starts = mw.clone(starts) s_scalings = mw.clone(scalings) -- If # of super features != # of base features, trim or expand the deep-copied tables accordingly. Avoid index errors. if s_featureCount > featureCount then for i = featureCount + 1, s_featureCount do table.insert( s_features, {"",""} ) table.insert( s_starts, {"",""} ) table.insert( s_scalings, {"",""} ) end elseif s_featureCount < featureCount then for i = s_featureCount + 1, featureCount do s_features[i] = nil s_starts[i] = nil s_scalings[i] = nil end end -- Parse super data, set the has_s_... flags if triggered for i = 1,s_featureCount do if frame.args["SUPER Feature "..i] then s_features[i][1] = frame.args["SUPER Feature "..i] if (not has_s_features) then has_s_features = true end end if frame.args["SUPER Starting value "..i] then s_starts[i][2] = frame.args["SUPER Starting value "..i] if (not has_s_starts) then has_s_starts = true end end if frame.args["SUPER Scaling "..i] then s_scalings[i][2] = frame.args["SUPER Scaling "..i] if (not has_s_scalings) then has_s_scalings = true end end if frame.args["SUPER Var "..i] then s_features[i][2] = " (" .. p.var(frame.args["SUPER Var "..i]) .. ")" s_starts[i][1] = p.var( frame.args["SUPER Var0 "..i] or (frame.args["SUPER Var "..i].."₀") ) .. ": " s_scalings[i][1] = p.var( '<span style="font-style:normal">Δ</span>'..(frame.args["SUPER Var "..i]) ) .. ": " if (not has_s_features) then has_s_features = true end if (not has_s_starts) then has_s_starts = true end if (not has_s_scalings) then has_s_scalings = true end end s_features[i] = table.concat(s_features[i]) s_starts[i] = table.concat(s_starts[i]) s_scalings[i] = table.concat(s_scalings[i]) end s_features = table.concat(s_features,"<br>") s_starts = table.concat(s_starts,"<br>") s_scalings = table.concat(s_scalings,"<br>") else -- # of super features = 1? just write directly to the variable if frame.args["SUPER Var"] or frame.args["SUPER Feature"] then has_s_features = true s_features = frame.args["SUPER Feature"] end if frame.args["SUPER Var0"] or frame.args["SUPER Var"] or frame.args["SUPER Starting value"] then has_s_starts = true s_starts = frame.args["SUPER Starting value"] end if frame.args["SUPER Scaling"] then has_s_scalings = true s_scalings = frame.args["SUPER Scaling"] end end end -- finalize base data as strings now that work is otherwise complete if (featureCount > 1) then for i = 1, featureCount do features[i] = table.concat(features[i]) starts[i] = table.concat(starts[i]) scalings[i] = table.concat(scalings[i]) end features = table.concat(features,"<br>") starts = table.concat(starts,"<br>") scalings = table.concat(scalings,"<br>") else features = features[1][1] starts = starts[1][2] scalings = scalings[1][2] end --[[ Begin rendering ]] -- Section Heading infobox:node( p.subheading( (frame.args["SUPER Feature count"]), "Base Scaling Characteristics", "Scaling Characteristics" ) ) :node( (frame.args["SUPER Feature count"]) and p.s_subheading( "Super Scaling Characteristics" ) ) -- Features :node( p.row( (has_s_features), (featureCount > 1) and "Features" or ( (frame.args["Var"]) and ("Feature (" .. p.var(frame.args["Var"]) .. ")") or "Feature" ), features ) ) :node( (has_s_features) and p.s_row( (s_featureCount > 1) and "Features" or ( (frame.args["SUPER Var"]) and ("Feature (" .. p.var(frame.args["SUPER Var"]) .. ")") or "Feature" ), s_features ) ) -- Starting values :node( p.row( (has_s_starts), (featureCount > 1) and "Starting values" or ( (frame.args["Var"]) and ("Starting value (" .. ( p.var(frame.args["Var0"] or (frame.args["Var"].."₀") ) ) .. ")") or "Starting value" ), starts ) ) :node( (has_s_starts) and p.s_row( (s_featureCount > 1) and "Starting values" or ( (frame.args["SUPER Var"]) and ("Starting value (" .. ( p.var(frame.args["SUPER Var0"] or (frame.args["SUPER Var"].."₀") ) ) .. ")") or "Starting value" ), s_starts ) ) -- Scaling :node( p.row( (has_s_scalings), "Scaling", scalings) ) :node( (has_s_scalings) and p.s_row("Scaling", s_scalings) ) -- SECTION: Career --[[ Some data will be collected first. ]] -- (Base) Games played local gamesPlayedText = {} if matchCount.total > 0 then table.insert(gamesPlayedText, matchCount.total .. " (total)") if matchCount.standard > 0 then table.insert(gamesPlayedText, matchCount.standard .. " (standard)") end end -- (Base) Winrate local winrateText = {} if matchCount.total > 0 then if matchCount.standard > 0 then table.insert(winrateText, p.roundedPct(matchWinCount.standard,matchCount.standard) .. "% (standard)" ) end end -- Super Games played local s_gamesPlayedText = {} if s_matchCount.total > 0 then table.insert(s_gamesPlayedText, s_matchCount.total .. " (total)") if s_matchCount.standard > 0 then table.insert(s_gamesPlayedText, s_matchCount.standard .. " (standard)") end end -- Super Winrate local s_winrateText = {} if s_matchCount.total > 0 then if s_matchCount.standard > 0 then table.insert(s_winrateText, p.roundedPct(s_matchWinCount.standard,s_matchCount.standard) .. "% (standard)" ) end end --[[ Begin rendering ]] -- Section Heading infobox:node( p.subheading( (isSuper), "Base Career", "Career ") ) :node( (isSuper) and p.s_subheading( "Super Career") ) -- Debuted :node( p.row( (isSuper), "Debut", frame.args["Debut"] ) ) :node( (isSuper) and p.s_row("Debut", frame.args["SUPER Debut"]) ) -- Games played :node( p.row( (isSuper), "Games played", (#gamesPlayedText > 0) and table.concat(gamesPlayedText, "<br>") or "<i>Not enough data...</i>" ) ) :node( (isSuper) and p.s_row( "Games played", (#s_gamesPlayedText > 0) and table.concat(s_gamesPlayedText, "<br>") or "<i>Not enough data...</i>" ) ) -- Winrate :node( p.row( (isSuper), "Winrate", (#winrateText > 0) and table.concat(winrateText, "<br>") or "<i>Not enough data...</i>" ) ) :node( (isSuper) and p.s_row( "Winrate", (#s_winrateText > 0) and table.concat(s_winrateText, "<br>") or "<i>Not enough data...</i>" ) ) return tostring(infobox) end function p.referenceTest() local element = mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( "mw-collapsible" ) :css( "text-align","left" ) local bigElement = mw.html.create( "div" ) :node( mw.clone(element) :attr( "colspan", "2" ) :node( "shitface") ) :node( mw.clone(element) :attr( "colspan", "2" ) :node( "shitface2") ) return tostring(element) .. "\n" .. tostring(bigElement) .. "\n" end function p.roundedPct(num, den) return (num/den % 0.01 < 0.005) and math.floor(num/den * 100) or math.ceil(num/den * 100) end function p.title() --[[local grammatical_cases = { ablative = 1, inessive = { ANCOVA = "ANCOVA" } } local cases2 = "ba" local cases3 = "ba" -- if grammatical_cases.inessive[frame:getParent():getTitle()] then cases2 = "true" else cases2 = "false" end -- if "ANCOVA" == frame:getParent():getTitle() then cases3 = "true" else cases3 = "false" end local detected = false detected = detected or true]] return mw.title.getCurrentTitle() end function p.ifexist() return tonumber(frame:expandTemplate{ title = "User:Helpme2222/Sandbox", args = {frame.args[1]} }) end function p.performance() for i = 1,5000000 do p.tableMake() end return end function p.performance1() local var = "" for i = 1,100000000 do if var[1] then end end return end function p.performance2() local var = "" for i = 1,100000000 do if type(var) == "table" then end end return end p.counter = 0 function p.tableBake() p.counter = p.counter + 1 return p.counter end function p.tableMake() p.counter = 0 local var = { keyword = {p.tableBake()}, kljuczslovo = {p.tableBake()}, yaoshiwenzi = {p.tableBake()}, llavepalabra = {p.tableBake()}, } return var end function p.expand() return frame:expandTemplate{ title = "User:Helpme2222/Sandbox" } end function p.title3() return mw.title.getCurrentTitle().fullText end function p.getBallAttribute() return p.getBallAttributeInternal(frame.args[1], frame.args[2], frame.args[3], frame.args[4]) end function p.getBallAttributeInternal(arg1_table, arg2_ball, arg3_att, arg4_iteration) local _, ballData = pcall( p.getBallAttributeInternalInternal, arg1_table, arg2_ball, arg3_att, arg4_iteration ) if _ then return mw.text.nowiki(ballData) else return "" end end function p.getBallAttributeInternalInternal(arg1_table, arg2_ball, arg3_att, arg4_iteration) local ballData = mw.loadData(arg1_table)[arg2_ball][arg3_att] if ballData[1] then return ballData[tonumber(arg4_iteration) or p.listCountInternal(ballData)] end return ballData end function p.emojiCodepointInternal( emoji ) emoji = mw.text.trim( emoji ) local i,v = mw.ustring.codepoint( emoji, 1, mw.ustring.len(emoji) ) if v then return "U+" .. string.format("%X", i ) .. " U+" .. string.format("%X", v ) else return "U+" .. string.format("%X", i ) end end function p.emojiCodepoint() local emoji = mw.text.trim( mw.getCurrentFrame().args[1] ) local i,v = mw.ustring.codepoint( emoji, 1, mw.ustring.len(emoji) ) if v then return "U+" .. string.format("%X", i ) .. " U+" .. string.format("%X", v ) else return "U+" .. string.format("%X", i ) end end function p.title2() local grammatical_cases = { ablative = 1, inessive = { ANCOVA = "ANCOVA", ["Module:Sandbox/22"] = "Module:Sandbox/22" } } local concepts = { grammatical_cases, } local PAGENAME = tostring(mw.title.getCurrentTitle()) -- local detected = false local out = {} local debugger = {} for i, group in ipairs(concepts) do if group.inessive[PAGENAME] then table.insert(debugger,"Okay, managed TRUE on "..i..":"..group.ablative) -- detected = detected or true local formattedGroup = {} for memberKey, memberRendervalue in pairs(group.inessive) do table.insert(formattedGroup, "<li>" .. memberRendervalue .. "</li>") end table.insert(out, "<h3>" .. group.ablative .. "</h3><ul>" .. table.concat( formattedGroup ) .. "</ul>" ) table.insert(out, "this sucks ass") return "this sucks ass" else table.insert(debugger,"Managed FALSE on "..i..":"..group.ablative..". Comparator: "..PAGENAME..", ") end end return debugger --[[ if detected then return tostring(detected) .. table.concat(out) end return --]] end function p.sanitizeChar(capture) -- If the set of likely illegal characters to appear in title expands, a rewrite of this as a table is merited if capture == "?" then return "" elseif capture == "#" then return "No. " end end function p.sanitizeTitle() local title = frame.args[1] return mw.ustring.gsub( title, "(?:\\?|\\#)", p.sanitizeChar) end function p.sanitizeTitletest2() return mw.ustring.gsub( "Ki vagy? (🌡️🌾⭐🗡️ VS 🪐 🪨 💣 🧿)", "(?:\\?|\\#)", p.sanitizeChar()) end function p.safetyTest() if string.len(frame.args[1]) < 500 then return frame.args[1] else return "" end end --[[ function array_iter(t) local i = 0 return function () i = i + 1 return t[i] end end --]] function p.listInline() --[[ This function is a godsend! https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#mw.text.listToText --]] local spritedTable = {} for i,entry in ipairs(balls[tonumber(frame.args[1])]) do spritedTable[i] = "{{Sprite|named=1|linked=1|"..entry.."}}" end return mw.text.listToText( spritedTable , ", ", ", and " ) end function p.listNavbox() -- https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#table.concat local spritedTable = {} for i,entry in ipairs(balls[tonumber(frame.args[1])]) do spritedTable[i] = "{{Sprite|named=1|linked=1|"..entry.."}}" end return table.concat( spritedTable , " • ") end function p.listCountInternal(table) local count = 0 for index,value in ipairs( table ) do count = count + 1 end return count end function p.listCount() return table.maxn(balls[tonumber(frame.args[1])]) end -- https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#table.maxn function p.tableTest() return balls[1][1] end function p.todaysBall() --[[ https://www.lua.org/pil/3.6.html The use of explicit indexing here is not strictly semantic; it's just to emphasize the rotation order. ]] local unixDay = math.floor(os.time()/86400) local ballTotalCount = 0 local ballCounts = {} for whichTable,subtable in ipairs(balls) do ballCounts[whichTable] = #subtable ballTotalCount = ballTotalCount + ballCounts[whichTable] end local cycleDayIndex, cycleStartingBall = unixDay % ballTotalCount, math.floor(unixDay/ballTotalCount) % ballTotalCount local cycleTodaysBall if ballTotalCount % 7 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*7) % ballTotalCount elseif ballTotalCount % 11 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*11) % ballTotalCount elseif ballTotalCount % 13 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*13) % ballTotalCount else cycleTodaysBall = (cycleStartingBall + cycleDayIndex*(ballTotalCount - 1)) % ballTotalCount end --[[ debug return cycleTodaysBall .. " " .. ballTotalCount .. " " .. os.time() .. " " .. math.floor(os.time()/86400) .. " " .. cycleDayIndex .. " " .. cycleStartingBall ]] for whichTable = 1, #balls do if ballCounts[whichTable] > cycleTodaysBall then return balls[whichTable][cycleTodaysBall + 1] else cycleTodaysBall = cycleTodaysBall - ballCounts[whichTable] end end --]] end return p; 1ytxysv4csy4d4o3sbled4yicev834c 0 331046 2835252 2835012 2026-10-01T02:09:56Z U3253363 3106362 /* Overview */ 2835252 wikitext text/x-wiki {{title|Self-concept and motivation:<br>How does self-concept relate to motivation?}} == Overview == {{RoundBoxTop|theme=3}} [[File:Sinclair Swimming.JPG|right|thumb|180px|'''Figure 1'''. Ash is a competitive swimmer and swims daily.]] ;Scenario Ash is a swimmer training for a national competition. Being "a swimmer" is the first thing Ash thinks of when she’s asked to describe herself and she’s eager to succeed in the upcoming competition. Ash wakes up at 4:00 a.m. every morning to swim four kilometres (see Figure 1). Her friend Riley is always surprised by how Ash wakes up so early and swims so much. Why is Ash able to do this when many would find this a struggle? {{RoundBoxBottom}} [[Motivation and emotion/Book/2010/Self-concept|Self-concept]] is an individual's understanding of who they are and how they feel about themselves (Wehrle & Fasbender, 2018). This includes a complex system of attitudes, beliefs, and judgements about oneself. Self-concept guides people in answering the question “who am I?”. But its importance extends beyond that. Self-concept influences thinking, feelings, and behaviour. Consider self-concept an internal compass which motivates and guides how people navigate the world. This chapter explores how the understanding of oneself influences what people are motivated to do and examines how what people repeatedly do subsequently shapes their self-concepts. Understanding this reciprocal relationship can help people develop motivation around meaningful identities while reducing the risk that failure becomes a threat to personal worth.{{RoundBoxTop|theme=12}} '''Focus questions''' *What is self-concept? *How does self-concept influence motivation? *How does motivation shape self-concept?{{RoundBoxBottom}} == What is self-concept? == Self-concept is a cognitive framework containing a system of self-knowledge (Wehrle & Fasbender, 2018). It is related to but unique from many of the popular “self-” constructs such as [[self-esteem]], [[w:Self-efficacy|self-efficacy]], and [[w:Self-image|self-image]]. Although each self-concept-relevant theory approaches the construct differently, several common properties emerge and provide the foundation for understanding its motivational effects (see Table 1). [[wikipedia:William_James|James]] (1892) conceptualised the self as having two separate parts: “I”, the subjective thinker and “knower”, and “me” the material, social and “known” self. Cooley's (1902) [[wikipedia:Looking-glass_self|looking-glass self theory]] later emphasised people as social beings, theorising that self-concept is a reflection of the responses and evaluations of others. Identity-based motivation theory (Oyserman, 2024) and the multidimensional model (Marsh et al., 1992) further develop that self-concept is multifaceted and dynamic, with different parts of the self influencing different behaviours. Together, these theories explain several mechanisms linking self-concept and motivation (see Table 1). '''Table 1''' ''Self-Concept Properties and Their Significance for Motivation'' {| class="wikitable" style="margin: auto;" !Property !Theory !Significance for motivation |- |'''Descriptive  ''' |James |Identity beliefs influence goals and expectations |- |'''Socially developed''' |The looking glass self, James |Social feedback influences which behaviours are pursued   |- |'''Dynamic''' |Multidimensional model, identity-based motivation theory |Self-concept changes situationally and with experience |- |'''Multidimensional''' |Multidimensional model |Different aspects of the self motivate different behaviours |- |'''Hierarchical  ''' |Multidimensional model |General and specific domains of the self influence each other and different behaviours |} == How does self-concept influence motivation? == Like self-concept, motivation is multidimensional, ubiquitous, and central to human behaviour (Bandhu et al., 2024). This creates an interesting intersection of properties; self-concept and motivation both influence which goals people pursue and responses to difficulty. This section explores how self-concept influences motivation.   === How the self directs and energises behaviour === Higgins' (1987) [[w:Self-discrepancy_theory|self-discrepancy theory]] proposes that people have three representations of the self: the actual (who one is), ideal (who one wants to become) and ought self (who one believes others want them to be; see Table 2). Ideal and ought representations of the self set standards for one to strive toward, thus laying a framework for goal direction. Discrepancies between parts of the self cause emotional vulnerabilities which also generate motivation (see Table 2). Actual/ideal self-discrepancies result in dejection-related emotions (e.g. frustration, dissatisfaction; Higgins, 1987). Actual/ought self-discrepancies result in agitation-related emotions (e.g. anxiety, guilt). The greater the discrepancy, the greater the emotional discomfort and thus motivation to reduce the discrepancy (Higgins, 1989). Meta-analytic findings support that greater discrepancies result in more negative emotions (Mason et al., 2019). However, Mason et al. (2019) found that actual/ideal and actual/ought self-discrepancies both correlated with dejection- and agitation-related emotions, contrary to self-discrepancy theory's proposition. Further, while the negative emotions resulting from discrepancies are proposed to motivate people to change behaviour and reduce discrepancies, MacIntyre and Vincze (2017) suggest positive emotions have greater motivating strength than negative emotions. This suggests that while self-concepts provide frameworks for goal selection and energise behaviour, self-discrepancies may not be the most significant emotional sources of motivation. '''Table 2''' ''Dimensions of the Self and Emotional Effects of Discrepancies'' {| class="wikitable" !Self dimension !Examples !Emotional effect of discrepancy with actual self |- |Actual |Daily behaviours, beliefs | - |- |Ideal |Dreams, aspirations |Dejection-related emotions |- |Ought |Duties, obligations |Agitation-related emotions |}[[w:Regulatory_focus_theory|Regulatory focus theory]] (Higgins, 1997) expands self-discrepancy theory to suggest different self-representations produce different motivational orientations. Ideal-self goals create a promotion focus, whereby one is motivated to seek positive outcomes (see Table 3). Ought-self goals create a prevention focus, whereby one is motivated to avoid negative outcomes. These regulatory focuses both positively correlated with intrinsic motivation in Wang et al.'s (2021) study of adolescent task engagement. However, promotion focuses positively correlated with creativity and an innovative cognitive style, whereas prevention focuses negatively correlated with an innovative cognitive style and was characterised by error avoidance. This shows that while both promotion and prevention orientations generate self-sustained motivation, they result in different approaches to tasks. '''Table 3''' ''Self-concept's Motivational Mechanisms'' {| class="wikitable" |+ !Self-discrepancy !Motivational focus !Motivational mechanism !Task approach |- |Actual-ideal |Promotion |Seek positive outcomes |Creativity, innovation |- |Actual-ought |Prevention |Avoid negative outcomes |Reduced innovation, error avoidance |} Oyserman’s (2024) [[wikipedia:Identity_based_motivation|identity-based motivation theory]] provides an alternative explanation to how self-concept directs behaviour. The theory proposes that situations influence which aspects of self-concept are active. Active identities change interpretations of difficulty and thus influence motivation. When behaviour is congruent with one’s active identity, challenges in completing that behaviour are interpreted as evidence the behaviour is important (Oyserman, 2015). This is because identity-congruent behaviours provide information about who one is and who one wants to become, making difficulty meaningful rather than discouraging (Oyserman, 2024). Incongruent actions that have the same challenges are interpreted as pointless. Together, this means that identities mediate motivation and help goal selection through the process of difficulty interpretation (Oyserman, 2024). {{RoundBoxTop|theme=3}}'''Case study comprehension check''' Ash is finding her long training sessions for the upcoming swimming competition difficult. However, when she's training, her future-self-identity as an Olympic swimmer is active and helps her interpret this as a meaningful challenge. For her non-swimmer friend, Riley, these difficulties may be interpreted as evidence swimming is not for them.{{RoundBoxBottom}} Illustrating the motivating role of the self-concept within this framework, Nurra and Oyserman (2018) found that motivation to pursue future identity-relevant goals in school children, and subsequent achievement, was influenced by how children thought about their future selves. Students were exposed to prompts that helped them think of their adult self as either near or far. Students in the adult-self-is-near group achieved significantly higher final grades than the adult-self-is-far group. These findings indicate that closely identifying with one’s future self and viewing that future self as attainable can motivate goal attainment. Together, these results support identity-based motivation theory and detail that self-concept drives behaviour by defining desirable outcomes and shaping how challenges and opportunities are interpreted. Together, self-discrepancy, regulatory focus, and identity-based motivation theories suggest that a person's perceived distance from a valued self can create motivational pressure to change and active identities influence interpretations of challenges, each modifying goal engagement and motivation. In all three theories, self-concept is central to motivation, driving goal selection as well as goal engagement. Thus, what motivates each person and how they subsequently behave is shaped by their self-concept. === How self-concept can undermine motivation === The theories and research discussed so far optimistically show how self-concept facilitates motivation. However, self-concept can also undermine motivation through self-worth contingencies. [[wikipedia:Contingent_self-esteem#Self-esteem_and_contingent_self-worth|Self-worth contingencies]] refer to the standards one feels they must meet to have value as a person (Showers et al., 2015). For individuals who have highly contingent self-worth, goal attainment is closely tied to their self-concept, meaning failure threatens their self-concept. Contingent self-worth motivates pursuit of success for domains that are important for one's self-worth but can result in avoidant behaviour and strong responses to failure. {{RoundBoxTop|theme=11|title=Quiz}} <quiz display=simple> '''What are self-worth contingencies?''' |type="()"} - How you feel about yourself + Standards people feel they must meet to have value as a person - The ways people compare themselves to others </quiz>{{RoundBoxBottom}} Lietz et al. (2026) qualitatively studied 17 participants' identity-shaped goals and found that failing to achieve these goals resulted in negative and severe emotional responses. Further, participants tended to attribute failure to personal shortcomings, due to how closely held the goal was to their self-concept. This resulted in reduced motivation to reattempt, or blind pursuit of the same goal without re-examining the approach. This is consistent with [[Motivation and emotion/Book/2024/Attribution theory and emotion|attribution theory]] (Weiner, 1985), which suggests that causal thinking processes, whereby one attributes outcomes to stable, uncontrollable factors, results in low motivation. Attributional styles affect self-evaluations and thus can undermine motivation when failure is attributed to stable aspects of the self (Bandhu et al., 2024). This can cause maladaptive behaviours to emerge. One such response to the threat of failure is self-handicapping. [[w:Self-handicapping|Self-handicapping]] involves creating obstacles to one's own goal so that failure may not be self-attributed (Török & Szabó, 2018). A handicap generates a plausible external explanation for an outcome other than the self. This indicates that a handicapper is willing to increase the probability of failure to protect their self-concept, demonstrating that self-concept can impact motivation by hindering goal pursuit (Coudevylle et al., 2020). {{RoundBoxTop|theme=3}}'''Case study comprehension check''' Ash cares a lot about succeeding in her swimming competition. To protect her self-concept as a successful swimmer, Ash may feign a mild illness at the competition so that any failure is attributed to her illness, rather than her competence. {{RoundBoxBottom}} [[File:Multidimensional_model_of_self-concept_diagram.png|thumb|536x536px|'''Figure 2.''' The hierarchical multidimensional model of self-concept (Marsh et al., 2019).]] Illustrating the causes of self-handicapping, Schwinger et al. (2022) found a medium negative correlation between general self-evaluations and self-handicapping and a medium positive correlation between fear of failure and self-handicapping. With more negative general self-evaluations and greater fear of failure, people are more likely to self-handicap, highlighting self-concept as an precursor to self-handicapping. However, in this study, general, rather than domain-specific measures were used. According to the multidimensional model, self-concept is a hierarchical, multi-faceted construct, and more specific self-concepts are more closely related to actual behaviour (see Figure 2; Marsh et al., 2019). Accordingly, future research should investigate domain-specific measures of self-concept and fear of failure to illustrate their direct influence on self-handicapping and task motivation. Self-handicapping demonstrates that self-concept-driven motivation is not always directed towards achieving valued outcomes. Protecting self-worth can become more important than goal engagement. Together, this research suggests self-concept can act both as a motivational resource, and a motivational vulnerability. {{RoundBoxTop|theme=9}}'''Intervention application: Reduce self-threat''' Self-handicapping shows that holding success as a contingency for self-worth can be damaging (Showers et al., 2015). Thus, interventions should reduce how much self-worth depends on outcomes, by promoting self-compassion, diverse positive self-concept domains, self-concept flexibility, and growth-oriented interpretations of failure to improve both wellbeing and motivation.{{RoundBoxBottom}} == How does motivation shape self-concept? == The research and theories discussed so far have detailed how self-concept directs and motivates behaviour. The following section explores how, and whether, this relationship works in reverse.   === How internalising motivation shapes self-concept === [[File:Self-determination theory psychological needs.jpg|thumb|450x450px|'''Figure 3.''' Self-determination theory proposes that autonomy, competence, and relatedness support autonomous motivation (Ryan & Deci, 2020).]][[Self-determination theory]] (Ryan & Deci, 2020) proposes motivation exists on a continuum of self-determination, ranging from externally to increasingly internally regulated behaviour. The continuum consists of external, introjected, identified, integrated, and intrinsic regulation. These motivation types are influenced by three innate needs: competence, autonomy, and relatedness (see Figure 3; Ryan & Deci, 2020). Understanding the progression of these needs and motivation types can provide insight into how motivational processes influence self-concept. Intrinsic motivation refers to autonomous behaviours completed for enjoyment (see Table 4; Morris et al., 2022). Extrinsic motivation involves engaging in behaviour for an outcome separable from the activity itself (Morris et al., 2022). Its regulation ranges from externally controlled to personally valued and fully integrated. How self-determined one's motivations are depends on the extent to which one has internalised the values, beliefs and perceptions of the behaviour into their self-concept. Meeting the needs of competence, autonomy and relatedness supports motivations to become progressively internalised, and behaviour increasingly self-endorsed (Chiu, 2023). However, it should be noted that this process does not necessarily occur in a fixed sequence. This illustrates how self-concept and motivation reciprocally form one another. The degree to which one identifies with a behaviour shapes their motivation to engage with the behaviour; when needs are met, motivated behaviours and psychological processes shape the self-concept. This internalisation process helps explain how Ash came to identify as a swimmer (see Table 4).   '''Table 4''' ''Applying Self-Determination Theory to Ash's Motivation and Self-Concept Development'' {| class="wikitable" style="margin: auto;" !Type of motivation !Ash's circumstances   !Mechanism |- |External regulation |Ash received a lollipop after swimming lessons.   |Non-self-determined drive.   |- |Introjected regulation |Ash wants her parents to think she is dedicated to swimming. |Partially internalised extrinsic motivation, low self-determination.   |- |Identified regulation |Swimming becomes important to Ash as she starts feeling like a good swimmer (competence) and drives herself to training (autonomy).   |More internalised and self-determined. |- |Integrated regulation |Ash starts to identify as a swimmer and with her swim team (relatedness).   |Fully integrated into self-concept. Highly self-determined but performed for valued outcome not enjoyment. |- |Intrinsic motivation |After the swimming competition, Ash continues swimming for the joy of it.   |Fully integrated into self-concept. Fully autonomous motivation for enjoyment. |} Chiu (2023) provided compelling evidence for how motivation shapes self-concept within the context of self-determination theory. In their study, 342 Hong Kong high school students completed STEM activities taught using a standard teaching approach or a self-determination theory teaching method, focusing on supporting needs of autonomy, competence and relatedness (see Figure 3). Self-report measures reflected that the needs-supporting teaching approach increased students' feelings of autonomy, competence and relatedness; and, consequently, increased STEM identity and interest. This supports that fulfilling core psychological needs promotes more autonomous motivation and develops one's identity. Further supporting this relationship, Yip et al.'s (2024) longitudinal study of 236 anti-poverty activists who completed self-reported social attitudes and personality measures at two timepoints found that increases in self-determined motivations positively correlated with group identification. However, non-self-determined motivations, such as external regulation, did not correlate with group identification. This suggests that self-determined motivation facilitates the incorporation of behaviour and group membership into one's self-concept.   Together, self-determination theory suggests self-concepts develop as values and behaviours are progressively internalised. Ash was not initially motivated because she identified as a swimmer. Her repeated engagement in swimming and fulfilment of psychological needs gradually transformed swimming into part of her identity. This demonstrates that motivation can be a mechanism through which self-concept develops and is not simply a motivating force. {{RoundBoxTop|theme=11|title=Quiz}} <quiz display=simple> '''Which statement best reflects how motivation shapes self-concept?''' |type="()"} - People are only motivated to engage in behaviours that are part of their self-concept. - Self-concept does not change through motivational processes. + Repeated engagement with a behaviour and satisfaction of psychological needs gradually makes a behaviour part of one's self-concept. </quiz>{{RoundBoxBottom}} === The cyclical process of motivation and self-concept development === The reciprocal effects model proposes that self-concept and achievement reinforce one another over time (Marsh et al., 2018). People with stronger self-concepts tend to achieve more highly, while achievement experiences subsequently shape self-concept. Motivation plays an important role in this process, by influencing how people behave toward achievement experiences. There is a growing body of research investigating this model. For example, Sewasew et al.'s (2018) longitudinal study with 2,342 German high schoolers demonstrated mathematics self-concept was positively correlated with mathematics achievement. Their study highlighted a mutually dependent relationship between academic self-concept and achievement, each mediated by motivation. However, Garn and Shen's (2015) longitudinal study of 329 participants' self-concept and motivation for exercise found that the psychological needs posited by self-determination theory (Ryan & Deci, 2022) did not predict physical self-concept at follow-ups. Physical self-concept was only shown to shape, rather than be shaped by exercise motivation. This result conflicts with the reciprocal effects model and Sewasew et al.'s (2018) results, which may be a reflection of the different self-concept domains examined, mathematics versus physical self-concept. This may indicate that reciprocal effects are domain specific; the multidimensional model suggests academic and physical self-concepts function independently, meaning findings from one domain may not generalise to another (Marsh et al., 2019). Thus, future research should directly compare the reciprocal relationship between self-concept and motivation within different domains. Similarly, Sorjonen et al. (2024) reanalysed meta-analytic results which had provided evidence for the reciprocal effects model. Sorjonen et al. (2024) found that conclusions about the longitudinal relationship between achievement and academic self-concept changed depending on the statistical model used. Hübner et al.'s (2023) support for the reciprocal effects model was also inconsistent between statistical models. This may indicate a spurious correlation that undermines the credibility of the reciprocal effects model. Taken together, these findings suggest that achievement can shape self-concept, but the strength and direction of this relationship may depend on the domain being examined and the methodological approach used. Although the reciprocal effects model remains influential, current evidence indicates that the relationship between motivation, achievement, and self-concept is more complex than originally proposed. == Conclusion == Self-concept is a multidimensional and socially developed framework of beliefs about oneself which acts as a guiding compass. Self-concept shapes motivation by determining which goals feel meaningful, attainable, and identity-consistent through processes of self-discrepancy, difficulty interpretation and self-worth contingencies. Self-discrepancy theory explains how distance from valued selves can create motivational pressure for change and identity-based motivation theory explains how active identities change the meaning of difficulty, whereas self-worth contingencies can undermine motivation. Together, these theories detail how self-concept influences goal direction and engagement and provide insight that motivation-improving interventions should consider targeting how people understand themselves rather than solely targeting behaviours. Motivation may also influence self-concept. Self-determination theory details that motivation and subsequent behaviours form self-concept through internalisation processes when psychological needs are met. However, inconsistent support for the reciprocal effects model indicates that the extent to which motivation reshapes self-concept may vary across domains and statistical models. {{RoundBoxTop|theme=3}} '''Take-home message''' With self-concept and motivation inherently linked, who people believe they are shapes the goals they pursue, while motivations, behaviours, and experiences continually reshape who people become. {{RoundBoxBottom}} {{RoundBoxTop|theme=11|title=Quiz}}<quiz display=simple> {'''Chapter comprehension check quiz:''' Ash wakes up at 4:00 a.m. each day to train because being a swimmer is a central part of her identity. According to the chapter, what best explains Ash's motivation? |type="()"} +Self-concept acts as an internal compass that guides goals and behaviour. -Motivation is caused only by external rewards and punishment. -Self-concept remains fixed and has little influence on actions. </quiz> {{RoundBoxBottom}} == See also == * [[wikipedia:Self-concept|Self-concept]] (Wikipedia) * [[Motivation and emotion/Book/2019/Self-concept clarity|Self-concept clarity]] (Book chapter, 2019) * [[Motivation and emotion/Book/2014/Self-efficacy and motivation|Self-efficacy and motivation]] (Book chapter, 2014) == References == {{Hanging indent|Bandhu, D., Mohan, M. M., Nittala, N. A. P., Jadhav, P., Bhadauria, A., & Saxena, K. K. (2024). Theories of motivation: A comprehensive analysis of human behavior drivers. ''Acta Psychologica, 244'', 104177. https://doi.org/10.1016/j.actpsy.2024.104177 Chiu, T.K. (2023). Using self-determination theory (SDT) to explain student STEM interest and identity development. ''Instructional Science, 52'', 89–107. https://doi.org/10.1007/s11251-023-09642-8 Cooley, C. H. (1902). The looking-glass self. ''The production of reality: Essays and readings on social interaction, 6''(1902), 126–28. Coudevylle, G. R., Boulley-Escriva, G., Finez, L., Eugène, K., & Robin, N. (2020). An experimental investigation of claimed self-handicapping strategies across motivational climates based on achievement goal and self-determination theories. ''Educational Psychology, 40''(8), 1002–1021. https://doi.org/10.1080/01443410.2020.1746237 Garn, A., & Shen, B. (2015). Physical self-concept and basic psychological needs in exercise: Are there reciprocal effects? ''International Journal of Sport and Exercise Psychology, 13''(2), 169–181. https://doi.org/10.1080/1612197X.2014.940994 Higgins, E. T. (1987). Self-discrepancy: A theory relating self and affect. ''Psychological Review, 94''(3), 319. Higgins, E. T. (1989). Self-discrepancy theory: What patterns of self-beliefs cause people to suffer?. In ''Advances in experimental social psychology'' (Vol. 22, pp. 93–136). Academic Press. Higgins, E. T., Shah, J., & Friedman, R. (1997). Emotional responses to goal attainment: Strength of regulatory focus as moderator. ''Journal of Personality and Social Psychology, 72''(3), 515–525. https://doi.org/10.1037/0022-3514.72.3.515 Hübner, N., Wagner, W., Zitzmann, S., & Nagengast, B. (2023). How strong is the evidence for a causal reciprocal effect? Contrasting traditional and new methods to investigate the reciprocal effects model of self-concept and achievement. ''Educational Psychology Review, 35'', 6. https://doi.org/10.1007/s10648-023-09724-6 James, W. (1892). The self. In W. James (Ed.), ''Psychology: Briefer course'' (pp. 176–216). Macmillan and Co. https://doi.org/10.1037/11630-012 Lietz, R., Whittaker, S., & Su, N. M. (2026). ‘It meant something about who I am’: What the lived experience of failure teaches us about designing for goal setting. ''Behaviour & Information Technology,'' 1–27. https://doi.org/10.1080/0144929X.2026.2711023 MacIntyre, P. D., & Vincze, L. (2017). Positive and negative emotions in motivation for second language learning. ''Studies in Second Language Learning and Teaching, 7''(1), 61–88. https://doi.org/10.14746/ssllt.2017.7.1.4 Marsh, H. W., Byrne, B. M., & Shavelson, R. J. (1992). A multidimensional, hierarchical self-concept. In T. M. Brinthaupt & R. P. Lipka (Eds.), ''The self: Definitional and methodological issues'' (pp. 44–95). State University of New York Press. Marsh, H. W., Martin, A. J., Yeung, A. S., & Craven, R. G. (2018). Chapter 6: Competence self-perceptions. In A. J. Elliot, C. S. Dweck, & D. S. Yeager (Eds.), ''Handbook of competence and motivation: Theory and application'' (pp. 85–115). Guilford Publications. Marsh, H. W., Seaton, M., Dicke, T., Parker, P. D., & Horwood, M. S. (2019). The centrality of academic self-concept to motivation and learning. In K. A. Renninger, & S. E. Hidi (Eds.), ''The Cambridge handbook of motivation and learning'' (pp. 36–62). Cambridge University Press. https://doi.org/10.1017/9781316823279.004 Mason, T. B., Smith, K. E., Engwall, A., Lass, A., Mead, M., Sorby, M., Bjorlie, K., Strauman, T. J., & Wonderlich, S. (2019). Self-discrepancy theory as a transdiagnostic framework: A meta-analysis of self-discrepancy and psychopathology. ''Psychological Bulletin, 145''(4), 372–389. https://doi.org/10.1037/bul0000186 Morris, L. S., Grehl, M. M., Rutter, S. B., Mehta, M., & Westwater, M. L. (2022). On what motivates us: A detailed review of intrinsic v. extrinsic motivation. ''Psychological Medicine, 52''(10), 1801–1816. https://doi.org/10.1017/S0033291722001611 Nurra, C., & Oyserman, D. (2018). From future self to current action: An identity-based motivation perspective. ''Self and Identity, 17''(3), 343-364. https://doi.org/10.1080/15298868.2017.1375003 Oyserman, D. (2015). Identity-based motivation. ''Emerging Trends in the Social and Behavioral Sciences, 38'', 1–11. https://doi.org/10.1002/9781118900772.etrds0171 Oyserman, D. (2024), Identity-based motivation and the motivational consequences of difficulty. ''Social and Personality Psychology Compass, 18'', e70028. https://doi.org/10.1111/spc3.70028 Ryan, R. M., & Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. ''Contemporary Educational Psychology, 61'', 101860. https://doi.org/10.1016/j.cedpsych.2020.101860 Ryan, R. M., & Deci, E. L. (2022). Self-determination theory. In F. Maggino (Ed.), ''Encyclopedia of quality of life and well-being research'' (pp. 1–7). Springer, Cham. https://doi.org/10.1007/978-3-319-69909-7_2630-2 Schwinger, M., Trautner, M., Pütz, N., Fabianek, S., Lemmer, G., Lauermann, F., & Wirthwein, L. (2022). Why do students use strategies that hurt their chances of academic success? A meta-analysis of antecedents of academic self-handicapping. ''Journal of Educational Psychology, 114''(3), 576–596. https://doi.org/10.1037/edu0000706 Seaton, M., Parker, P., Marsh, H. W., Craven, R. G., & Yeung, A. S. (2014). The reciprocal relations between self-concept, motivation and achievement: Juxtaposing academic self-concept and achievement goal orientations for mathematics success. ''Educational Psychology, 34''(1), 49–72. https://doi.org/10.1080/01443410.2013.825232 Sewasew, D., Schroeders, U., Schiefer, I. M., Weirich, S., & Artelt, C. (2018). Development of sex differences in math achievement, self-concept, and interest from grade 5 to 7. ''Contemporary Educational Psychology, 54'', 55–65. https://doi.org/10.1016/j.cedpsych.2018.05.003 Showers, C. J., Ditzfeld, C. P., & Zeigler-Hill, V. (2015). Self-concept structure and the quality of self-knowledge. ''Journal of Personality, 83''(5), 535-551. https://doi.org/10.1111/jopy.12130 Sorjonen, K., Ingre, M., Melin, B., & Nilsonne, G. (2024). Questioning the reciprocal effects model of academic self-concept and achievement: A reanalysis of a meta-analysis of longitudinal studies and a simulation. ''Sage Open, 14''(4). https://doi.org/10.1177/21582440241292826 Török, L., & Szabó, Z. P. (2018). The theory of self-handicapping: Forms, influencing factors and measurement. ''Ceskoslovenska Psychologie, 62''(2), 173-188. Wang, L., Cui, Y., Wang, X., Wang, J., Du, K., & Luo, Z. (2021). Regulatory focus, motivation, and their relationship with creativity among adolescents. ''Frontiers in Psychology, 12'', 666071. https://doi.org/10.3389/fpsyg.2021.666071 Wehrle, K., & Fasbender, U. (2018). Self-concept. In Zeigler-Hill, V., & Shackelford, T. (Eds.), ''Encyclopedia of personality and individual differences'' (pp. 1–5). Springer, Cham. https://doi.org/10.1007/978-3-319-28099-8_2001-1 Weiner, B. (1985). An attributional theory of achievement motivation and emotion. ''Psychological Review, 92''(4), 548–573. https://doi.org/10.1037/0033-295X.92.4.548 Yip, L., Thomas, E. F., Amiot, C., Louis, W. R., & McGarty, C. (2024). Autonomous motives foster sustained commitment to action: Integrating self-determination theory and the social identity approach. ''Personality and Social Psychology Bulletin, 50''(5), 750–765. https://doi.org/10.1177/01461672221148396 }} == External links == * [https://rickhanson.com/being-well-podcast-self-concept-the-secret-to-changing-who-you-are/ Being well podcast: Self-concept: The secret to changing WHO you are] (Being Well Podcast) * [https://www.youtube.com/watch?v=Nck7lP-6C2g Unlocking success: The power of self-efficacy and self-concept] (TEDx Talks) * [https://www.ted.com/talks/anil_ananthaswamy_where_does_your_sense_of_self_come_from_a_scientific_look Where does your sense of self come from? A scientific look] (TEDx Talks) [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Self-concept]] [[Category:Motivation and emotion/Book/2026]] [[Category:Motivation and emotion/Book/Motivation]] bfiosi9t8zdb6ql3tchck425cat2e5q 2835268 2835252 2026-10-01T04:03:08Z U3253363 3106362 /* Overview */ A few grammatical changes suggested by Studiosity. https://studiosity.com/connect/partners/university-of-canberra/student_home 2835268 wikitext text/x-wiki {{title|Self-concept and motivation:<br>How does self-concept relate to motivation?}} == Overview == {{RoundBoxTop|theme=3}} [[File:Sinclair Swimming.JPG|right|thumb|180px|'''Figure 1'''. Ash is a competitive swimmer and swims daily.]] ;Scenario Ash is a swimmer training for a national competition. Being "a swimmer" is the first thing Ash thinks of when she’s asked to describe herself and she’s eager to succeed in the upcoming competition. Ash wakes up at 4:00 a.m. every morning to swim four kilometres (see Figure 1). Her friend Riley is always surprised by how Ash wakes up so early and swims so much. Why is Ash able to do this when many would find this a struggle? {{RoundBoxBottom}} [[Motivation and emotion/Book/2010/Self-concept|Self-concept]] is an individual's understanding of who they are and how they feel about themselves (Wehrle & Fasbender, 2018). This includes a complex system of attitudes, beliefs, and judgements about oneself. Self-concept guides people in answering the question “who am I?”. But its importance extends beyond that. Self-concept influences thinking, feelings, and behaviour. Consider self-concept an internal compass which motivates and guides how people navigate the world. This chapter explores how the understanding of oneself influences what people are motivated to do and examines how what people repeatedly do subsequently shapes their self-concepts. Understanding this reciprocal relationship can help people develop motivation around meaningful identities while reducing the risk that failure becomes a threat to personal worth.{{RoundBoxTop|theme=12}} '''Focus questions''' *What is self-concept? *How does self-concept influence motivation? *How does motivation shape self-concept?{{RoundBoxBottom}} == What is self-concept? == Self-concept is a cognitive framework containing a system of self-knowledge (Wehrle & Fasbender, 2018). It is related, but unique to many of the popular “self-” constructs such as [[self-esteem]], [[w:Self-efficacy|self-efficacy]], and [[w:Self-image|self-image]]. Although each self-concept-relevant theory approaches the construct differently, several common properties emerge and provide the foundation for understanding its motivational effects (see Table 1). [[wikipedia:William_James|James]] (1892) conceptualised the self as having two separate parts: “I”, the subjective thinker and “knower”, and “me”, the material, social and “known” self. Cooley's (1902) [[wikipedia:Looking-glass_self|looking-glass self theory]] later emphasised people as social beings, theorising that self-concept is a reflection of the responses and evaluations of others. Identity-based motivation theory (Oyserman, 2024) and the multidimensional model (Marsh et al., 1992) further develop that self-concept is multifaceted and dynamic, with different parts of the self influencing different behaviours. Together, these theories explain several mechanisms linking self-concept and motivation (see Table 1). '''Table 1''' ''Self-Concept Properties and Their Significance for Motivation'' {| class="wikitable" style="margin: auto;" !Property !Theory !Significance for motivation |- |'''Descriptive  ''' |James |Identity beliefs influence goals and expectations |- |'''Socially developed''' |The looking glass self, James |Social feedback influences which behaviours are pursued   |- |'''Dynamic''' |Multidimensional model, identity-based motivation theory |Self-concept changes situationally and with experience |- |'''Multidimensional''' |Multidimensional model |Different aspects of the self motivate different behaviours |- |'''Hierarchical  ''' |Multidimensional model |General and specific domains of the self influence each other and different behaviours |} == How does self-concept influence motivation? == Like self-concept, motivation is multidimensional, ubiquitous, and central to human behaviour (Bandhu et al., 2024). This creates an interesting intersection of properties; self-concept and motivation both influence which goals people pursue and responses to difficulty. This section explores how self-concept influences motivation.   === How the self directs and energises behaviour === Higgins' (1987) [[w:Self-discrepancy_theory|self-discrepancy theory]] proposes that people have three representations of the self: the actual (who one is), ideal (who one wants to become), and ought self (who one believes others want them to be; see Table 2). Ideal and ought selves set standards for one to strive toward, thus laying a framework for goal direction. Discrepancies between parts of the self cause emotional vulnerabilities which also generate motivation (see Table 2). Actual/ideal self-discrepancies result in dejection-related emotions (e.g. frustration, dissatisfaction; Higgins, 1987). Actual/ought self-discrepancies result in agitation-related emotions (e.g. anxiety, guilt). The greater the discrepancy, the greater the emotional discomfort and thus motivation to reduce the discrepancy (Higgins, 1989). Meta-analytic findings support that greater discrepancies result in more negative emotions (Mason et al., 2019). However, Mason et al. (2019) found that actual/ideal and actual/ought self-discrepancies both correlated with dejection- and agitation-related emotions, contrary to self-discrepancy theory's proposition. Further, while the negative emotions resulting from discrepancies are proposed to motivate people to change behaviour and reduce discrepancies, MacIntyre and Vincze (2017) suggest positive emotions have greater motivating strength than negative emotions. This suggests that while self-concepts provide frameworks for goal selection and energise behaviour, self-discrepancies may not be the most significant emotional sources of motivation. '''Table 2''' ''Dimensions of the Self and Emotional Effects of Discrepancies'' {| class="wikitable" !Self dimension !Examples !Emotional effect of discrepancy with actual self |- |Actual |Daily behaviours, beliefs | - |- |Ideal |Dreams, aspirations |Dejection-related emotions |- |Ought |Duties, obligations |Agitation-related emotions |}[[w:Regulatory_focus_theory|Regulatory focus theory]] (Higgins, 1997) expands self-discrepancy theory to suggest different self-representations produce different motivational orientations. Ideal-self goals create a promotion focus, whereby one is motivated to seek positive outcomes (see Table 3). Ought-self goals create a prevention focus, whereby one is motivated to avoid negative outcomes. These regulatory focuses both positively correlated with intrinsic motivation in Wang et al.'s (2021) study of adolescent task engagement. However, promotion focuses positively correlated with creativity and an innovative cognitive style, whereas prevention focuses negatively correlated with an innovative cognitive style and was characterised by error avoidance. This shows that while both promotion and prevention orientations generate self-sustained motivation, they result in different approaches to tasks. '''Table 3''' ''Self-concept's Motivational Mechanisms'' {| class="wikitable" |+ !Self-discrepancy !Motivational focus !Motivational mechanism !Task approach |- |Actual-ideal |Promotion |Seek positive outcomes |Creativity, innovation |- |Actual-ought |Prevention |Avoid negative outcomes |Reduced innovation, error avoidance |} Oyserman’s (2024) [[wikipedia:Identity_based_motivation|identity-based motivation theory]] provides an alternative explanation to how self-concept directs behaviour. The theory proposes that situations influence which aspects of self-concept are active. Active identities change interpretations of difficulty and thus influence motivation. When behaviour is congruent with one’s active identity, challenges in completing that behaviour are interpreted as evidence the behaviour is important (Oyserman, 2015). This is because identity-congruent behaviours provide information about who one is and who one wants to become, making difficulty meaningful rather than discouraging (Oyserman, 2024). Incongruent actions that have the same challenges are interpreted as pointless. Together, this means that identities mediate motivation and help goal selection through the process of difficulty interpretation (Oyserman, 2024). {{RoundBoxTop|theme=3}}'''Case study comprehension check''' Ash is finding her long training sessions for the upcoming swimming competition difficult. However, when she's training, her future-self-identity as an Olympic swimmer is active and helps her interpret this as a meaningful challenge. For her non-swimmer friend, Riley, these difficulties may be interpreted as evidence swimming is not for them.{{RoundBoxBottom}} Illustrating the motivating role of the self-concept within this framework, Nurra and Oyserman (2018) found that motivation to pursue future identity-relevant goals in school children, and subsequent achievement, was influenced by how children thought about their future selves. Students were exposed to prompts that helped them think of their adult self as either near or far. Students in the adult-self-is-near group achieved significantly higher final grades than the adult-self-is-far group. These findings indicate that closely identifying with one’s future self and viewing that future self as attainable can motivate goal attainment. Together, these results support identity-based motivation theory and detail that self-concept drives behaviour by defining desirable outcomes and shaping how challenges and opportunities are interpreted. Together, self-discrepancy, regulatory focus, and identity-based motivation theories suggest that a person's perceived distance from a valued self can create motivational pressure to change and active identities influence interpretations of challenges. These states modify goal engagement and motivation. In all three theories, self-concept is central to motivation, driving goal selection as well as goal engagement. Thus, what motivates each person, and how they subsequently behave, are shaped by their self-concept. === How self-concept can undermine motivation === The theories and research discussed so far optimistically show how self-concept facilitates motivation. However, self-concept can also undermine motivation through self-worth contingencies. [[wikipedia:Contingent_self-esteem#Self-esteem_and_contingent_self-worth|Self-worth contingencies]] refer to the standards one feels they must meet to have value as a person (Showers et al., 2015). For individuals who have highly contingent self-worth, goal attainment is closely tied to their self-concept, meaning failure threatens their self-concept. Contingent self-worth motivates pursuit of success for domains that are important for one's self-worth but can result in avoidant behaviour and strong responses to failure. {{RoundBoxTop|theme=11|title=Quiz}} <quiz display=simple> '''What are self-worth contingencies?''' |type="()"} - How you feel about yourself + Standards people feel they must meet to have value as a person - The ways people compare themselves to others </quiz>{{RoundBoxBottom}} Lietz et al. (2026) qualitatively studied 17 participants' identity-shaped goals and found that failing to achieve these goals resulted in negative and severe emotional responses. Further, participants tended to attribute failure to personal shortcomings, because of how closely held the goal was to their self-concept. This resulted in reduced motivation to reattempt, or blind pursuit of the same goal without re-examining the approach. This is consistent with [[Motivation and emotion/Book/2024/Attribution theory and emotion|attribution theory]] (Weiner, 1985), which suggests that causal thinking processes, whereby one attributes outcomes to stable, uncontrollable factors, result in low motivation. Attributional styles affect self-evaluations and thus can undermine motivation when failure is attributed to stable aspects of the self (Bandhu et al., 2024). This can cause maladaptive behaviours to emerge. One such response to the threat of failure is self-handicapping. [[w:Self-handicapping|Self-handicapping]] involves creating obstacles to one's own goal so that failure may not be self-attributed (Török & Szabó, 2018). A handicap generates a plausible external explanation for an outcome other than the self. This indicates that a handicapper is willing to increase the probability of failure to protect their self-concept, demonstrating that self-concept can impact motivation by hindering goal pursuit (Coudevylle et al., 2020). {{RoundBoxTop|theme=3}}'''Case study comprehension check''' Ash cares a lot about succeeding in her swimming competition. To protect her self-concept as a successful swimmer, Ash may feign a mild illness at the competition so that any failure is attributed to her illness, rather than her competence. {{RoundBoxBottom}} [[File:Multidimensional_model_of_self-concept_diagram.png|thumb|536x536px|'''Figure 2.''' The hierarchical multidimensional model of self-concept (Marsh et al., 2019).]] Illustrating the causes of self-handicapping, Schwinger et al. (2022) found a medium negative correlation between general self-evaluations and self-handicapping and a medium positive correlation between fear of failure and self-handicapping. With more negative general self-evaluations and greater fear of failure, people are more likely to self-handicap, highlighting self-concept as an precursor to self-handicapping. However, in this study, general, rather than domain-specific measures were used. According to the multidimensional model, self-concept is a hierarchical, multi-faceted construct, and more specific self-concepts are more closely related to actual behaviour (see Figure 2; Marsh et al., 2019). Accordingly, future research should investigate domain-specific measures of self-concept and fear of failure to illustrate their direct influence on self-handicapping and task motivation. Self-handicapping demonstrates that self-concept-driven motivation is not always directed towards achieving valued outcomes. Protecting self-worth can become more important than goal engagement. Together, this research suggests self-concept can act both as a motivational resource, and a motivational vulnerability. {{RoundBoxTop|theme=9}}'''Intervention application: Reduce self-threat''' Self-handicapping shows that holding success as a contingency for self-worth can be damaging (Showers et al., 2015). Thus, interventions should reduce how much self-worth depends on outcomes, by promoting self-compassion, diverse positive self-concept domains, self-concept flexibility, and growth-oriented interpretations of failure to improve both wellbeing and motivation.{{RoundBoxBottom}} == How does motivation shape self-concept? == The research and theories discussed so far have detailed how self-concept directs and motivates behaviour. The following section explores how, and whether, this relationship works in reverse.   === How internalising motivation shapes self-concept === [[File:Self-determination theory psychological needs.jpg|thumb|450x450px|'''Figure 3.''' Self-determination theory proposes that autonomy, competence, and relatedness support autonomous motivation (Ryan & Deci, 2020).]][[Self-determination theory]] (Ryan & Deci, 2020) proposes motivation exists on a continuum of self-determination, ranging from externally to increasingly internally regulated behaviour. The continuum consists of external, introjected, identified, integrated, and intrinsic regulation. These motivation types are influenced by three innate needs: competence, autonomy, and relatedness (see Figure 3; Ryan & Deci, 2020). Understanding the progression of these needs and motivation types can provide insight into how motivational processes influence self-concept. Intrinsic motivation refers to autonomous behaviours completed for enjoyment (see Table 4; Morris et al., 2022). Extrinsic motivation involves engaging in behaviour for an outcome separable from the activity itself (Morris et al., 2022). Its regulation ranges from externally controlled to personally valued and fully integrated. How self-determined one's motivations are depends on the extent to which one has internalised the values, beliefs and perceptions of the behaviour into their self-concept. Meeting the needs of competence, autonomy and relatedness supports motivations to become progressively internalised, and behaviour increasingly self-endorsed (Chiu, 2023). However, it should be noted that this process does not necessarily occur in a fixed sequence. This illustrates how self-concept and motivation reciprocally form one another. The degree to which one identifies with a behaviour shapes their motivation to engage with the behaviour; when needs are met, motivated behaviours and psychological processes shape the self-concept. This internalisation process helps explain how Ash came to identify as a swimmer (see Table 4).   '''Table 4''' ''Applying Self-Determination Theory to Ash's Motivation and Self-Concept Development'' {| class="wikitable" style="margin: auto;" !Type of motivation !Ash's circumstances   !Mechanism |- |External regulation |Ash received a lollipop after swimming lessons.   |Non-self-determined drive.   |- |Introjected regulation |Ash wants her parents to think she is dedicated to swimming. |Partially internalised extrinsic motivation, low self-determination.   |- |Identified regulation |Swimming becomes important to Ash as she starts feeling like a good swimmer (competence) and drives herself to training (autonomy).   |More internalised and self-determined. |- |Integrated regulation |Ash starts to identify as a swimmer and with her swim team (relatedness).   |Fully integrated into self-concept. Highly self-determined but performed for valued outcome not enjoyment. |- |Intrinsic motivation |After the swimming competition, Ash continues swimming for the joy of it.   |Fully integrated into self-concept. Fully autonomous motivation for enjoyment. |} Chiu (2023) provided compelling evidence for how motivation shapes self-concept within the context of self-determination theory. In their study, 342 Hong Kong high school students completed STEM activities taught using a standard teaching approach or a self-determination theory teaching method, focusing on supporting needs of autonomy, competence and relatedness (see Figure 3). Self-report measures reflected that the needs-supporting teaching approach increased students' feelings of autonomy, competence and relatedness; and, consequently, increased STEM identity and interest. This supports that fulfilling core psychological needs promotes more autonomous motivation and develops one's identity. Further supporting this relationship, Yip et al.'s (2024) longitudinal study of 236 anti-poverty activists who completed self-reported social attitudes and personality measures at two timepoints found that increases in self-determined motivations positively correlated with group identification. However, non-self-determined motivations, such as external regulation, did not correlate with group identification. This suggests that self-determined motivation facilitates the incorporation of behaviour and group membership into one's self-concept.   Together, self-determination theory suggests self-concepts develop as values and behaviours are progressively internalised. Ash was not initially motivated because she identified as a swimmer. Her repeated engagement in swimming and fulfilment of psychological needs gradually transformed swimming into part of her identity. This demonstrates that motivation can be a mechanism through which self-concept develops and is not simply a motivating force. {{RoundBoxTop|theme=11|title=Quiz}} <quiz display=simple> '''Which statement best reflects how motivation shapes self-concept?''' |type="()"} - People are only motivated to engage in behaviours that are part of their self-concept. - Self-concept does not change through motivational processes. + Repeated engagement with a behaviour and satisfaction of psychological needs gradually makes a behaviour part of one's self-concept. </quiz>{{RoundBoxBottom}} === The cyclical process of motivation and self-concept development === The reciprocal effects model proposes that self-concept and achievement reinforce one another over time (Marsh et al., 2018). People with stronger self-concepts tend to achieve more highly, while achievement experiences subsequently shape self-concept. Motivation plays an important role in this process, influencing how people behave toward achievement experiences. There is a growing body of research investigating this model. For example, Sewasew et al.'s (2018) longitudinal study with 2,342 German high schoolers demonstrated mathematics self-concept was positively correlated with mathematics achievement. Their study highlighted a mutually dependent relationship between academic self-concept and achievement, each mediated by motivation. However, Garn and Shen's (2015) longitudinal study of 329 participants' self-concept and motivation for exercise found that the psychological needs posited by self-determination theory (Ryan & Deci, 2022) did not predict physical self-concept at follow-ups. Physical self-concept was only shown to shape, rather than be shaped by exercise motivation. This result conflicts with the reciprocal effects model and Sewasew et al.'s (2018) results, which may be a reflection of the different self-concept domains examined, mathematics versus physical self-concept. This may indicate that reciprocal effects are domain specific; the multidimensional model suggests academic and physical self-concepts function independently, meaning findings from one domain may not generalise to another (Marsh et al., 2019). Thus, future research should directly compare the reciprocal relationship between self-concept and motivation within different domains. Similarly, Sorjonen et al. (2024) reanalysed meta-analytic results which had provided evidence for the reciprocal effects model. Sorjonen et al. (2024) found that conclusions about the longitudinal relationship between achievement and academic self-concept changed depending on the statistical model used. Hübner et al.'s (2023) support for the reciprocal effects model was also inconsistent between statistical models. This may indicate a spurious correlation that undermines the credibility of the reciprocal effects model. Taken together, these findings suggest that achievement can shape self-concept, but the strength and direction of this relationship may depend on the domain being examined and the methodological approach used. Although the reciprocal effects model remains influential, current evidence indicates that the relationship between motivation, achievement, and self-concept is more complex than originally proposed. == Conclusion == Self-concept is a multidimensional and socially developed framework of beliefs about oneself which acts as a guiding compass. Self-concept shapes motivation by determining which goals feel meaningful, attainable, and identity-consistent through processes of self-discrepancy, difficulty interpretation and self-worth contingencies. Self-discrepancy theory explains how distance from valued selves can create motivational pressure for change. Identity-based motivation theory explains how active identities change the meaning of difficulty. Whereas self-worth contingencies can undermine motivation. Together, these theories detail that self-concept influences goal direction and engagement through social, emotional and cognitive processes. These theories provide insight that motivation-improving interventions should consider targeting how people understand themselves rather than solely targeting behaviours. Motivation may also influence self-concept. Self-determination theory details that motivation and subsequent behaviours form self-concept through internalisation processes when psychological needs are met. However, inconsistent support for the reciprocal effects model indicates that the extent to which motivation reshapes self-concept may vary across domains and statistical models. {{RoundBoxTop|theme=3}} '''Take-home message''' With self-concept and motivation inherently linked, who people believe they are shapes the goals they pursue, while motivations, behaviours, and experiences continually reshape who people become. {{RoundBoxBottom}} {{RoundBoxTop|theme=11|title=Quiz}}<quiz display=simple> {'''Chapter comprehension check quiz:''' Ash wakes up at 4:00 a.m. each day to train because being a swimmer is a central part of her identity. According to the chapter, what best explains Ash's motivation? |type="()"} +Self-concept acts as an internal compass that guides goals and behaviour. -Motivation is caused only by external rewards and punishment. -Self-concept remains fixed and has little influence on actions. </quiz> {{RoundBoxBottom}} == See also == * [[wikipedia:Self-concept|Self-concept]] (Wikipedia) * [[Motivation and emotion/Book/2019/Self-concept clarity|Self-concept clarity]] (Book chapter, 2019) * [[Motivation and emotion/Book/2014/Self-efficacy and motivation|Self-efficacy and motivation]] (Book chapter, 2014) == References == {{Hanging indent|Bandhu, D., Mohan, M. M., Nittala, N. A. P., Jadhav, P., Bhadauria, A., & Saxena, K. K. (2024). Theories of motivation: A comprehensive analysis of human behavior drivers. ''Acta Psychologica, 244'', 104177. https://doi.org/10.1016/j.actpsy.2024.104177 Chiu, T.K. (2023). Using self-determination theory (SDT) to explain student STEM interest and identity development. ''Instructional Science, 52'', 89–107. https://doi.org/10.1007/s11251-023-09642-8 Cooley, C. H. (1902). The looking-glass self. ''The production of reality: Essays and readings on social interaction, 6''(1902), 126–28. Coudevylle, G. R., Boulley-Escriva, G., Finez, L., Eugène, K., & Robin, N. (2020). An experimental investigation of claimed self-handicapping strategies across motivational climates based on achievement goal and self-determination theories. ''Educational Psychology, 40''(8), 1002–1021. https://doi.org/10.1080/01443410.2020.1746237 Garn, A., & Shen, B. (2015). Physical self-concept and basic psychological needs in exercise: Are there reciprocal effects? ''International Journal of Sport and Exercise Psychology, 13''(2), 169–181. https://doi.org/10.1080/1612197X.2014.940994 Higgins, E. T. (1987). Self-discrepancy: A theory relating self and affect. ''Psychological Review, 94''(3), 319. Higgins, E. T. (1989). Self-discrepancy theory: What patterns of self-beliefs cause people to suffer?. In ''Advances in experimental social psychology'' (Vol. 22, pp. 93–136). Academic Press. Higgins, E. T., Shah, J., & Friedman, R. (1997). Emotional responses to goal attainment: Strength of regulatory focus as moderator. ''Journal of Personality and Social Psychology, 72''(3), 515–525. https://doi.org/10.1037/0022-3514.72.3.515 Hübner, N., Wagner, W., Zitzmann, S., & Nagengast, B. (2023). How strong is the evidence for a causal reciprocal effect? Contrasting traditional and new methods to investigate the reciprocal effects model of self-concept and achievement. ''Educational Psychology Review, 35'', 6. https://doi.org/10.1007/s10648-023-09724-6 James, W. (1892). The self. In W. James (Ed.), ''Psychology: Briefer course'' (pp. 176–216). Macmillan and Co. https://doi.org/10.1037/11630-012 Lietz, R., Whittaker, S., & Su, N. M. (2026). ‘It meant something about who I am’: What the lived experience of failure teaches us about designing for goal setting. ''Behaviour & Information Technology,'' 1–27. https://doi.org/10.1080/0144929X.2026.2711023 MacIntyre, P. D., & Vincze, L. (2017). Positive and negative emotions in motivation for second language learning. ''Studies in Second Language Learning and Teaching, 7''(1), 61–88. https://doi.org/10.14746/ssllt.2017.7.1.4 Marsh, H. W., Byrne, B. M., & Shavelson, R. J. (1992). A multidimensional, hierarchical self-concept. In T. M. Brinthaupt & R. P. Lipka (Eds.), ''The self: Definitional and methodological issues'' (pp. 44–95). State University of New York Press. Marsh, H. W., Martin, A. J., Yeung, A. S., & Craven, R. G. (2018). Chapter 6: Competence self-perceptions. In A. J. Elliot, C. S. Dweck, & D. S. Yeager (Eds.), ''Handbook of competence and motivation: Theory and application'' (pp. 85–115). Guilford Publications. Marsh, H. W., Seaton, M., Dicke, T., Parker, P. D., & Horwood, M. S. (2019). The centrality of academic self-concept to motivation and learning. In K. A. Renninger, & S. E. Hidi (Eds.), ''The Cambridge handbook of motivation and learning'' (pp. 36–62). Cambridge University Press. https://doi.org/10.1017/9781316823279.004 Mason, T. B., Smith, K. E., Engwall, A., Lass, A., Mead, M., Sorby, M., Bjorlie, K., Strauman, T. J., & Wonderlich, S. (2019). Self-discrepancy theory as a transdiagnostic framework: A meta-analysis of self-discrepancy and psychopathology. ''Psychological Bulletin, 145''(4), 372–389. https://doi.org/10.1037/bul0000186 Morris, L. S., Grehl, M. M., Rutter, S. B., Mehta, M., & Westwater, M. L. (2022). On what motivates us: A detailed review of intrinsic v. extrinsic motivation. ''Psychological Medicine, 52''(10), 1801–1816. https://doi.org/10.1017/S0033291722001611 Nurra, C., & Oyserman, D. (2018). From future self to current action: An identity-based motivation perspective. ''Self and Identity, 17''(3), 343-364. https://doi.org/10.1080/15298868.2017.1375003 Oyserman, D. (2015). Identity-based motivation. ''Emerging Trends in the Social and Behavioral Sciences, 38'', 1–11. https://doi.org/10.1002/9781118900772.etrds0171 Oyserman, D. (2024), Identity-based motivation and the motivational consequences of difficulty. ''Social and Personality Psychology Compass, 18'', e70028. https://doi.org/10.1111/spc3.70028 Ryan, R. M., & Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. ''Contemporary Educational Psychology, 61'', 101860. https://doi.org/10.1016/j.cedpsych.2020.101860 Ryan, R. M., & Deci, E. L. (2022). Self-determination theory. In F. Maggino (Ed.), ''Encyclopedia of quality of life and well-being research'' (pp. 1–7). Springer, Cham. https://doi.org/10.1007/978-3-319-69909-7_2630-2 Schwinger, M., Trautner, M., Pütz, N., Fabianek, S., Lemmer, G., Lauermann, F., & Wirthwein, L. (2022). Why do students use strategies that hurt their chances of academic success? A meta-analysis of antecedents of academic self-handicapping. ''Journal of Educational Psychology, 114''(3), 576–596. https://doi.org/10.1037/edu0000706 Seaton, M., Parker, P., Marsh, H. W., Craven, R. G., & Yeung, A. S. (2014). The reciprocal relations between self-concept, motivation and achievement: Juxtaposing academic self-concept and achievement goal orientations for mathematics success. ''Educational Psychology, 34''(1), 49–72. https://doi.org/10.1080/01443410.2013.825232 Sewasew, D., Schroeders, U., Schiefer, I. M., Weirich, S., & Artelt, C. (2018). Development of sex differences in math achievement, self-concept, and interest from grade 5 to 7. ''Contemporary Educational Psychology, 54'', 55–65. https://doi.org/10.1016/j.cedpsych.2018.05.003 Showers, C. J., Ditzfeld, C. P., & Zeigler-Hill, V. (2015). Self-concept structure and the quality of self-knowledge. ''Journal of Personality, 83''(5), 535-551. https://doi.org/10.1111/jopy.12130 Sorjonen, K., Ingre, M., Melin, B., & Nilsonne, G. (2024). Questioning the reciprocal effects model of academic self-concept and achievement: A reanalysis of a meta-analysis of longitudinal studies and a simulation. ''Sage Open, 14''(4). https://doi.org/10.1177/21582440241292826 Török, L., & Szabó, Z. P. (2018). The theory of self-handicapping: Forms, influencing factors and measurement. ''Ceskoslovenska Psychologie, 62''(2), 173-188. Wang, L., Cui, Y., Wang, X., Wang, J., Du, K., & Luo, Z. (2021). Regulatory focus, motivation, and their relationship with creativity among adolescents. ''Frontiers in Psychology, 12'', 666071. https://doi.org/10.3389/fpsyg.2021.666071 Wehrle, K., & Fasbender, U. (2018). Self-concept. In Zeigler-Hill, V., & Shackelford, T. (Eds.), ''Encyclopedia of personality and individual differences'' (pp. 1–5). Springer, Cham. https://doi.org/10.1007/978-3-319-28099-8_2001-1 Weiner, B. (1985). An attributional theory of achievement motivation and emotion. ''Psychological Review, 92''(4), 548–573. https://doi.org/10.1037/0033-295X.92.4.548 Yip, L., Thomas, E. F., Amiot, C., Louis, W. R., & McGarty, C. (2024). Autonomous motives foster sustained commitment to action: Integrating self-determination theory and the social identity approach. ''Personality and Social Psychology Bulletin, 50''(5), 750–765. https://doi.org/10.1177/01461672221148396 }} == External links == * [https://rickhanson.com/being-well-podcast-self-concept-the-secret-to-changing-who-you-are/ Being well podcast: Self-concept: The secret to changing WHO you are] (Being Well Podcast) * [https://www.youtube.com/watch?v=Nck7lP-6C2g Unlocking success: The power of self-efficacy and self-concept] (TEDx Talks) * [https://www.ted.com/talks/anil_ananthaswamy_where_does_your_sense_of_self_come_from_a_scientific_look Where does your sense of self come from? A scientific look] (TEDx Talks) [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Self-concept]] [[Category:Motivation and emotion/Book/2026]] [[Category:Motivation and emotion/Book/Motivation]] j4qlavgmix75amz672my40gwle5a348 2835269 2835268 2026-10-01T04:07:17Z U3253363 3106362 2835269 wikitext text/x-wiki {{title|Self-concept and motivation:<br>How does self-concept relate to motivation?}} == Overview == {{RoundBoxTop|theme=3}} [[File:Sinclair Swimming.JPG|right|thumb|180px|'''Figure 1'''. Ash is a competitive swimmer and swims daily.]] ;Scenario Ash is a swimmer training for a national competition. Being "a swimmer" is the first thing Ash thinks of when she’s asked to describe herself and she’s eager to succeed in the upcoming competition. Ash wakes up at 4:00 a.m. every morning to swim four kilometres (see Figure 1). Her friend Riley is always surprised by how Ash wakes up so early and swims so much. Why is Ash able to do this when many would find this a struggle? {{RoundBoxBottom}} [[Motivation and emotion/Book/2010/Self-concept|Self-concept]] is an individual's understanding of who they are and how they feel about themselves (Wehrle & Fasbender, 2018). This includes a complex system of attitudes, beliefs, and judgements about oneself. Self-concept guides people in answering the question “who am I?”. But its importance extends beyond that. Self-concept influences thinking, feelings, and behaviour. Consider self-concept an internal compass which motivates and guides how people navigate the world. This chapter explores how the understanding of oneself influences what people are motivated to do and examines how motivated behaviour can shape self-concepts. Understanding this reciprocal relationship can help people develop motivation around meaningful identities while reducing the risk that failure becomes a threat to personal worth. {{RoundBoxTop|theme=12}} '''Focus questions''' *What is self-concept? *How does self-concept influence motivation? *How does motivation shape self-concept?{{RoundBoxBottom}} == What is self-concept? == Self-concept is a cognitive framework containing a system of self-knowledge (Wehrle & Fasbender, 2018). It is related, but unique to many of the popular “self-” constructs such as [[self-esteem]], [[w:Self-efficacy|self-efficacy]], and [[w:Self-image|self-image]]. Although each self-concept-relevant theory approaches the construct differently, several common properties emerge and provide the foundation for understanding its motivational effects (see Table 1). [[wikipedia:William_James|James]] (1892) conceptualised the self as having two separate parts: “I”, the subjective thinker and “knower”, and “me”, the material, social and “known” self. Cooley's (1902) [[wikipedia:Looking-glass_self|looking-glass self theory]] later emphasised people as social beings, theorising that self-concept is a reflection of the responses and evaluations of others. Identity-based motivation theory (Oyserman, 2024) and the multidimensional model (Marsh et al., 1992) further develop that self-concept is multifaceted and dynamic, with different parts of the self influencing different behaviours. Together, these theories explain several mechanisms linking self-concept and motivation (see Table 1). '''Table 1''' ''Self-Concept Properties and Their Significance for Motivation'' {| class="wikitable" style="margin: auto;" !Property !Theory !Significance for motivation |- |'''Descriptive  ''' |James |Identity beliefs influence goals and expectations |- |'''Socially developed''' |The looking glass self, James |Social feedback influences which behaviours are pursued   |- |'''Dynamic''' |Multidimensional model, identity-based motivation theory |Self-concept changes situationally and with experience |- |'''Multidimensional''' |Multidimensional model |Different aspects of the self motivate different behaviours |- |'''Hierarchical  ''' |Multidimensional model |General and specific domains of the self influence each other and different behaviours |} == How does self-concept influence motivation? == Like self-concept, motivation is multidimensional, ubiquitous, and central to human behaviour (Bandhu et al., 2024). This creates an interesting intersection of properties; self-concept and motivation both influence which goals people pursue and responses to difficulty. This section explores how self-concept influences motivation.   === How the self directs and energises behaviour === Higgins' (1987) [[w:Self-discrepancy_theory|self-discrepancy theory]] proposes that people have three representations of the self: the actual (who one is), ideal (who one wants to become), and ought self (who one believes others want them to be; see Table 2). Ideal and ought selves set standards for one to strive toward, thus laying a framework for goal direction. Discrepancies between parts of the self cause emotional vulnerabilities which also generate motivation (see Table 2). Actual/ideal self-discrepancies result in dejection-related emotions (e.g. frustration, dissatisfaction; Higgins, 1987). Actual/ought self-discrepancies result in agitation-related emotions (e.g. anxiety, guilt). The greater the discrepancy, the greater the emotional discomfort and thus motivation to reduce the discrepancy (Higgins, 1989). Meta-analytic findings support that greater discrepancies result in more negative emotions (Mason et al., 2019). However, Mason et al. (2019) found that actual/ideal and actual/ought self-discrepancies both correlated with dejection- and agitation-related emotions, contrary to self-discrepancy theory's proposition. Further, while the negative emotions resulting from discrepancies are proposed to motivate people to change behaviour and reduce discrepancies, MacIntyre and Vincze (2017) suggest positive emotions have greater motivating strength than negative emotions. This suggests that while self-concepts provide frameworks for goal selection and energise behaviour, self-discrepancies may not be the most significant emotional sources of motivation. '''Table 2''' ''Dimensions of the Self and Emotional Effects of Discrepancies'' {| class="wikitable" !Self dimension !Examples !Emotional effect of discrepancy with actual self |- |Actual |Daily behaviours, beliefs | - |- |Ideal |Dreams, aspirations |Dejection-related emotions |- |Ought |Duties, obligations |Agitation-related emotions |}[[w:Regulatory_focus_theory|Regulatory focus theory]] (Higgins, 1997) expands self-discrepancy theory to suggest different self-representations produce different motivational orientations. Ideal-self goals create a promotion focus, whereby one is motivated to seek positive outcomes (see Table 3). Ought-self goals create a prevention focus, whereby one is motivated to avoid negative outcomes. These regulatory focuses both positively correlated with intrinsic motivation in Wang et al.'s (2021) study of adolescent task engagement. However, promotion focuses positively correlated with creativity and an innovative cognitive style, whereas prevention focuses negatively correlated with an innovative cognitive style and was characterised by error avoidance. This shows that while both promotion and prevention orientations generate self-sustained motivation, they result in different approaches to tasks. '''Table 3''' ''Self-concept's Motivational Mechanisms'' {| class="wikitable" |+ !Self-discrepancy !Motivational focus !Motivational mechanism !Task approach |- |Actual-ideal |Promotion |Seek positive outcomes |Creativity, innovation |- |Actual-ought |Prevention |Avoid negative outcomes |Reduced innovation, error avoidance |} Oyserman’s (2024) [[wikipedia:Identity_based_motivation|identity-based motivation theory]] provides an alternative explanation to how self-concept directs behaviour. The theory proposes that situations influence which aspects of self-concept are active. Active identities change interpretations of difficulty and thus influence motivation. When behaviour is congruent with one’s active identity, challenges in completing that behaviour are interpreted as evidence the behaviour is important (Oyserman, 2015). This is because identity-congruent behaviours provide information about who one is and who one wants to become, making difficulty meaningful rather than discouraging (Oyserman, 2024). Incongruent actions that have the same challenges are interpreted as pointless. Together, this means that identities mediate motivation and help goal selection through the process of difficulty interpretation (Oyserman, 2024). {{RoundBoxTop|theme=3}}'''Case study comprehension check''' Ash is finding her long training sessions for the upcoming swimming competition difficult. However, when she's training, her future-self-identity as an Olympic swimmer is active and helps her interpret this as a meaningful challenge. For her non-swimmer friend, Riley, these difficulties may be interpreted as evidence swimming is not for them.{{RoundBoxBottom}} Illustrating the motivating role of the self-concept within this framework, Nurra and Oyserman (2018) found that motivation to pursue future identity-relevant goals in school children, and subsequent achievement, was influenced by how children thought about their future selves. Students were exposed to prompts that helped them think of their adult self as either near or far. Students in the adult-self-is-near group achieved significantly higher final grades than the adult-self-is-far group. These findings indicate that closely identifying with one’s future self and viewing that future self as attainable can motivate goal attainment. Together, these results support identity-based motivation theory and detail that self-concept drives behaviour by defining desirable outcomes and shaping how challenges and opportunities are interpreted. Together, self-discrepancy, regulatory focus, and identity-based motivation theories suggest that a person's perceived distance from a valued self can create motivational pressure to change and active identities influence interpretations of challenges. These states modify goal engagement and motivation. In all three theories, self-concept is central to motivation, driving goal selection as well as goal engagement. Thus, what motivates each person, and how they subsequently behave, are shaped by their self-concept. === How self-concept can undermine motivation === The theories and research discussed so far optimistically show how self-concept facilitates motivation. However, self-concept can also undermine motivation through self-worth contingencies. [[wikipedia:Contingent_self-esteem#Self-esteem_and_contingent_self-worth|Self-worth contingencies]] refer to the standards one feels they must meet to have value as a person (Showers et al., 2015). For individuals who have highly contingent self-worth, goal attainment is closely tied to their self-concept, meaning failure threatens their self-concept. Contingent self-worth motivates pursuit of success for domains that are important for one's self-worth but can result in avoidant behaviour and strong responses to failure. {{RoundBoxTop|theme=11|title=Quiz}} <quiz display=simple> '''What are self-worth contingencies?''' |type="()"} - How you feel about yourself + Standards people feel they must meet to have value as a person - The ways people compare themselves to others </quiz>{{RoundBoxBottom}} Lietz et al. (2026) qualitatively studied 17 participants' identity-shaped goals and found that failing to achieve these goals resulted in negative and severe emotional responses. Further, participants tended to attribute failure to personal shortcomings, because of how closely held the goal was to their self-concept. This resulted in reduced motivation to reattempt, or blind pursuit of the same goal without re-examining the approach. This is consistent with [[Motivation and emotion/Book/2024/Attribution theory and emotion|attribution theory]] (Weiner, 1985), which suggests that causal thinking processes, whereby one attributes outcomes to stable, uncontrollable factors, result in low motivation. Attributional styles affect self-evaluations and thus can undermine motivation when failure is attributed to stable aspects of the self (Bandhu et al., 2024). This can cause maladaptive behaviours to emerge. One such response to the threat of failure is self-handicapping. [[w:Self-handicapping|Self-handicapping]] involves creating obstacles to one's own goal so that failure may not be self-attributed (Török & Szabó, 2018). A handicap generates a plausible external explanation for an outcome other than the self. This indicates that a handicapper is willing to increase the probability of failure to protect their self-concept, demonstrating that self-concept can impact motivation by hindering goal pursuit (Coudevylle et al., 2020). {{RoundBoxTop|theme=3}}'''Case study comprehension check''' Ash cares a lot about succeeding in her swimming competition. To protect her self-concept as a successful swimmer, Ash may feign a mild illness at the competition so that any failure is attributed to her illness, rather than her competence. {{RoundBoxBottom}} [[File:Multidimensional_model_of_self-concept_diagram.png|thumb|536x536px|'''Figure 2.''' The hierarchical multidimensional model of self-concept (Marsh et al., 2019).]] Illustrating the causes of self-handicapping, Schwinger et al. (2022) found a medium negative correlation between general self-evaluations and self-handicapping and a medium positive correlation between fear of failure and self-handicapping. With more negative general self-evaluations and greater fear of failure, people are more likely to self-handicap, highlighting self-concept as an precursor to self-handicapping. However, in this study, general, rather than domain-specific measures were used. According to the multidimensional model, self-concept is a hierarchical, multi-faceted construct, and more specific self-concepts are more closely related to actual behaviour (see Figure 2; Marsh et al., 2019). Accordingly, future research should investigate domain-specific measures of self-concept and fear of failure to illustrate their direct influence on self-handicapping and task motivation. Self-handicapping demonstrates that self-concept-driven motivation is not always directed towards achieving valued outcomes. Protecting self-worth can become more important than goal engagement. Together, this research suggests self-concept can act both as a motivational resource, and a motivational vulnerability. {{RoundBoxTop|theme=9}}'''Intervention application: Reduce self-threat''' Self-handicapping shows that holding success as a contingency for self-worth can be damaging (Showers et al., 2015). Thus, interventions should reduce how much self-worth depends on outcomes, by promoting self-compassion, diverse positive self-concept domains, self-concept flexibility, and growth-oriented interpretations of failure to improve both wellbeing and motivation.{{RoundBoxBottom}} == How does motivation shape self-concept? == The research and theories discussed so far have detailed how self-concept directs and motivates behaviour. The following section explores how, and whether, this relationship works in reverse.   === How internalising motivation shapes self-concept === [[File:Self-determination theory psychological needs.jpg|thumb|450x450px|'''Figure 3.''' Self-determination theory proposes that autonomy, competence, and relatedness support autonomous motivation (Ryan & Deci, 2020).]][[Self-determination theory]] (Ryan & Deci, 2020) proposes motivation exists on a continuum of self-determination, ranging from externally to increasingly internally regulated behaviour. The continuum consists of external, introjected, identified, integrated, and intrinsic regulation. These motivation types are influenced by three innate needs: competence, autonomy, and relatedness (see Figure 3; Ryan & Deci, 2020). Understanding the progression of these needs and motivation types can provide insight into how motivational processes influence self-concept. Intrinsic motivation refers to autonomous behaviours completed for enjoyment (see Table 4; Morris et al., 2022). Extrinsic motivation involves engaging in behaviour for an outcome separable from the activity itself (Morris et al., 2022). Its regulation ranges from externally controlled to personally valued and fully integrated. How self-determined one's motivations are depends on the extent to which one has internalised the values, beliefs and perceptions of the behaviour into their self-concept. Meeting the needs of competence, autonomy and relatedness supports motivations to become progressively internalised, and behaviour increasingly self-endorsed (Chiu, 2023). However, it should be noted that this process does not necessarily occur in a fixed sequence. This illustrates how self-concept and motivation reciprocally form one another. The degree to which one identifies with a behaviour shapes their motivation to engage with the behaviour; when needs are met, motivated behaviours and psychological processes shape the self-concept. This internalisation process helps explain how Ash came to identify as a swimmer (see Table 4).   '''Table 4''' ''Applying Self-Determination Theory to Ash's Motivation and Self-Concept Development'' {| class="wikitable" style="margin: auto;" !Type of motivation !Ash's circumstances   !Mechanism |- |External regulation |Ash received a lollipop after swimming lessons.   |Non-self-determined drive.   |- |Introjected regulation |Ash wants her parents to think she is dedicated to swimming. |Partially internalised extrinsic motivation, low self-determination.   |- |Identified regulation |Swimming becomes important to Ash as she starts feeling like a good swimmer (competence) and drives herself to training (autonomy).   |More internalised and self-determined. |- |Integrated regulation |Ash starts to identify as a swimmer and with her swim team (relatedness).   |Fully integrated into self-concept. Highly self-determined but performed for valued outcome not enjoyment. |- |Intrinsic motivation |After the swimming competition, Ash continues swimming for the joy of it.   |Fully integrated into self-concept. Fully autonomous motivation for enjoyment. |} Chiu (2023) provided compelling evidence for how motivation shapes self-concept within the context of self-determination theory. In their study, 342 Hong Kong high school students completed STEM activities taught using a standard teaching approach or a self-determination theory teaching method, focusing on supporting needs of autonomy, competence and relatedness (see Figure 3). Self-report measures reflected that the needs-supporting teaching approach increased students' feelings of autonomy, competence and relatedness; and, consequently, increased STEM identity and interest. This supports that fulfilling core psychological needs promotes more autonomous motivation and develops one's identity. Further supporting this relationship, Yip et al.'s (2024) longitudinal study of 236 anti-poverty activists who completed self-reported social attitudes and personality measures at two timepoints found that increases in self-determined motivations positively correlated with group identification. However, non-self-determined motivations, such as external regulation, did not correlate with group identification. This suggests that self-determined motivation facilitates the incorporation of behaviour and group membership into one's self-concept.   Together, self-determination theory suggests self-concepts develop as values and behaviours are progressively internalised. Ash was not initially motivated because she identified as a swimmer. Her repeated engagement in swimming and fulfilment of psychological needs gradually transformed swimming into part of her identity. This demonstrates that motivation can be a mechanism through which self-concept develops and is not simply a motivating force. {{RoundBoxTop|theme=11|title=Quiz}} <quiz display=simple> '''Which statement best reflects how motivation shapes self-concept?''' |type="()"} - People are only motivated to engage in behaviours that are part of their self-concept. - Self-concept does not change through motivational processes. + Repeated engagement with a behaviour and satisfaction of psychological needs gradually makes a behaviour part of one's self-concept. </quiz>{{RoundBoxBottom}} === The cyclical process of motivation and self-concept development === The reciprocal effects model proposes that self-concept and achievement reinforce one another over time (Marsh et al., 2018). People with stronger self-concepts tend to achieve more highly, while achievement experiences subsequently shape self-concept. Motivation plays an important role in this process, influencing how people behave toward achievement experiences. There is a growing body of research investigating this model. For example, Sewasew et al.'s (2018) longitudinal study with 2,342 German high schoolers demonstrated mathematics self-concept was positively correlated with mathematics achievement. Their study highlighted a mutually dependent relationship between academic self-concept and achievement, each mediated by motivation. However, Garn and Shen's (2015) longitudinal study of 329 participants' self-concept and motivation for exercise found that the psychological needs posited by self-determination theory (Ryan & Deci, 2022) did not predict physical self-concept at follow-ups. Physical self-concept was only shown to shape, rather than be shaped by exercise motivation. This result conflicts with the reciprocal effects model and Sewasew et al.'s (2018) results, which may be a reflection of the different self-concept domains examined, mathematics versus physical self-concept. This may indicate that reciprocal effects are domain specific; the multidimensional model suggests academic and physical self-concepts function independently, meaning findings from one domain may not generalise to another (Marsh et al., 2019). Thus, future research should directly compare the reciprocal relationship between self-concept and motivation within different domains. Similarly, Sorjonen et al. (2024) reanalysed meta-analytic results which had provided evidence for the reciprocal effects model. Sorjonen et al. (2024) found that conclusions about the longitudinal relationship between achievement and academic self-concept changed depending on the statistical model used. Hübner et al.'s (2023) support for the reciprocal effects model was also inconsistent between statistical models. This may indicate a spurious correlation that undermines the credibility of the reciprocal effects model. Taken together, these findings suggest that achievement can shape self-concept, but the strength and direction of this relationship may depend on the domain being examined and the methodological approach used. Although the reciprocal effects model remains influential, current evidence indicates that the relationship between motivation, achievement, and self-concept is more complex than originally proposed. == Conclusion == Self-concept is a multidimensional and socially developed framework of beliefs about oneself which acts as a guiding compass. Self-concept shapes motivation by determining which goals feel meaningful, attainable, and identity-consistent through processes of self-discrepancy, difficulty interpretation and self-worth contingencies. Self-discrepancy theory explains how distance from valued selves can create motivational pressure for change. Identity-based motivation theory explains how active identities change the meaning of difficulty. Whereas self-worth contingencies can undermine motivation. Together, these theories detail that self-concept influences goal direction and engagement through social, emotional and cognitive processes. These theories provide insight that motivation-improving interventions should consider targeting how people understand themselves rather than solely targeting behaviours. Motivation may also influence self-concept. Self-determination theory details that motivation and subsequent behaviours form self-concept through internalisation processes when psychological needs are met. However, inconsistent support for the reciprocal effects model indicates that the extent to which motivation reshapes self-concept may vary across domains and statistical models. {{RoundBoxTop|theme=3}} '''Take-home message''' With self-concept and motivation inherently linked, who people believe they are shapes the goals they pursue, while motivations, behaviours, and experiences continually reshape who people become. {{RoundBoxBottom}} {{RoundBoxTop|theme=11|title=Quiz}}<quiz display=simple> {'''Chapter comprehension check quiz:''' Ash wakes up at 4:00 a.m. each day to train because being a swimmer is a central part of her identity. According to the chapter, what best explains Ash's motivation? |type="()"} +Self-concept acts as an internal compass that guides goals and behaviour. -Motivation is caused only by external rewards and punishment. -Self-concept remains fixed and has little influence on actions. </quiz> {{RoundBoxBottom}} == See also == * [[wikipedia:Self-concept|Self-concept]] (Wikipedia) * [[Motivation and emotion/Book/2019/Self-concept clarity|Self-concept clarity]] (Book chapter, 2019) * [[Motivation and emotion/Book/2014/Self-efficacy and motivation|Self-efficacy and motivation]] (Book chapter, 2014) == References == {{Hanging indent|Bandhu, D., Mohan, M. M., Nittala, N. A. P., Jadhav, P., Bhadauria, A., & Saxena, K. K. (2024). Theories of motivation: A comprehensive analysis of human behavior drivers. ''Acta Psychologica, 244'', 104177. https://doi.org/10.1016/j.actpsy.2024.104177 Chiu, T.K. (2023). Using self-determination theory (SDT) to explain student STEM interest and identity development. ''Instructional Science, 52'', 89–107. https://doi.org/10.1007/s11251-023-09642-8 Cooley, C. H. (1902). The looking-glass self. ''The production of reality: Essays and readings on social interaction, 6''(1902), 126–28. Coudevylle, G. R., Boulley-Escriva, G., Finez, L., Eugène, K., & Robin, N. (2020). An experimental investigation of claimed self-handicapping strategies across motivational climates based on achievement goal and self-determination theories. ''Educational Psychology, 40''(8), 1002–1021. https://doi.org/10.1080/01443410.2020.1746237 Garn, A., & Shen, B. (2015). Physical self-concept and basic psychological needs in exercise: Are there reciprocal effects? ''International Journal of Sport and Exercise Psychology, 13''(2), 169–181. https://doi.org/10.1080/1612197X.2014.940994 Higgins, E. T. (1987). Self-discrepancy: A theory relating self and affect. ''Psychological Review, 94''(3), 319. Higgins, E. T. (1989). Self-discrepancy theory: What patterns of self-beliefs cause people to suffer?. In ''Advances in experimental social psychology'' (Vol. 22, pp. 93–136). Academic Press. Higgins, E. T., Shah, J., & Friedman, R. (1997). Emotional responses to goal attainment: Strength of regulatory focus as moderator. ''Journal of Personality and Social Psychology, 72''(3), 515–525. https://doi.org/10.1037/0022-3514.72.3.515 Hübner, N., Wagner, W., Zitzmann, S., & Nagengast, B. (2023). How strong is the evidence for a causal reciprocal effect? Contrasting traditional and new methods to investigate the reciprocal effects model of self-concept and achievement. ''Educational Psychology Review, 35'', 6. https://doi.org/10.1007/s10648-023-09724-6 James, W. (1892). The self. In W. James (Ed.), ''Psychology: Briefer course'' (pp. 176–216). Macmillan and Co. https://doi.org/10.1037/11630-012 Lietz, R., Whittaker, S., & Su, N. M. (2026). ‘It meant something about who I am’: What the lived experience of failure teaches us about designing for goal setting. ''Behaviour & Information Technology,'' 1–27. https://doi.org/10.1080/0144929X.2026.2711023 MacIntyre, P. D., & Vincze, L. (2017). Positive and negative emotions in motivation for second language learning. ''Studies in Second Language Learning and Teaching, 7''(1), 61–88. https://doi.org/10.14746/ssllt.2017.7.1.4 Marsh, H. W., Byrne, B. M., & Shavelson, R. J. (1992). A multidimensional, hierarchical self-concept. In T. M. Brinthaupt & R. P. Lipka (Eds.), ''The self: Definitional and methodological issues'' (pp. 44–95). State University of New York Press. Marsh, H. W., Martin, A. J., Yeung, A. S., & Craven, R. G. (2018). Chapter 6: Competence self-perceptions. In A. J. Elliot, C. S. Dweck, & D. S. Yeager (Eds.), ''Handbook of competence and motivation: Theory and application'' (pp. 85–115). Guilford Publications. Marsh, H. W., Seaton, M., Dicke, T., Parker, P. D., & Horwood, M. S. (2019). The centrality of academic self-concept to motivation and learning. In K. A. Renninger, & S. E. Hidi (Eds.), ''The Cambridge handbook of motivation and learning'' (pp. 36–62). Cambridge University Press. https://doi.org/10.1017/9781316823279.004 Mason, T. B., Smith, K. E., Engwall, A., Lass, A., Mead, M., Sorby, M., Bjorlie, K., Strauman, T. J., & Wonderlich, S. (2019). Self-discrepancy theory as a transdiagnostic framework: A meta-analysis of self-discrepancy and psychopathology. ''Psychological Bulletin, 145''(4), 372–389. https://doi.org/10.1037/bul0000186 Morris, L. S., Grehl, M. M., Rutter, S. B., Mehta, M., & Westwater, M. L. (2022). On what motivates us: A detailed review of intrinsic v. extrinsic motivation. ''Psychological Medicine, 52''(10), 1801–1816. https://doi.org/10.1017/S0033291722001611 Nurra, C., & Oyserman, D. (2018). From future self to current action: An identity-based motivation perspective. ''Self and Identity, 17''(3), 343-364. https://doi.org/10.1080/15298868.2017.1375003 Oyserman, D. (2015). Identity-based motivation. ''Emerging Trends in the Social and Behavioral Sciences, 38'', 1–11. https://doi.org/10.1002/9781118900772.etrds0171 Oyserman, D. (2024), Identity-based motivation and the motivational consequences of difficulty. ''Social and Personality Psychology Compass, 18'', e70028. https://doi.org/10.1111/spc3.70028 Ryan, R. M., & Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. ''Contemporary Educational Psychology, 61'', 101860. https://doi.org/10.1016/j.cedpsych.2020.101860 Ryan, R. M., & Deci, E. L. (2022). Self-determination theory. In F. Maggino (Ed.), ''Encyclopedia of quality of life and well-being research'' (pp. 1–7). Springer, Cham. https://doi.org/10.1007/978-3-319-69909-7_2630-2 Schwinger, M., Trautner, M., Pütz, N., Fabianek, S., Lemmer, G., Lauermann, F., & Wirthwein, L. (2022). Why do students use strategies that hurt their chances of academic success? A meta-analysis of antecedents of academic self-handicapping. ''Journal of Educational Psychology, 114''(3), 576–596. https://doi.org/10.1037/edu0000706 Seaton, M., Parker, P., Marsh, H. W., Craven, R. G., & Yeung, A. S. (2014). The reciprocal relations between self-concept, motivation and achievement: Juxtaposing academic self-concept and achievement goal orientations for mathematics success. ''Educational Psychology, 34''(1), 49–72. https://doi.org/10.1080/01443410.2013.825232 Sewasew, D., Schroeders, U., Schiefer, I. M., Weirich, S., & Artelt, C. (2018). Development of sex differences in math achievement, self-concept, and interest from grade 5 to 7. ''Contemporary Educational Psychology, 54'', 55–65. https://doi.org/10.1016/j.cedpsych.2018.05.003 Showers, C. J., Ditzfeld, C. P., & Zeigler-Hill, V. (2015). Self-concept structure and the quality of self-knowledge. ''Journal of Personality, 83''(5), 535-551. https://doi.org/10.1111/jopy.12130 Sorjonen, K., Ingre, M., Melin, B., & Nilsonne, G. (2024). Questioning the reciprocal effects model of academic self-concept and achievement: A reanalysis of a meta-analysis of longitudinal studies and a simulation. ''Sage Open, 14''(4). https://doi.org/10.1177/21582440241292826 Török, L., & Szabó, Z. P. (2018). The theory of self-handicapping: Forms, influencing factors and measurement. ''Ceskoslovenska Psychologie, 62''(2), 173-188. Wang, L., Cui, Y., Wang, X., Wang, J., Du, K., & Luo, Z. (2021). Regulatory focus, motivation, and their relationship with creativity among adolescents. ''Frontiers in Psychology, 12'', 666071. https://doi.org/10.3389/fpsyg.2021.666071 Wehrle, K., & Fasbender, U. (2018). Self-concept. In Zeigler-Hill, V., & Shackelford, T. (Eds.), ''Encyclopedia of personality and individual differences'' (pp. 1–5). Springer, Cham. https://doi.org/10.1007/978-3-319-28099-8_2001-1 Weiner, B. (1985). An attributional theory of achievement motivation and emotion. ''Psychological Review, 92''(4), 548–573. https://doi.org/10.1037/0033-295X.92.4.548 Yip, L., Thomas, E. F., Amiot, C., Louis, W. R., & McGarty, C. (2024). Autonomous motives foster sustained commitment to action: Integrating self-determination theory and the social identity approach. ''Personality and Social Psychology Bulletin, 50''(5), 750–765. https://doi.org/10.1177/01461672221148396 }} == External links == * [https://rickhanson.com/being-well-podcast-self-concept-the-secret-to-changing-who-you-are/ Being well podcast: Self-concept: The secret to changing WHO you are] (Being Well Podcast) * [https://www.youtube.com/watch?v=Nck7lP-6C2g Unlocking success: The power of self-efficacy and self-concept] (TEDx Talks) * [https://www.ted.com/talks/anil_ananthaswamy_where_does_your_sense_of_self_come_from_a_scientific_look Where does your sense of self come from? A scientific look] (TEDx Talks) [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Self-concept]] [[Category:Motivation and emotion/Book/2026]] [[Category:Motivation and emotion/Book/Motivation]] 37quen39dq1qqq552drfy3xjbfktw50 2835307 2835269 2026-10-01T09:38:08Z U3253363 3106362 /* What is self-concept? */ Copy editing. Checking for readability 2835307 wikitext text/x-wiki {{title|Self-concept and motivation:<br>How does self-concept relate to motivation?}} == Overview == {{RoundBoxTop|theme=3}} [[File:Sinclair Swimming.JPG|right|thumb|180px|'''Figure 1'''. Ash is a competitive swimmer and swims daily.]] ;Scenario Ash is a swimmer training for a national competition. Being "a swimmer" is the first thing Ash thinks of when she’s asked to describe herself and she’s eager to succeed in the upcoming competition. Ash wakes up at 4:00 a.m. every morning to swim four kilometres (see Figure 1). Her friend Riley is always surprised by how Ash wakes up so early and swims so much. Why is Ash able to do this when many would find this a struggle? {{RoundBoxBottom}} [[Motivation and emotion/Book/2010/Self-concept|Self-concept]] is an individual's understanding of who they are and how they feel about themselves (Wehrle & Fasbender, 2018). This includes a complex system of attitudes, beliefs, and judgements about oneself. Self-concept guides people in answering the question “who am I?”. But its importance extends beyond that. Self-concept influences thinking, feelings, and behaviour. Consider self-concept an internal compass which motivates and guides how people navigate the world. This chapter explores how the understanding of oneself influences what people are motivated to do and examines how motivated behaviour can shape self-concepts. Understanding this reciprocal relationship can help people develop motivation around meaningful identities while reducing the risk that failure becomes a threat to personal worth. {{RoundBoxTop|theme=12}} '''Focus questions''' *What is self-concept? *How does self-concept influence motivation? *How does motivation shape self-concept?{{RoundBoxBottom}} == What is self-concept? == Self-concept is a cognitive framework containing a system of self-knowledge (Wehrle & Fasbender, 2018). It is related, but unique to many of the popular “self-” constructs like [[self-esteem]], [[w:Self-efficacy|self-efficacy]], and [[w:Self-image|self-image]]. Although each self-concept-relevant theory approaches the construct differently, several common properties emerge and provide the foundation for understanding its motivational effects (see Table 1). [[wikipedia:William_James|James]] (1892) conceptualised the self as having two separate parts: “I”, the subjective thinker and “knower”, and “me”, the material, social, and “known” self. Cooley's (1902) [[wikipedia:Looking-glass_self|looking-glass self theory]] later emphasised people as social beings, theorising that self-concept is a reflection of other peoples' responses and evaluations. Identity-based motivation theory (Oyserman, 2024) and the multidimensional model (Marsh et al., 1992) further develop that self-concept is multifaceted and dynamic, with different parts of the self influencing different behaviours. Together, these theories explain several mechanisms linking self-concept and motivation (see Table 1). '''Table 1''' ''Self-Concept Properties and Their Significance for Motivation'' {| class="wikitable" style="margin: auto;" !Property !Theory !Significance for motivation |- |'''Descriptive  ''' |James |Identity beliefs influence goals and expectations |- |'''Socially developed''' |The looking glass self, James |Social feedback influences which behaviours are pursued |- |'''Dynamic''' |Multidimensional model, identity-based motivation theory |Self-concept changes situationally and with experience |- |'''Multidimensional''' |Multidimensional model |Different aspects of the self motivate different behaviours |- |'''Hierarchical  ''' |Multidimensional model |General and specific domains of the self influence each other and different behaviours |} == How does self-concept influence motivation? == Like self-concept, motivation is multidimensional and central to human behaviour (Bandhu et al., 2024). This creates an interesting intersection of properties; self-concept and motivation both influence which goals people pursue and responses to difficulty. This section explores how self-concept influences motivation.   === How the self directs and energises behaviour === Higgins' (1987) [[w:Self-discrepancy_theory|self-discrepancy theory]] proposes that people have three representations of the self: the actual (who one is), ideal (who one wants to become), and ought self (who one believes others want them to be; see Table 2). Ideal and ought selves set standards for one to strive toward, laying a framework for goal direction. Discrepancies between parts of the self cause emotional vulnerabilities which also generate motivation (Table 2). Actual/ideal self-discrepancies result in dejection-related emotions (e.g. frustration, dissatisfaction; Higgins, 1987). Actual/ought self-discrepancies result in agitation-related emotions (e.g. anxiety, guilt). The greater the discrepancy, the greater the emotional discomfort and thus motivation to reduce the discrepancy (Higgins, 1989). Meta-analytic findings support that greater discrepancies result in more negative emotions (Mason et al., 2019). However, Mason et al. (2019) found that actual/ideal and actual/ought self-discrepancies both correlated with dejection- and agitation-related emotions, contrary to self-discrepancy theory's proposition. Further, while the negative emotions resulting from discrepancies are proposed to motivate people to change behaviour and reduce discrepancies, MacIntyre and Vincze (2017) suggest positive emotions have greater motivating strength than negative emotions. This suggests that while self-concepts provide frameworks for goal selection and energise behaviour, self-discrepancies may not be the most significant emotional sources of motivation. '''Table 2''' ''Dimensions of the Self and Emotional Effects of Discrepancies'' {| class="wikitable" !Self dimension !Examples !Emotional effect of discrepancy with actual self |- |Actual |Daily behaviours, beliefs | - |- |Ideal |Dreams, aspirations |Dejection-related emotions |- |Ought |Duties, obligations |Agitation-related emotions |}[[w:Regulatory_focus_theory|Regulatory focus theory]] (Higgins, 1997) expands self-discrepancy theory to suggest different self-representations produce different motivational orientations. Ideal-self goals create a promotion focus, whereby one is motivated to seek positive outcomes (see Table 3). Ought-self goals create a prevention focus, whereby one is motivated to avoid negative outcomes. These regulatory focuses both positively correlated with intrinsic motivation in Wang et al.'s (2021) study of adolescent task engagement. However, promotion focuses positively correlated with creativity and an innovative cognitive style, whereas prevention focuses negatively correlated with an innovative cognitive style and was characterised by error avoidance. This shows that while both promotion and prevention orientations generate self-sustained motivation, they result in different approaches to tasks. '''Table 3''' ''Self-concept's Motivational Mechanisms'' {| class="wikitable" |+ !Self-discrepancy !Motivational focus !Motivational mechanism !Task approach |- |Actual-ideal |Promotion |Seek positive outcomes |Creativity, innovation |- |Actual-ought |Prevention |Avoid negative outcomes |Reduced innovation, error avoidance |} Oyserman’s (2024) [[wikipedia:Identity_based_motivation|identity-based motivation theory]] provides an alternative explanation to how self-concept directs behaviour. The theory proposes that situations influence which aspects of self-concept are active. Active identities change interpretations of difficulty and thus influence motivation. When behaviour is congruent with one’s active identity, challenges in completing that behaviour are interpreted as evidence the behaviour is important (Oyserman, 2015). This is because identity-congruent behaviours provide information about who one is and who one wants to become, making difficulty meaningful rather than discouraging (Oyserman, 2024). Incongruent actions that have the same challenges are interpreted as pointless. Together, this means that identities mediate motivation and help goal selection through the process of difficulty interpretation (Oyserman, 2024). {{RoundBoxTop|theme=3}}'''Case study comprehension check''' Ash is finding her long training sessions for the upcoming swimming competition difficult. However, when she's training, her future-self-identity as an Olympic swimmer is active and helps her interpret this as a meaningful challenge. For her non-swimmer friend, Riley, these difficulties may be interpreted as evidence swimming is not for them.{{RoundBoxBottom}} Illustrating the motivating role of the self-concept within this framework, Nurra and Oyserman (2018) found that motivation to pursue future identity-relevant goals in school children, and subsequent achievement, was influenced by how children thought about their future selves. Students were exposed to prompts that helped them think of their adult self as either near or far. Students in the adult-self-is-near group achieved significantly higher final grades than the adult-self-is-far group. These findings indicate that closely identifying with one’s future self and viewing that future self as attainable can motivate goal attainment. Together, these results support identity-based motivation theory and detail that self-concept drives behaviour by defining desirable outcomes and shaping how challenges and opportunities are interpreted. Together, self-discrepancy, regulatory focus, and identity-based motivation theories suggest that a person's perceived distance from a valued self can create motivational pressure to change and active identities influence interpretations of challenges. These states modify goal engagement and motivation. In all three theories, self-concept is central to motivation, driving goal selection as well as goal engagement. Thus, what motivates each person, and how they subsequently behave, are shaped by their self-concept. === How self-concept can undermine motivation === The theories and research discussed so far optimistically show how self-concept facilitates motivation. However, self-concept can also undermine motivation through self-worth contingencies. [[wikipedia:Contingent_self-esteem#Self-esteem_and_contingent_self-worth|Self-worth contingencies]] refer to the standards one feels they must meet to have value as a person (Showers et al., 2015). For individuals who have highly contingent self-worth, goal attainment is closely tied to their self-concept, meaning failure threatens their self-concept. Contingent self-worth motivates pursuit of success for domains that are important for one's self-worth but can result in avoidant behaviour and strong responses to failure. {{RoundBoxTop|theme=11|title=Quiz}} <quiz display=simple> '''What are self-worth contingencies?''' |type="()"} - How you feel about yourself + Standards people feel they must meet to have value as a person - The ways people compare themselves to others </quiz>{{RoundBoxBottom}} Lietz et al. (2026) qualitatively studied 17 participants' identity-shaped goals and found that failing to achieve these goals resulted in negative and severe emotional responses. Further, participants tended to attribute failure to personal shortcomings, because of how closely held the goal was to their self-concept. This resulted in reduced motivation to reattempt, or blind pursuit of the same goal without re-examining the approach. This is consistent with [[Motivation and emotion/Book/2024/Attribution theory and emotion|attribution theory]] (Weiner, 1985), which suggests that causal thinking processes, whereby one attributes outcomes to stable, uncontrollable factors, result in low motivation. Attributional styles affect self-evaluations and thus can undermine motivation when failure is attributed to stable aspects of the self (Bandhu et al., 2024). This can cause maladaptive behaviours to emerge. One such response to the threat of failure is self-handicapping. [[w:Self-handicapping|Self-handicapping]] involves creating obstacles to one's own goal so that failure may not be self-attributed (Török & Szabó, 2018). A handicap generates a plausible external explanation for an outcome other than the self. This indicates that a handicapper is willing to increase the probability of failure to protect their self-concept, demonstrating that self-concept can impact motivation by hindering goal pursuit (Coudevylle et al., 2020). {{RoundBoxTop|theme=3}}'''Case study comprehension check''' Ash cares a lot about succeeding in her swimming competition. To protect her self-concept as a successful swimmer, Ash may feign a mild illness at the competition so that any failure is attributed to her illness, rather than her competence. {{RoundBoxBottom}} [[File:Multidimensional_model_of_self-concept_diagram.png|thumb|536x536px|'''Figure 2.''' The hierarchical multidimensional model of self-concept (Marsh et al., 2019).]] Illustrating the causes of self-handicapping, Schwinger et al. (2022) found a medium negative correlation between general self-evaluations and self-handicapping and a medium positive correlation between fear of failure and self-handicapping. With more negative general self-evaluations and greater fear of failure, people are more likely to self-handicap, highlighting self-concept as an precursor to self-handicapping. However, in this study, general, rather than domain-specific measures were used. According to the multidimensional model, self-concept is a hierarchical, multi-faceted construct, and more specific self-concepts are more closely related to actual behaviour (see Figure 2; Marsh et al., 2019). Accordingly, future research should investigate domain-specific measures of self-concept and fear of failure to illustrate their direct influence on self-handicapping and task motivation. Self-handicapping demonstrates that self-concept-driven motivation is not always directed towards achieving valued outcomes. Protecting self-worth can become more important than goal engagement. Together, this research suggests self-concept can act both as a motivational resource, and a motivational vulnerability. {{RoundBoxTop|theme=9}}'''Intervention application: Reduce self-threat''' Self-handicapping shows that holding success as a contingency for self-worth can be damaging (Showers et al., 2015). Thus, interventions should reduce how much self-worth depends on outcomes, by promoting self-compassion, diverse positive self-concept domains, self-concept flexibility, and growth-oriented interpretations of failure to improve both wellbeing and motivation.{{RoundBoxBottom}} == How does motivation shape self-concept? == The research and theories discussed so far have detailed how self-concept directs and motivates behaviour. The following section explores how, and whether, this relationship works in reverse.   === How internalising motivation shapes self-concept === [[File:Self-determination theory psychological needs.jpg|thumb|450x450px|'''Figure 3.''' Self-determination theory proposes that autonomy, competence, and relatedness support autonomous motivation (Ryan & Deci, 2020).]][[Self-determination theory]] (Ryan & Deci, 2020) proposes motivation exists on a continuum of self-determination, ranging from externally to increasingly internally regulated behaviour. The continuum consists of external, introjected, identified, integrated, and intrinsic regulation. These motivation types are influenced by three innate needs: competence, autonomy, and relatedness (see Figure 3; Ryan & Deci, 2020). Understanding the progression of these needs and motivation types can provide insight into how motivational processes influence self-concept. Intrinsic motivation refers to autonomous behaviours completed for enjoyment (see Table 4; Morris et al., 2022). Extrinsic motivation involves engaging in behaviour for an outcome separable from the activity itself (Morris et al., 2022). Its regulation ranges from externally controlled to personally valued and fully integrated. How self-determined one's motivations are depends on the extent to which one has internalised the values, beliefs and perceptions of the behaviour into their self-concept. Meeting the needs of competence, autonomy and relatedness supports motivations to become progressively internalised, and behaviour increasingly self-endorsed (Chiu, 2023). However, it should be noted that this process does not necessarily occur in a fixed sequence. This illustrates how self-concept and motivation reciprocally form one another. The degree to which one identifies with a behaviour shapes their motivation to engage with the behaviour; when needs are met, motivated behaviours and psychological processes shape the self-concept. This internalisation process helps explain how Ash came to identify as a swimmer (see Table 4).   '''Table 4''' ''Applying Self-Determination Theory to Ash's Motivation and Self-Concept Development'' {| class="wikitable" style="margin: auto;" !Type of motivation !Ash's circumstances   !Mechanism |- |External regulation |Ash received a lollipop after swimming lessons.   |Non-self-determined drive.   |- |Introjected regulation |Ash wants her parents to think she is dedicated to swimming. |Partially internalised extrinsic motivation, low self-determination.   |- |Identified regulation |Swimming becomes important to Ash as she starts feeling like a good swimmer (competence) and drives herself to training (autonomy).   |More internalised and self-determined. |- |Integrated regulation |Ash starts to identify as a swimmer and with her swim team (relatedness).   |Fully integrated into self-concept. Highly self-determined but performed for valued outcome not enjoyment. |- |Intrinsic motivation |After the swimming competition, Ash continues swimming for the joy of it.   |Fully integrated into self-concept. Fully autonomous motivation for enjoyment. |} Chiu (2023) provided compelling evidence for how motivation shapes self-concept within the context of self-determination theory. In their study, 342 Hong Kong high school students completed STEM activities taught using a standard teaching approach or a self-determination theory teaching method, focusing on supporting needs of autonomy, competence and relatedness (see Figure 3). Self-report measures reflected that the needs-supporting teaching approach increased students' feelings of autonomy, competence and relatedness; and, consequently, increased STEM identity and interest. This supports that fulfilling core psychological needs promotes more autonomous motivation and develops one's identity. Further supporting this relationship, Yip et al.'s (2024) longitudinal study of 236 anti-poverty activists who completed self-reported social attitudes and personality measures at two timepoints found that increases in self-determined motivations positively correlated with group identification. However, non-self-determined motivations, such as external regulation, did not correlate with group identification. This suggests that self-determined motivation facilitates the incorporation of behaviour and group membership into one's self-concept.   Together, self-determination theory suggests self-concepts develop as values and behaviours are progressively internalised. Ash was not initially motivated because she identified as a swimmer. Her repeated engagement in swimming and fulfilment of psychological needs gradually transformed swimming into part of her identity. This demonstrates that motivation can be a mechanism through which self-concept develops and is not simply a motivating force. {{RoundBoxTop|theme=11|title=Quiz}} <quiz display=simple> '''Which statement best reflects how motivation shapes self-concept?''' |type="()"} - People are only motivated to engage in behaviours that are part of their self-concept. - Self-concept does not change through motivational processes. + Repeated engagement with a behaviour and satisfaction of psychological needs gradually makes a behaviour part of one's self-concept. </quiz>{{RoundBoxBottom}} === The cyclical process of motivation and self-concept development === The reciprocal effects model proposes that self-concept and achievement reinforce one another over time (Marsh et al., 2018). People with stronger self-concepts tend to achieve more highly, while achievement experiences subsequently shape self-concept. Motivation plays an important role in this process, influencing how people behave toward achievement experiences. There is a growing body of research investigating this model. For example, Sewasew et al.'s (2018) longitudinal study with 2,342 German high schoolers demonstrated mathematics self-concept was positively correlated with mathematics achievement. Their study highlighted a mutually dependent relationship between academic self-concept and achievement, each mediated by motivation. However, Garn and Shen's (2015) longitudinal study of 329 participants' self-concept and motivation for exercise found that the psychological needs posited by self-determination theory (Ryan & Deci, 2022) did not predict physical self-concept at follow-ups. Physical self-concept was only shown to shape, rather than be shaped by exercise motivation. This result conflicts with the reciprocal effects model and Sewasew et al.'s (2018) results, which may be a reflection of the different self-concept domains examined, mathematics versus physical self-concept. This may indicate that reciprocal effects are domain specific; the multidimensional model suggests academic and physical self-concepts function independently, meaning findings from one domain may not generalise to another (Marsh et al., 2019). Thus, future research should directly compare the reciprocal relationship between self-concept and motivation within different domains. Similarly, Sorjonen et al. (2024) reanalysed meta-analytic results which had provided evidence for the reciprocal effects model. Sorjonen et al. (2024) found that conclusions about the longitudinal relationship between achievement and academic self-concept changed depending on the statistical model used. Hübner et al.'s (2023) support for the reciprocal effects model was also inconsistent between statistical models. This may indicate a spurious correlation that undermines the credibility of the reciprocal effects model. Taken together, these findings suggest that achievement can shape self-concept, but the strength and direction of this relationship may depend on the domain being examined and the methodological approach used. Although the reciprocal effects model remains influential, current evidence indicates that the relationship between motivation, achievement, and self-concept is more complex than originally proposed. == Conclusion == Self-concept is a multidimensional and socially developed framework of beliefs about oneself which acts as a guiding compass. Self-concept shapes motivation by determining which goals feel meaningful, attainable, and identity-consistent through processes of self-discrepancy, difficulty interpretation and self-worth contingencies. Self-discrepancy theory explains how distance from valued selves can create motivational pressure for change. Identity-based motivation theory explains how active identities change the meaning of difficulty. Whereas self-worth contingencies can undermine motivation. Together, these theories detail that self-concept influences goal direction and engagement through social, emotional and cognitive processes. These theories provide insight that motivation-improving interventions should consider targeting how people understand themselves rather than solely targeting behaviours. Motivation may also influence self-concept. Self-determination theory details that motivation and subsequent behaviours form self-concept through internalisation processes when psychological needs are met. However, inconsistent support for the reciprocal effects model indicates that the extent to which motivation reshapes self-concept may vary across domains and statistical models. {{RoundBoxTop|theme=3}} '''Take-home message''' With self-concept and motivation inherently linked, who people believe they are shapes the goals they pursue, while motivations, behaviours, and experiences continually reshape who people become. {{RoundBoxBottom}} {{RoundBoxTop|theme=11|title=Quiz}}<quiz display=simple> {'''Chapter comprehension check quiz:''' Ash wakes up at 4:00 a.m. each day to train because being a swimmer is a central part of her identity. According to the chapter, what best explains Ash's motivation? |type="()"} +Self-concept acts as an internal compass that guides goals and behaviour. -Motivation is caused only by external rewards and punishment. -Self-concept remains fixed and has little influence on actions. </quiz> {{RoundBoxBottom}} == See also == * [[wikipedia:Self-concept|Self-concept]] (Wikipedia) * [[Motivation and emotion/Book/2019/Self-concept clarity|Self-concept clarity]] (Book chapter, 2019) * [[Motivation and emotion/Book/2014/Self-efficacy and motivation|Self-efficacy and motivation]] (Book chapter, 2014) == References == {{Hanging indent|Bandhu, D., Mohan, M. M., Nittala, N. A. P., Jadhav, P., Bhadauria, A., & Saxena, K. K. (2024). Theories of motivation: A comprehensive analysis of human behavior drivers. ''Acta Psychologica, 244'', 104177. https://doi.org/10.1016/j.actpsy.2024.104177 Chiu, T.K. (2023). Using self-determination theory (SDT) to explain student STEM interest and identity development. ''Instructional Science, 52'', 89–107. https://doi.org/10.1007/s11251-023-09642-8 Cooley, C. H. (1902). The looking-glass self. ''The production of reality: Essays and readings on social interaction, 6''(1902), 126–28. Coudevylle, G. R., Boulley-Escriva, G., Finez, L., Eugène, K., & Robin, N. (2020). An experimental investigation of claimed self-handicapping strategies across motivational climates based on achievement goal and self-determination theories. ''Educational Psychology, 40''(8), 1002–1021. https://doi.org/10.1080/01443410.2020.1746237 Garn, A., & Shen, B. (2015). Physical self-concept and basic psychological needs in exercise: Are there reciprocal effects? ''International Journal of Sport and Exercise Psychology, 13''(2), 169–181. https://doi.org/10.1080/1612197X.2014.940994 Higgins, E. T. (1987). Self-discrepancy: A theory relating self and affect. ''Psychological Review, 94''(3), 319. Higgins, E. T. (1989). Self-discrepancy theory: What patterns of self-beliefs cause people to suffer?. In ''Advances in experimental social psychology'' (Vol. 22, pp. 93–136). Academic Press. Higgins, E. T., Shah, J., & Friedman, R. (1997). Emotional responses to goal attainment: Strength of regulatory focus as moderator. ''Journal of Personality and Social Psychology, 72''(3), 515–525. https://doi.org/10.1037/0022-3514.72.3.515 Hübner, N., Wagner, W., Zitzmann, S., & Nagengast, B. (2023). How strong is the evidence for a causal reciprocal effect? Contrasting traditional and new methods to investigate the reciprocal effects model of self-concept and achievement. ''Educational Psychology Review, 35'', 6. https://doi.org/10.1007/s10648-023-09724-6 James, W. (1892). The self. In W. James (Ed.), ''Psychology: Briefer course'' (pp. 176–216). Macmillan and Co. https://doi.org/10.1037/11630-012 Lietz, R., Whittaker, S., & Su, N. M. (2026). ‘It meant something about who I am’: What the lived experience of failure teaches us about designing for goal setting. ''Behaviour & Information Technology,'' 1–27. https://doi.org/10.1080/0144929X.2026.2711023 MacIntyre, P. D., & Vincze, L. (2017). Positive and negative emotions in motivation for second language learning. ''Studies in Second Language Learning and Teaching, 7''(1), 61–88. https://doi.org/10.14746/ssllt.2017.7.1.4 Marsh, H. W., Byrne, B. M., & Shavelson, R. J. (1992). A multidimensional, hierarchical self-concept. In T. M. Brinthaupt & R. P. Lipka (Eds.), ''The self: Definitional and methodological issues'' (pp. 44–95). State University of New York Press. Marsh, H. W., Martin, A. J., Yeung, A. S., & Craven, R. G. (2018). Chapter 6: Competence self-perceptions. In A. J. Elliot, C. S. Dweck, & D. S. Yeager (Eds.), ''Handbook of competence and motivation: Theory and application'' (pp. 85–115). Guilford Publications. Marsh, H. W., Seaton, M., Dicke, T., Parker, P. D., & Horwood, M. S. (2019). The centrality of academic self-concept to motivation and learning. In K. A. Renninger, & S. E. Hidi (Eds.), ''The Cambridge handbook of motivation and learning'' (pp. 36–62). Cambridge University Press. https://doi.org/10.1017/9781316823279.004 Mason, T. B., Smith, K. E., Engwall, A., Lass, A., Mead, M., Sorby, M., Bjorlie, K., Strauman, T. J., & Wonderlich, S. (2019). Self-discrepancy theory as a transdiagnostic framework: A meta-analysis of self-discrepancy and psychopathology. ''Psychological Bulletin, 145''(4), 372–389. https://doi.org/10.1037/bul0000186 Morris, L. S., Grehl, M. M., Rutter, S. B., Mehta, M., & Westwater, M. L. (2022). On what motivates us: A detailed review of intrinsic v. extrinsic motivation. ''Psychological Medicine, 52''(10), 1801–1816. https://doi.org/10.1017/S0033291722001611 Nurra, C., & Oyserman, D. (2018). From future self to current action: An identity-based motivation perspective. ''Self and Identity, 17''(3), 343-364. https://doi.org/10.1080/15298868.2017.1375003 Oyserman, D. (2015). Identity-based motivation. ''Emerging Trends in the Social and Behavioral Sciences, 38'', 1–11. https://doi.org/10.1002/9781118900772.etrds0171 Oyserman, D. (2024), Identity-based motivation and the motivational consequences of difficulty. ''Social and Personality Psychology Compass, 18'', e70028. https://doi.org/10.1111/spc3.70028 Ryan, R. M., & Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. ''Contemporary Educational Psychology, 61'', 101860. https://doi.org/10.1016/j.cedpsych.2020.101860 Ryan, R. M., & Deci, E. L. (2022). Self-determination theory. In F. Maggino (Ed.), ''Encyclopedia of quality of life and well-being research'' (pp. 1–7). Springer, Cham. https://doi.org/10.1007/978-3-319-69909-7_2630-2 Schwinger, M., Trautner, M., Pütz, N., Fabianek, S., Lemmer, G., Lauermann, F., & Wirthwein, L. (2022). Why do students use strategies that hurt their chances of academic success? A meta-analysis of antecedents of academic self-handicapping. ''Journal of Educational Psychology, 114''(3), 576–596. https://doi.org/10.1037/edu0000706 Seaton, M., Parker, P., Marsh, H. W., Craven, R. G., & Yeung, A. S. (2014). The reciprocal relations between self-concept, motivation and achievement: Juxtaposing academic self-concept and achievement goal orientations for mathematics success. ''Educational Psychology, 34''(1), 49–72. https://doi.org/10.1080/01443410.2013.825232 Sewasew, D., Schroeders, U., Schiefer, I. M., Weirich, S., & Artelt, C. (2018). Development of sex differences in math achievement, self-concept, and interest from grade 5 to 7. ''Contemporary Educational Psychology, 54'', 55–65. https://doi.org/10.1016/j.cedpsych.2018.05.003 Showers, C. J., Ditzfeld, C. P., & Zeigler-Hill, V. (2015). Self-concept structure and the quality of self-knowledge. ''Journal of Personality, 83''(5), 535-551. https://doi.org/10.1111/jopy.12130 Sorjonen, K., Ingre, M., Melin, B., & Nilsonne, G. (2024). Questioning the reciprocal effects model of academic self-concept and achievement: A reanalysis of a meta-analysis of longitudinal studies and a simulation. ''Sage Open, 14''(4). https://doi.org/10.1177/21582440241292826 Török, L., & Szabó, Z. P. (2018). The theory of self-handicapping: Forms, influencing factors and measurement. ''Ceskoslovenska Psychologie, 62''(2), 173-188. Wang, L., Cui, Y., Wang, X., Wang, J., Du, K., & Luo, Z. (2021). Regulatory focus, motivation, and their relationship with creativity among adolescents. ''Frontiers in Psychology, 12'', 666071. https://doi.org/10.3389/fpsyg.2021.666071 Wehrle, K., & Fasbender, U. (2018). Self-concept. In Zeigler-Hill, V., & Shackelford, T. (Eds.), ''Encyclopedia of personality and individual differences'' (pp. 1–5). Springer, Cham. https://doi.org/10.1007/978-3-319-28099-8_2001-1 Weiner, B. (1985). An attributional theory of achievement motivation and emotion. ''Psychological Review, 92''(4), 548–573. https://doi.org/10.1037/0033-295X.92.4.548 Yip, L., Thomas, E. F., Amiot, C., Louis, W. R., & McGarty, C. (2024). Autonomous motives foster sustained commitment to action: Integrating self-determination theory and the social identity approach. ''Personality and Social Psychology Bulletin, 50''(5), 750–765. https://doi.org/10.1177/01461672221148396 }} == External links == * [https://rickhanson.com/being-well-podcast-self-concept-the-secret-to-changing-who-you-are/ Being well podcast: Self-concept: The secret to changing WHO you are] (Being Well Podcast) * [https://www.youtube.com/watch?v=Nck7lP-6C2g Unlocking success: The power of self-efficacy and self-concept] (TEDx Talks) * [https://www.ted.com/talks/anil_ananthaswamy_where_does_your_sense_of_self_come_from_a_scientific_look Where does your sense of self come from? A scientific look] (TEDx Talks) [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Self-concept]] [[Category:Motivation and emotion/Book/2026]] [[Category:Motivation and emotion/Book/Motivation]] 0zmc7q6lpwwis9e4tpde5kxvf4sk8gl 2835330 2835307 2026-10-01T10:40:34Z U3253363 3106362 /* How self-concept can undermine motivation */ trying to reduce word count 2835330 wikitext text/x-wiki {{title|Self-concept and motivation:<br>How does self-concept relate to motivation?}} == Overview == {{RoundBoxTop|theme=3}} [[File:Sinclair Swimming.JPG|right|thumb|180px|'''Figure 1'''. Ash is a competitive swimmer and swims daily.]] ;Scenario Ash is a swimmer training for a national competition. Being "a swimmer" is the first thing Ash thinks of when she’s asked to describe herself and she’s eager to succeed in the upcoming competition. Ash wakes up at 4:00 a.m. every morning to swim four kilometres (see Figure 1). Her friend Riley is always surprised by how Ash wakes up so early and swims so much. Why is Ash able to do this when many would find this a struggle? {{RoundBoxBottom}} [[Motivation and emotion/Book/2010/Self-concept|Self-concept]] is an individual's understanding of who they are and how they feel about themselves (Wehrle & Fasbender, 2018). This includes a complex system of attitudes, beliefs, and judgements about oneself. Self-concept guides people in answering the question “who am I?”. But its importance extends beyond that. Self-concept influences thinking, feelings, and behaviour. Consider self-concept an internal compass which motivates and guides how people navigate the world. This chapter explores how the understanding of oneself influences what people are motivated to do and examines how motivated behaviour can shape self-concepts. Understanding this reciprocal relationship can help people develop motivation around meaningful identities while reducing the risk that failure becomes a threat to personal worth. {{RoundBoxTop|theme=12}} '''Focus questions''' *What is self-concept? *How does self-concept influence motivation? *How does motivation shape self-concept?{{RoundBoxBottom}} == What is self-concept? == Self-concept is a cognitive framework containing a system of self-knowledge (Wehrle & Fasbender, 2018). It is related, but unique to many of the popular “self-” constructs like [[self-esteem]], [[w:Self-efficacy|self-efficacy]], and [[w:Self-image|self-image]]. Although each self-concept-relevant theory approaches the construct differently, several common properties emerge and provide the foundation for understanding its motivational effects (see Table 1). [[wikipedia:William_James|James]] (1892) conceptualised the self as having two separate parts: “I”, the subjective thinker and “knower”, and “me”, the material, social, and “known” self. Cooley's (1902) [[wikipedia:Looking-glass_self|looking-glass self theory]] later emphasised people as social beings, theorising that self-concept is a reflection of other peoples' responses and evaluations. Identity-based motivation theory (Oyserman, 2024) and the multidimensional model (Marsh et al., 1992) further develop that self-concept is multifaceted and dynamic, with different parts of the self influencing different behaviours. Together, these theories explain several mechanisms linking self-concept and motivation (see Table 1). '''Table 1''' ''Self-Concept Properties and Their Significance for Motivation'' {| class="wikitable" style="margin: auto;" !Property !Theory !Significance for motivation |- |'''Descriptive  ''' |James |Identity beliefs influence goals and expectations |- |'''Socially developed''' |The looking glass self, James |Social feedback influences which behaviours are pursued |- |'''Dynamic''' |Multidimensional model, identity-based motivation theory |Self-concept changes situationally and with experience |- |'''Multidimensional''' |Multidimensional model |Different aspects of the self motivate different behaviours |- |'''Hierarchical  ''' |Multidimensional model |General and specific domains of the self influence each other and different behaviours |} == How does self-concept influence motivation? == Like self-concept, motivation is multidimensional and central to human behaviour (Bandhu et al., 2024). This creates an interesting intersection of properties; self-concept and motivation both influence which goals people pursue and responses to difficulty. This section explores how self-concept influences motivation.   === How the self directs and energises behaviour === Higgins' (1987) [[w:Self-discrepancy_theory|self-discrepancy theory]] proposes that people have three representations of the self: the actual (who one is), ideal (who one wants to become), and ought self (who one believes others want them to be; see Table 2). Ideal and ought selves set standards for one to strive toward, laying a framework for goal direction. Discrepancies between parts of the self cause emotional vulnerabilities which also generate motivation (Table 2). Actual/ideal self-discrepancies result in dejection-related emotions (e.g. frustration, dissatisfaction; Higgins, 1987). Actual/ought self-discrepancies result in agitation-related emotions (e.g. anxiety, guilt). The greater the discrepancy, the greater the emotional discomfort and thus motivation to reduce the discrepancy (Higgins, 1989). Meta-analytic findings support that greater discrepancies result in more negative emotions (Mason et al., 2019). However, Mason et al. (2019) found that actual/ideal and actual/ought self-discrepancies both correlated with dejection- and agitation-related emotions, contrary to self-discrepancy theory's proposition. Further, while the negative emotions resulting from discrepancies are proposed to motivate people to change behaviour and reduce discrepancies, MacIntyre and Vincze (2017) suggest positive emotions have greater motivating strength than negative emotions. This suggests that while self-concepts provide frameworks for goal selection and energise behaviour, self-discrepancies may not be the most significant emotional sources of motivation. '''Table 2''' ''Dimensions of the Self and Emotional Effects of Discrepancies'' {| class="wikitable" !Self dimension !Examples !Emotional effect of discrepancy with actual self |- |Actual |Daily behaviours, beliefs | - |- |Ideal |Dreams, aspirations |Dejection-related emotions |- |Ought |Duties, obligations |Agitation-related emotions |}[[w:Regulatory_focus_theory|Regulatory focus theory]] (Higgins, 1997) expands self-discrepancy theory to suggest different self-representations produce different motivational orientations. Ideal-self goals create a promotion focus, whereby one is motivated to seek positive outcomes (see Table 3). Ought-self goals create a prevention focus, whereby one is motivated to avoid negative outcomes. These regulatory focuses both positively correlated with intrinsic motivation in Wang et al.'s (2021) study of adolescent task engagement. However, promotion focuses positively correlated with creativity and an innovative cognitive style, whereas prevention focuses negatively correlated with an innovative cognitive style and was characterised by error avoidance. This shows that while both promotion and prevention orientations generate self-sustained motivation, they result in different approaches to tasks. '''Table 3''' ''Self-concept's Motivational Mechanisms'' {| class="wikitable" |+ !Self-discrepancy !Motivational focus !Motivational mechanism !Task approach |- |Actual-ideal |Promotion |Seek positive outcomes |Creativity, innovation |- |Actual-ought |Prevention |Avoid negative outcomes |Reduced innovation, error avoidance |} Oyserman’s (2024) [[wikipedia:Identity_based_motivation|identity-based motivation theory]] provides an alternative explanation to how self-concept directs behaviour. The theory proposes that situations influence which aspects of self-concept are active. Active identities change interpretations of difficulty and thus influence motivation. When behaviour is congruent with one’s active identity, challenges in completing that behaviour are interpreted as evidence the behaviour is important (Oyserman, 2015). This is because identity-congruent behaviours provide information about who one is and who one wants to become, making difficulty meaningful rather than discouraging (Oyserman, 2024). Incongruent actions that have the same challenges are interpreted as pointless. Together, this means that identities mediate motivation and help goal selection through the process of difficulty interpretation (Oyserman, 2024). {{RoundBoxTop|theme=3}}'''Case study comprehension check''' Ash is finding her long training sessions for the upcoming swimming competition difficult. However, when she's training, her future-self-identity as an Olympic swimmer is active and helps her interpret this as a meaningful challenge. For her non-swimmer friend, Riley, these difficulties may be interpreted as evidence swimming is not for them.{{RoundBoxBottom}} Illustrating the motivating role of the self-concept within this framework, Nurra and Oyserman (2018) found that motivation to pursue future identity-relevant goals in school children, and subsequent achievement, was influenced by how children thought about their future selves. Students were exposed to prompts that helped them think of their adult self as either near or far. Students in the adult-self-is-near group achieved significantly higher final grades than the adult-self-is-far group. These findings indicate that closely identifying with one’s future self and viewing that future self as attainable can motivate goal attainment. Together, these results support identity-based motivation theory and detail that self-concept drives behaviour by defining desirable outcomes and shaping how challenges and opportunities are interpreted. Together, self-discrepancy, regulatory focus, and identity-based motivation theories suggest that a person's perceived distance from a valued self can create motivational pressure to change and active identities influence interpretations of challenges. These states modify goal engagement and motivation. In all three theories, self-concept is central to motivation, driving goal selection as well as goal engagement. Thus, what motivates each person, and how they subsequently behave, are shaped by their self-concept. === How self-concept can undermine motivation === The theories and research discussed so far optimistically show how self-concept facilitates motivation. However, self-concept can also undermine motivation through self-worth contingencies. [[wikipedia:Contingent_self-esteem#Self-esteem_and_contingent_self-worth|Self-worth contingencies]] refer to the standards one feels they must meet to have value as a person (Showers et al., 2015). For individuals who have highly contingent self-worth, goal attainment is closely tied to their self-concept, meaning failure threatens their self-concept. Contingent self-worth motivates pursuit of success for domains that are important for one's self-worth but can result in avoidant behaviour and strong responses to failure. {{RoundBoxTop|theme=11|title=Quiz}} <quiz display=simple> '''What are self-worth contingencies?''' |type="()"} - How people feel about themselves + Standards people feel they must meet to have value - How people compare themselves to others </quiz>{{RoundBoxBottom}} Lietz et al. (2026) qualitatively studied 17 participants' identity-shaped goals and found that failing to achieve these goals resulted in negative and severe emotional responses. Further, participants tended to attribute failure to personal shortcomings, because of how closely held the goal was to their self-concept. This resulted in reduced motivation to reattempt, or blind pursuit of the same goal without re-examining the approach. This is consistent with [[Motivation and emotion/Book/2024/Attribution theory and emotion|attribution theory]] (Weiner, 1985), which suggests that causal thinking processes, whereby one attributes outcomes to stable, uncontrollable factors, result in low motivation. Attributional styles affect self-evaluations and thus can undermine motivation when failure is attributed to stable aspects of the self (Bandhu et al., 2024). This can cause maladaptive behaviours to emerge. One such response to the threat of failure is self-handicapping. [[w:Self-handicapping|Self-handicapping]] involves creating obstacles to one's own goal so that failure cannot be self-attributed (Török & Szabó, 2018). A handicap acts as a plausible external explanation for an outcome other than the self. This means that a handicapper is willing to increase the probability of failure to protect their self-concept (Coudevylle et al., 2020). Therefore, self-concept can impact motivation by hindering goal pursuit. {{RoundBoxTop|theme=3}}'''Case study comprehension check''' Ash cares a lot about succeeding in her swimming competition. To protect her self-concept as a successful swimmer, Ash may feign a mild illness at the competition so that any failure is attributed to her illness, rather than her competence. {{RoundBoxBottom}} [[File:Multidimensional_model_of_self-concept_diagram.png|thumb|536x536px|'''Figure 2.''' The hierarchical multidimensional model of self-concept (Marsh et al., 2019).]] Illustrating the causes of self-handicapping, Schwinger et al. (2022) found a medium negative correlation between general self-evaluations and self-handicapping and a medium positive correlation between fear of failure and self-handicapping. With more negative general self-evaluations and greater fear of failure, people are more likely to self-handicap, highlighting self-concept as an precursor to self-handicapping. However, in this study, general, rather than domain-specific measures were used. According to the multidimensional model, self-concept is a hierarchical, multi-faceted construct, and more specific self-concepts are more closely related to actual behaviour (see Figure 2; Marsh et al., 2019). Accordingly, future research should investigate domain-specific measures of self-concept and fear of failure to illustrate their direct influence on self-handicapping and task motivation. Self-handicapping demonstrates that self-concept-driven motivation is not always directed towards achieving valued outcomes. Protecting self-worth can become more important than goal engagement. Together, this research suggests self-concept can act both as a motivational resource, and a motivational vulnerability. {{RoundBoxTop|theme=9}}'''Intervention application: Reduce self-threat''' Self-handicapping shows that holding success as a contingency for self-worth can be damaging (Showers et al., 2015). This means interventions should reduce how much self-worth depends on outcomes, by promoting self-compassion, diverse positive self-concepts, and growth-oriented interpretations of failure to improve motivation and wellbeing.{{RoundBoxBottom}} == How does motivation shape self-concept? == The research and theories discussed so far have detailed how self-concept directs and motivates behaviour. The following section explores how, and whether, this relationship works in reverse.   === How internalising motivation shapes self-concept === [[File:Self-determination theory psychological needs.jpg|thumb|450x450px|'''Figure 3.''' Self-determination theory proposes that autonomy, competence, and relatedness support autonomous motivation (Ryan & Deci, 2020).]][[Self-determination theory]] (Ryan & Deci, 2020) proposes motivation exists on a continuum of self-determination, ranging from externally to increasingly internally regulated behaviour. The continuum consists of external, introjected, identified, integrated, and intrinsic regulation (Table 4). These motivation types are influenced by three innate needs: competence, autonomy, and relatedness (see Figure 3; Ryan & Deci, 2020). Understanding the progression of these needs and motivation types can provide insight into how motivational processes influence self-concept. Intrinsic motivation refers to autonomous behaviours completed for enjoyment (see Table 4; Morris et al., 2022). Extrinsic motivation involves engaging in behaviour for an outcome separable from the activity itself (Morris et al., 2022). Its regulation ranges from externally controlled to personally valued and fully integrated. How self-determined people's motivations are depends on the extent to which one has internalised the values, beliefs and perceptions of the behaviour into their self-concept. Meeting the needs of competence, autonomy and relatedness supports motivations to become progressively internalised, and behaviour increasingly self-endorsed (Chiu, 2023). However, it should be noted that this process does not necessarily occur in a fixed sequence. This illustrates how self-concept and motivation reciprocally form one another. The degree to which one identifies with a behaviour shapes their motivation to engage with the behaviour; when needs are met, motivated behaviours and psychological processes shape the self-concept. This internalisation process helps explain how Ash came to identify as a swimmer (see Table 4).   '''Table 4''' ''Applying Self-Determination Theory to Ash's Motivation and Self-Concept Development'' {| class="wikitable" style="margin: auto;" !Type of motivation !Ash's circumstances   !Mechanism |- |External regulation |Ash received a lollipop after swimming lessons.   |Non-self-determined drive.   |- |Introjected regulation |Ash wants her parents to think she is dedicated to swimming. |Partially internalised extrinsic motivation, low self-determination.   |- |Identified regulation |Swimming becomes important to Ash as she starts feeling like a good swimmer (competence) and drives herself to training (autonomy).   |More internalised and self-determined. |- |Integrated regulation |Ash starts to identify as a swimmer and with her swim team (relatedness).   |Fully integrated into self-concept. Highly self-determined but performed for valued outcome not enjoyment. |- |Intrinsic motivation |After the swimming competition, Ash continues swimming for the joy of it.   |Fully integrated into self-concept. Fully autonomous motivation for enjoyment. |} Chiu (2023) provided compelling evidence for how motivation shapes self-concept within the context of self-determination theory. In their study, 342 Hong Kong high school students completed STEM activities taught using a standard teaching approach or a self-determination theory teaching method, focusing on supporting needs of autonomy, competence and relatedness (see Figure 3). Self-report measures reflected that the needs-supporting teaching approach increased students' feelings of autonomy, competence and relatedness; and, consequently, increased STEM identity and interest. This supports that fulfilling core psychological needs promotes more autonomous motivation and develops one's identity. Further supporting this relationship, Yip et al.'s (2024) longitudinal study of 236 anti-poverty activists who completed self-reported social attitudes and personality measures at two timepoints found that increases in self-determined motivations positively correlated with group identification. However, non-self-determined motivations, such as external regulation, did not correlate with group identification. This suggests that self-determined motivation facilitates the incorporation of behaviour and group membership into one's self-concept.   Together, self-determination theory suggests self-concepts develop as values and behaviours are progressively internalised. Ash was not initially motivated because she identified as a swimmer. Her repeated engagement in swimming and fulfilment of psychological needs gradually transformed swimming into part of her identity. This demonstrates that motivation can be a mechanism through which self-concept develops and is not simply a motivating force. {{RoundBoxTop|theme=11|title=Quiz}} <quiz display=simple> '''Which statement best reflects how motivation shapes self-concept?''' |type="()"} - People are only motivated to engage in behaviours that are part of their self-concept. - Self-concept does not change through motivational processes. + Repeated engagement with a behaviour and satisfaction of psychological needs gradually makes a behaviour part of one's self-concept. </quiz>{{RoundBoxBottom}} === The cyclical process of motivation and self-concept development === The reciprocal effects model proposes that self-concept and achievement reinforce one another over time (Marsh et al., 2018). People with stronger self-concepts tend to achieve more highly, while achievement experiences subsequently shape self-concept. Motivation plays an important role in this process, influencing how people behave toward achievement experiences. There is a growing body of research investigating this model. For example, Sewasew et al.'s (2018) longitudinal study with 2,342 German high schoolers demonstrated mathematics self-concept was positively correlated with mathematics achievement. Their study highlighted a mutually dependent relationship between academic self-concept and achievement, each mediated by motivation. However, Garn and Shen's (2015) longitudinal study of 329 participants' self-concept and motivation for exercise found that the psychological needs posited by self-determination theory (Ryan & Deci, 2022) did not predict physical self-concept at follow-ups. Physical self-concept was only shown to shape, rather than be shaped by exercise motivation. This result conflicts with the reciprocal effects model and Sewasew et al.'s (2018) results, which may be a reflection of the different self-concept domains examined, mathematics versus physical self-concept. This may indicate that reciprocal effects are domain specific; the multidimensional model suggests academic and physical self-concepts function independently, meaning findings from one domain may not generalise to another (Marsh et al., 2019). Thus, future research should directly compare the reciprocal relationship between self-concept and motivation within different domains. Similarly, Sorjonen et al. (2024) reanalysed meta-analytic results which had provided evidence for the reciprocal effects model. Sorjonen et al. (2024) found that conclusions about the longitudinal relationship between achievement and academic self-concept changed depending on the statistical model used. Hübner et al.'s (2023) support for the reciprocal effects model was also inconsistent between statistical models. This may indicate a spurious correlation that undermines the credibility of the reciprocal effects model. Taken together, these findings suggest that achievement can shape self-concept, but the strength and direction of this relationship may depend on the domain being examined and the methodological approach used. Although the reciprocal effects model remains influential, current evidence indicates that the relationship between motivation, achievement, and self-concept is more complex than originally proposed. == Conclusion == Self-concept is a multidimensional and socially developed framework of beliefs about oneself which acts as a guiding compass. Self-concept shapes motivation by determining which goals feel meaningful, attainable, and identity-consistent through processes of self-discrepancy, difficulty interpretation and self-worth contingencies. Self-discrepancy theory explains how distance from valued selves can create motivational pressure for change. Identity-based motivation theory explains how active identities change the meaning of difficulty. Whereas self-worth contingencies can undermine motivation. Together, these theories detail that self-concept influences goal direction and engagement through social, emotional and cognitive processes. These theories provide insight that motivation-improving interventions should consider targeting how people understand themselves rather than solely targeting behaviours. Motivation may also influence self-concept. Self-determination theory details that motivation and subsequent behaviours form self-concept through internalisation processes when psychological needs are met. However, inconsistent support for the reciprocal effects model indicates that the extent to which motivation reshapes self-concept may vary across domains and statistical models. {{RoundBoxTop|theme=3}} '''Take-home message''' With self-concept and motivation inherently linked, who people believe they are shapes the goals they pursue, while motivations, behaviours, and experiences continually reshape who people become. {{RoundBoxBottom}} {{RoundBoxTop|theme=11|title=Quiz}}<quiz display=simple> {'''Chapter comprehension check quiz:''' Ash wakes up at 4:00 a.m. each day to train because being a swimmer is a central part of her identity. According to the chapter, what best explains Ash's motivation? |type="()"} +Self-concept acts as an internal compass that guides goals and behaviour. -Motivation is caused only by external rewards and punishment. -Self-concept remains fixed and has little influence on actions. </quiz> {{RoundBoxBottom}} == See also == * [[wikipedia:Self-concept|Self-concept]] (Wikipedia) * [[Motivation and emotion/Book/2019/Self-concept clarity|Self-concept clarity]] (Book chapter, 2019) * [[Motivation and emotion/Book/2014/Self-efficacy and motivation|Self-efficacy and motivation]] (Book chapter, 2014) == References == {{Hanging indent|Bandhu, D., Mohan, M. M., Nittala, N. A. P., Jadhav, P., Bhadauria, A., & Saxena, K. K. (2024). Theories of motivation: A comprehensive analysis of human behavior drivers. ''Acta Psychologica, 244'', 104177. https://doi.org/10.1016/j.actpsy.2024.104177 Chiu, T.K. (2023). Using self-determination theory (SDT) to explain student STEM interest and identity development. ''Instructional Science, 52'', 89–107. https://doi.org/10.1007/s11251-023-09642-8 Cooley, C. H. (1902). The looking-glass self. ''The production of reality: Essays and readings on social interaction, 6''(1902), 126–28. Coudevylle, G. R., Boulley-Escriva, G., Finez, L., Eugène, K., & Robin, N. (2020). An experimental investigation of claimed self-handicapping strategies across motivational climates based on achievement goal and self-determination theories. ''Educational Psychology, 40''(8), 1002–1021. https://doi.org/10.1080/01443410.2020.1746237 Garn, A., & Shen, B. (2015). Physical self-concept and basic psychological needs in exercise: Are there reciprocal effects? ''International Journal of Sport and Exercise Psychology, 13''(2), 169–181. https://doi.org/10.1080/1612197X.2014.940994 Higgins, E. T. (1987). Self-discrepancy: A theory relating self and affect. ''Psychological Review, 94''(3), 319. Higgins, E. T. (1989). Self-discrepancy theory: What patterns of self-beliefs cause people to suffer?. In ''Advances in experimental social psychology'' (Vol. 22, pp. 93–136). Academic Press. Higgins, E. T., Shah, J., & Friedman, R. (1997). Emotional responses to goal attainment: Strength of regulatory focus as moderator. ''Journal of Personality and Social Psychology, 72''(3), 515–525. https://doi.org/10.1037/0022-3514.72.3.515 Hübner, N., Wagner, W., Zitzmann, S., & Nagengast, B. (2023). How strong is the evidence for a causal reciprocal effect? Contrasting traditional and new methods to investigate the reciprocal effects model of self-concept and achievement. ''Educational Psychology Review, 35'', 6. https://doi.org/10.1007/s10648-023-09724-6 James, W. (1892). The self. In W. James (Ed.), ''Psychology: Briefer course'' (pp. 176–216). Macmillan and Co. https://doi.org/10.1037/11630-012 Lietz, R., Whittaker, S., & Su, N. M. (2026). ‘It meant something about who I am’: What the lived experience of failure teaches us about designing for goal setting. ''Behaviour & Information Technology,'' 1–27. https://doi.org/10.1080/0144929X.2026.2711023 MacIntyre, P. D., & Vincze, L. (2017). Positive and negative emotions in motivation for second language learning. ''Studies in Second Language Learning and Teaching, 7''(1), 61–88. https://doi.org/10.14746/ssllt.2017.7.1.4 Marsh, H. W., Byrne, B. M., & Shavelson, R. J. (1992). A multidimensional, hierarchical self-concept. In T. M. Brinthaupt & R. P. Lipka (Eds.), ''The self: Definitional and methodological issues'' (pp. 44–95). State University of New York Press. Marsh, H. W., Martin, A. J., Yeung, A. S., & Craven, R. G. (2018). Chapter 6: Competence self-perceptions. In A. J. Elliot, C. S. Dweck, & D. S. Yeager (Eds.), ''Handbook of competence and motivation: Theory and application'' (pp. 85–115). Guilford Publications. Marsh, H. W., Seaton, M., Dicke, T., Parker, P. D., & Horwood, M. S. (2019). The centrality of academic self-concept to motivation and learning. In K. A. Renninger, & S. E. Hidi (Eds.), ''The Cambridge handbook of motivation and learning'' (pp. 36–62). Cambridge University Press. https://doi.org/10.1017/9781316823279.004 Mason, T. B., Smith, K. E., Engwall, A., Lass, A., Mead, M., Sorby, M., Bjorlie, K., Strauman, T. J., & Wonderlich, S. (2019). Self-discrepancy theory as a transdiagnostic framework: A meta-analysis of self-discrepancy and psychopathology. ''Psychological Bulletin, 145''(4), 372–389. https://doi.org/10.1037/bul0000186 Morris, L. S., Grehl, M. M., Rutter, S. B., Mehta, M., & Westwater, M. L. (2022). On what motivates us: A detailed review of intrinsic v. extrinsic motivation. ''Psychological Medicine, 52''(10), 1801–1816. https://doi.org/10.1017/S0033291722001611 Nurra, C., & Oyserman, D. (2018). From future self to current action: An identity-based motivation perspective. ''Self and Identity, 17''(3), 343-364. https://doi.org/10.1080/15298868.2017.1375003 Oyserman, D. (2015). Identity-based motivation. ''Emerging Trends in the Social and Behavioral Sciences, 38'', 1–11. https://doi.org/10.1002/9781118900772.etrds0171 Oyserman, D. (2024), Identity-based motivation and the motivational consequences of difficulty. ''Social and Personality Psychology Compass, 18'', e70028. https://doi.org/10.1111/spc3.70028 Ryan, R. M., & Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. ''Contemporary Educational Psychology, 61'', 101860. https://doi.org/10.1016/j.cedpsych.2020.101860 Ryan, R. M., & Deci, E. L. (2022). Self-determination theory. In F. Maggino (Ed.), ''Encyclopedia of quality of life and well-being research'' (pp. 1–7). Springer, Cham. https://doi.org/10.1007/978-3-319-69909-7_2630-2 Schwinger, M., Trautner, M., Pütz, N., Fabianek, S., Lemmer, G., Lauermann, F., & Wirthwein, L. (2022). Why do students use strategies that hurt their chances of academic success? A meta-analysis of antecedents of academic self-handicapping. ''Journal of Educational Psychology, 114''(3), 576–596. https://doi.org/10.1037/edu0000706 Seaton, M., Parker, P., Marsh, H. W., Craven, R. G., & Yeung, A. S. (2014). The reciprocal relations between self-concept, motivation and achievement: Juxtaposing academic self-concept and achievement goal orientations for mathematics success. ''Educational Psychology, 34''(1), 49–72. https://doi.org/10.1080/01443410.2013.825232 Sewasew, D., Schroeders, U., Schiefer, I. M., Weirich, S., & Artelt, C. (2018). Development of sex differences in math achievement, self-concept, and interest from grade 5 to 7. ''Contemporary Educational Psychology, 54'', 55–65. https://doi.org/10.1016/j.cedpsych.2018.05.003 Showers, C. J., Ditzfeld, C. P., & Zeigler-Hill, V. (2015). Self-concept structure and the quality of self-knowledge. ''Journal of Personality, 83''(5), 535-551. https://doi.org/10.1111/jopy.12130 Sorjonen, K., Ingre, M., Melin, B., & Nilsonne, G. (2024). Questioning the reciprocal effects model of academic self-concept and achievement: A reanalysis of a meta-analysis of longitudinal studies and a simulation. ''Sage Open, 14''(4). https://doi.org/10.1177/21582440241292826 Török, L., & Szabó, Z. P. (2018). The theory of self-handicapping: Forms, influencing factors and measurement. ''Ceskoslovenska Psychologie, 62''(2), 173-188. Wang, L., Cui, Y., Wang, X., Wang, J., Du, K., & Luo, Z. (2021). Regulatory focus, motivation, and their relationship with creativity among adolescents. ''Frontiers in Psychology, 12'', 666071. https://doi.org/10.3389/fpsyg.2021.666071 Wehrle, K., & Fasbender, U. (2018). Self-concept. In Zeigler-Hill, V., & Shackelford, T. (Eds.), ''Encyclopedia of personality and individual differences'' (pp. 1–5). Springer, Cham. https://doi.org/10.1007/978-3-319-28099-8_2001-1 Weiner, B. (1985). An attributional theory of achievement motivation and emotion. ''Psychological Review, 92''(4), 548–573. https://doi.org/10.1037/0033-295X.92.4.548 Yip, L., Thomas, E. F., Amiot, C., Louis, W. R., & McGarty, C. (2024). Autonomous motives foster sustained commitment to action: Integrating self-determination theory and the social identity approach. ''Personality and Social Psychology Bulletin, 50''(5), 750–765. https://doi.org/10.1177/01461672221148396 }} == External links == * [https://rickhanson.com/being-well-podcast-self-concept-the-secret-to-changing-who-you-are/ Being well podcast: Self-concept: The secret to changing WHO you are] (Being Well Podcast) * [https://www.youtube.com/watch?v=Nck7lP-6C2g Unlocking success: The power of self-efficacy and self-concept] (TEDx Talks) * [https://www.ted.com/talks/anil_ananthaswamy_where_does_your_sense_of_self_come_from_a_scientific_look Where does your sense of self come from? A scientific look] (TEDx Talks) [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Self-concept]] [[Category:Motivation and emotion/Book/2026]] [[Category:Motivation and emotion/Book/Motivation]] rittrxuzaau75vmrh6d7j2r00w6fw7f 0 331068 2835302 2833392 2026-10-01T09:13:41Z Flickstar888 3106813 Placed information into CoPilot to format a table. 2835302 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ ==Overview== {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian. Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Malicious envy vs benign envy == Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. {| class="wikitable" |+ '''Benign and Malicious Envy''' ! Aspect ! Benign Envy ! Malicious Envy |- | Definition | A form of envy that motivates self‑improvement. | A form of envy that arises when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, effort, and learning. | Creates feelings of resentment, threat, or inadequacy. |- | Typical Behaviours | Working harder, learning new skills, seeking development opportunities. | Exclusion, criticism, gossip, or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into interpersonal conflict. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * [[Self-Efficacy]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= doi:10.1007/s10490-021-09772-y Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] mv48e8cfuzmqorkvi5m039a22gwz5yh 2835303 2835302 2026-10-01T09:16:25Z Flickstar888 3106813 Tried to move text around although it didnt work. I will try another way 2835303 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ ==Overview== {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian. Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Malicious envy vs benign envy == Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. {| class="wikitable" |+ '''Benign and Malicious Envy''' ! Aspect ! Benign Envy ! Malicious Envy |- | Definition | A form of envy that motivates self‑improvement. | A form of envy that arises when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, effort, and learning. | Creates feelings of resentment, threat, or inadequacy. |- | Typical Behaviours | Working harder, learning new skills, seeking development opportunities. | Exclusion, criticism, gossip, or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into interpersonal conflict. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * [[Self-Efficacy]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= doi:10.1007/s10490-021-09772-y Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] 9rd5xi3e2cap17za0o71eji72l0xksf 2835305 2835303 2026-10-01T09:19:34Z Flickstar888 3106813 Cut and paste text so it flows better 2835305 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ ==Overview== {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian. Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. == Malicious envy vs benign envy == Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} {| class="wikitable" |+ '''Benign and Malicious Envy''' ! Aspect ! Benign Envy ! Malicious Envy |- | Definition | A form of envy that motivates self‑improvement. | A form of envy that arises when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, effort, and learning. | Creates feelings of resentment, threat, or inadequacy. |- | Typical Behaviours | Working harder, learning new skills, seeking development opportunities. | Exclusion, criticism, gossip, or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into interpersonal conflict. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * [[Self-Efficacy]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= doi:10.1007/s10490-021-09772-y Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] muss0v97kkm0nswkudj5p7nffqfqeeu 2835306 2835305 2026-10-01T09:21:53Z Flickstar888 3106813 Moved text around page 2835306 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ ==Overview== {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian. Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. == Malicious envy vs benign envy == Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} {| class="wikitable" |+ '''Benign and Malicious Envy''' ! Aspect ! Benign Envy ! Malicious Envy |- | Definition | A form of envy that motivates self‑improvement. | A form of envy that arises when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, effort, and learning. | Creates feelings of resentment, threat, or inadequacy. |- | Typical Behaviours | Working harder, learning new skills, seeking development opportunities. | Exclusion, criticism, gossip, or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into interpersonal conflict. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * [[Self-Efficacy]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= doi:10.1007/s10490-021-09772-y Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] nazydkuj97j6n28z28kly5s5r6x0k0y 0 331100 2835270 2835001 2026-10-01T04:41:01Z U3239236 3106753 2835270 wikitext text/x-wiki {{title|Emotional intelligence:<br>How does emotional intelligence affect emotional wellbeing?}} __TOC__ == Overview == {{RoundBoxTop|theme=3}} [[File:Sophie emotional regulation scenario.png|thumb|'''Figure 1.''' A university student pausing to regulate her emotions after receiving a disappointing grade, generated with ai ]] '''Scenario''' Imagine Sophie, a university student managing several assessments and conflict with a close friend. After receiving a disappointing mark, she feels frustrated, embarrassed, and overwhelmed. Rather than reacting immediately, she recognises her emotions, takes time to regulate them, and later talks calmly with her friend. Another student in the same situation might become overwhelmed or react impulsively. Why might people respond differently to similar emotional situations? One explanation involves emotional intelligence, the ability to perceive, understand, use, and regulate emotions. EI may influence how people interpret and respond to emotional experiences and, consequently, their emotional wellbeing. Emotional wellbeing involves more than experiencing positive emotions or avoiding negative ones; it also concerns how people experience and manage emotions. Understanding the relationship between EI and wellbeing can help explain which emotional abilities may support wellbeing, which components are particularly important, and the psychological processes underlying this relationship. {{RoundBoxBottom}} {{RoundBoxTop}} ; Focus questions # What are emotional intelligence and emotional wellbeing? # What is the relationship between emotional intelligence and emotional wellbeing? #How does emotional intelligence influence emotional wellbeing? #Which components of emotional intelligence are particularly important for emotional wellbeing? # How can emotional intelligence be developed to support emotional wellbeing? {{RoundBoxBottom}} == What are emotional intelligence and emotional wellbeing? == Emotional intelligence can play an important role in how people recognise, understand, and regulate their emotions. These emotional abilities may influence how people cope with difficult experiences and support their overall emotional wellbeing. However, EI is a complex construct, and different emotional abilities may contribute to wellbeing in different ways. Before examining this relationship, it is important to understand what psychologists mean by emotional intelligence and emotional wellbeing. One influential approach to emotional intelligence is Mayer and Salovey's ability model, which describes emotional intelligence through four related abilities: perceiving emotions, using emotions to support thinking, understanding emotions, and managing emotions see Figure 1. An important practical question is whether emotional abilities can be developed and whether improving them leads to better wellbeing.[[File:Model of emotional intelligence.png|thumb|'''Figure 1.''' ''Mayer and Salovey's Emotional Intelligence model'' |359x359px]] === Defining emotional wellbeing === Emotional wellbeing refers to people's emotional experiences and how they evaluate their lives. Psychological research often distinguishes between hedonic and eudaimonic approaches to wellbeing. Hedonic wellbeing focuses on experiences such as pleasure, enjoyment, and comfort, whereas eudaimonic wellbeing emphasises personal growth, meaning, and authenticity (Huta & Waterman, 2014). Both approaches are important for understanding wellbeing, although researchers differ in how they define and measure these concepts. Importantly, emotional wellbeing does not mean feeling happy or positive all the time. Negative emotions such as sadness, anger, anxiety, and disappointment are normal responses to difficult experiences. Chen et al. (2023) explain that adaptive stress responses can help people cope with stressful situations or adjust to challenges that cannot be resolved, whereas maladaptive responses can increase the risk of stress-related difficulties. This highlights why wellbeing involves more than simply experiencing positive emotions; how people respond to difficult experiences is also important. Another approach to understanding wellbeing is Seligman's PERMA model, which identifies five elements of flourishing: positive emotion, engagement, relationships, meaning, and accomplishment (Al-Hendawi et al., 2024). Unlike approaches that focus mainly on emotional experiences, PERMA considers several aspects of a fulfilling life see Figure 2.[[File:ChatGPT Image Sep 26, 2026, 01 48 17 PM.png|thumb|335x335px|'''Figure 2.''' ''Seligman's PERMA model of wellbeing, consisting of positive emotion, engagement, relationships, meaning, and accomplishment. (AI generated)'' ]]<quiz display="simple"> Quiz 1. Which statement best describes emotional intelligence? |type="()"} + The ability to perceive, understand, use, and manage emotions. - The ability to avoid experiencing negative emotions. - The ability to remain happy in all situations. - The ability to control the emotions of other people. } </quiz> <quiz display="simple"> Quiz 2. What does emotion regulation involve? |type="()"} + Managing how we experience and respond to emotions. - Avoiding all negative emotions. - Staying positive in stressful situations. - Ignoring emotions until they disappear. } </quiz> === Trait emotional intelligence === Trait EI focuses on how people perceive their own emotional abilities and tendencies rather than how they perform on an objective test. It is usually measured through self-report questionnaires that assess how people typically recognise, understand, and manage emotions. In contrast, performance-based tests assess emotional abilities through emotion-related tasks. Chapman (2005) explains that trait EI is more closely related to personality, whereas ability EI is more closely associated with cognitive abilities. Performance-based measures, such as the Multifactor Emotional Intelligence Scale and Mayer-Salovey-Caruso Emotional Intelligence Test, assess responses using scoring criteria. However, determining a correct emotional response can be difficult because emotional situations may be interpreted differently. Expert scoring relies on selected experts, while consensus scoring reflects the responses of a reference group (Chapman, 2005). Trait EI avoids this scoring issue by focusing on people's perceptions of their emotional abilities. Common self-report measures include the Trait Meta-Mood Scale and the 33-item Schutte Self-Report Inventory of Emotional Intelligence (Chapman, 2005). However, people's perceptions of their emotional abilities may not always reflect their actual performance. This distinction is important when examining emotional wellbeing. Someone may believe they manage emotions effectively even when their behaviour suggests otherwise. Trait EI and wellbeing are also often measured using self-report questionnaires, which may influence the strength of the relationship observed between them (Sánchez-Álvarez et al., 2016). == What is the relationship between emotional intelligence and emotional wellbeing? == === Emotional intelligence and positive wellbeing === Research generally suggests that people with higher EI report greater subjective wellbeing. A meta-analysis of 25 studies involving more than 8,500 participants found a moderate positive association between EI and subjective wellbeing (''r'' = .32; Sánchez-Álvarez et al., 2016). This indicates that higher EI tends to be associated with greater subjective wellbeing, although the relationship is moderate rather than strong. Importantly, the strength of the relationship depended on how EI was measured. The association was stronger for self-report measures that incorporated emotional and personality-related characteristics (''r'' = .38) than for performance-based measures (''r'' = .22). EI also showed a somewhat stronger relationship with life satisfaction (''r'' = .35) than with emotional experiences (''r'' = .29). These findings demonstrate why the way EI and wellbeing are defined and measured matters when interpreting their relationship (Sánchez-Álvarez et al., 2016). However, these findings do not demonstrate that EI causes greater happiness or life satisfaction. People who already experience greater wellbeing may find it easier to perceive or manage emotions, while other characteristics, including personality, could potentially contribute to both EI and wellbeing. ==== Emotional intelligence and negative wellbeing ==== EI has also been examined in relation to psychological distress and other negative outcomes. Martins et al. (2010) found that higher EI was associated with better health outcomes, including aspects of mental health. Research has also examined relationships between emotional abilities, emotion regulation, and symptoms of depression (Fernández-Berrocal & Extremera, 2016). Importantly, higher EI does not mean that someone will never experience negative emotions. Instead, emotional abilities may influence how people understand and respond to difficult emotions when they occur. Sophie's emotional abilities, for example, do not prevent her from feeling disappointed about her grade. They may instead help her recognise the emotion and choose how to respond to it. ===== Trait and ability emotional intelligence ===== Trait EI tends to show stronger associations with wellbeing than ability EI, which is typically assessed using performance-based measures. One possible explanation is that trait EI and wellbeing are often both assessed using self-report questionnaires. Similar measurement methods can contribute to stronger observed relationships between constructs. Self-report measures also assess people's perceptions of their emotional abilities, which may not always correspond with their performance on emotional ability tasks. This makes the way EI is measured particularly important when interpreting its relationship with wellbeing ====== '''What does the evidence tell us?''' ====== Overall, research suggests that higher EI is linked to greater subjective wellbeing and lower psychological distress. However, the strength of this relationship varies depending on how EI is defined and measured (Martins et al., 2010; Sánchez-Álvarez et al., 2016). However, an association between EI and wellbeing does not demonstrate that EI directly causes better wellbeing. Much of this research is correlational, meaning the direction of the relationship cannot necessarily be established and other factors may contribute to both constructs. Differences between EI models and measurement approaches further complicate interpretation. Therefore, the evidence supports a relationship between EI and wellbeing, but stronger causal conclusions require research capable of examining whether changes in EI actually produce changes in wellbeing. Finding an association also does not explain how EI and wellbeing are connected. Emotional awareness, emotional understanding, emotion regulation, coping with stress, and social relationships may provide possible pathways through which EI is associated with emotional wellbeing. == How does emotional intelligence influence emotional wellbeing? == === Emotional awareness and perception === The relationship between emotional intelligence and wellbeing may be explained by several psychological processes. Emotional intelligence may help people recognise what they are feeling, understand why those emotions have occurred, regulate difficult emotional responses, and cope more effectively with stressful situations. It may also support communication and relationships with others. Rather than working separately, these processes are likely to interact and may help explain why people with higher emotional intelligence often report greater wellbeing. ==== Emotional awareness and perception ==== Recognising emotions is an important first step in responding to them effectively. Being able to identify whether a person is feeling anxious, angry, disappointed, or overwhelmed can provide useful information about what is happening and what they may need to do next. For example, recognising feelings of anxiety before an assessment may help a student identify the source of their stress and decide whether they need to prepare further, seek support, or use a strategy to manage their anxiety. Difficulty recognising emotions may make it harder to respond appropriately. A person who interprets anxiety as anger, for example, may react to a situation differently than someone who accurately understands what they are experiencing. Emotional awareness alone does not guarantee good emotional wellbeing, but it may provide the information needed for later processes such as emotional understanding, regulation, and coping (Lane & Smith, 2021). {{RoundBoxTop|theme=3}}💡 Tip When you experience a strong emotion, try identifying exactly what you are feeling rather than simply describing it as “good” or “bad.” For example, you might recognise that you are disappointed rather than embarrassed, or anxious rather than angry. This ability to identify emotions more precisely, known as emotional granularity, can help build emotional awareness and guide how you respond.{{RoundBoxBottom}} ==== Understanding emotions ==== Emotional intelligence also involves understanding why emotions occur and how they may change over time. Emotional experiences are not always simple, and people can experience several emotions at once. Someone receiving critical feedback, for example, might simultaneously feel disappointed, embarrassed, and motivated to improve. Understanding the causes and possible consequences of these emotions may help people choose more appropriate responses. Instead of immediately reacting to disappointment, a person who understands where the feeling comes from may be better able to consider the situation before deciding what to do (Tzieropoulos et al., 2011). Emotional understanding may therefore contribute to wellbeing indirectly by supporting more effective emotion regulation and coping. ===== Emotion regulation ===== Emotion regulation refers to how people influence their emotional experiences and responses. Rather than eliminating negative emotions, regulation can involve changing how a situation is interpreted or choosing how to respond. Different strategies may have different consequences for wellbeing. Cognitive reappraisal changes the interpretation of a situation to alter its emotional impact, however suppression reduces emotional expression without necessarily changing the underlying experience. Emotional intelligence may help people select appropriate regulation strategies, potentially explaining its relationship with wellbeing (MacCann et al., 2026). However, further evidence is needed to determine whether emotion regulation actually mediates the relationship between emotional intelligence and wellbeing. ====== Coping with stress ====== Emotional intelligence may also influence how people respond to stressful experiences. Stress can produce difficult emotional responses such as tension, worry, and feelings of being overwhelmed. Chen et al. (2023) distinguish between adaptive responses that help people cope with or adjust to stressors and maladaptive responses that may interfere with functioning and increase the risk of stress-related difficulties. Emotional skills may be useful during this process because recognising and understanding an emotional response can help a person decide how to cope with the situation. Effective coping does not necessarily remove the stressor, particularly when a situation cannot be changed. Instead, people may need to adjust their response to it. Emotion regulation has also been identified as a resilience-related factor, further demonstrating the connection between emotional processes and responses to stress. ====== Social relationships and support ====== Emotional intelligence may also contribute to wellbeing through relationships with other people. Recognising another person's emotions can make it easier to understand their perspective, communicate appropriately, and respond to interpersonal difficulties. Managing one's own emotional responses may also be important during disagreements or emotionally challenging conversations. These abilities could support stronger relationships and access to social support, providing another possible pathway between emotional intelligence and wellbeing. However, being able to recognise another person's emotions does not automatically lead to supportive or prosocial behaviour (Hidalgo-Fuentes et al., 2024).. Emotional abilities describe how effectively emotional information is processed, rather than whether that information will always be used positively. '''Figure 3.''' ''Possible pathways through which emotional intelligence may support emotional wellbeing.'' Emotional intelligence may contribute to emotional wellbeing through several interacting processes, including emotional awareness, emotional understanding, emotion regulation, coping with stress, and social functioning. These processes may influence one another rather than occurring in a simple step-by-step sequence. == Which components of emotional intelligence are particularly important for emotional wellbeing? == Although emotional intelligence is often discussed as a single construct, Mayer and Salovey's ability model proposes several distinct emotional abilities. These components may not contribute equally to emotional wellbeing. Comparing emotion perception, using emotions, emotional understanding, and emotion management can therefore provide a clearer picture of which aspects of emotional intelligence may be particularly relevant to wellbeing. === Emotion perception === Emotion perception involves accurately recognising emotions in oneself and other people. This ability may contribute to wellbeing by helping individuals identify their emotional state and recognise emotional information in social situations. However, recognising an emotion does not necessarily mean that a person knows how to respond to it. Someone may accurately recognise that they are angry, for example, while still responding impulsively. Emotion perception may therefore provide an important foundation for emotional functioning without being sufficient on its own to support wellbeing (Carfagno, 2020). ==== '''Using emotions''' ==== Using emotions involves drawing on emotional information to support thinking, attention, judgement, and decision-making. Different emotional states can influence what people notice and how they approach a problem. Being able to use this information may therefore help individuals adapt their thinking to different situations. However, the relevance of this component to emotional wellbeing needs to be established through research rather than assumed (Blasco-Belled et al., 2019). Compared with emotion management, for example, using emotions may have a less direct connection with how people cope with distress or regulate difficult emotional experiences. ==== Emotion understanding ==== Emotion understanding involves recognising the causes of emotions, distinguishing between related emotional states, and understanding how emotions can change or combine. This ability may help people make sense of complicated emotional experiences and anticipate how feelings might develop. Understanding an emotion may also make it easier to choose an appropriate coping or regulation strategy. However, as with emotion perception, understanding an emotion does not guarantee that it will be managed effectively. Research comparing the different branches of emotional intelligence is therefore needed to determine whether emotional understanding has an independent relationship with wellbeing or primarily contributes through other emotional processes (Antonopoulou, 2024). ===== Emotion regulation and management ===== Emotion management may have a particularly direct connection with emotional wellbeing because it concerns how people respond to and regulate emotional experiences. Effective regulation could help people manage distress, maintain positive emotional functioning, and recover from stressful experiences. This does not mean eliminating negative emotions, but responding to them in ways that are appropriate to the situation. However, emotion management should not automatically be considered the most important component of emotional intelligence. Its relative importance needs to be established by studies that compare it directly with perception, use, and understanding of emotions. Differences in how emotional intelligence and wellbeing are measured may also affect which component appears most strongly related to wellbeing (Blasco-Belled et al., 2019). ====== Comparing the components ====== Overall, the four emotional abilities may contribute to wellbeing in different but connected ways. Perception provides information about emotional states, understanding helps make sense of that information, using emotions may support thinking and decision-making, and management concerns how emotional experiences are handled. Rather than functioning independently, these abilities may work together. Determining whether one component is particularly important requires direct comparisons across the four branches. Evidence that emotion management is associated with wellbeing would not, by itself, demonstrate that it is more important than the other components. Differences between ability-based and self-report measures should also be considered when interpreting these findings. <quiz display="simple"> Quiz 3. Which statement best describes how the components of emotional intelligence relate to wellbeing? |type="()"} + Different EI components may contribute to wellbeing in different but connected ways. - Emotion management is always the most important component for wellbeing. - Emotion perception alone is enough to support emotional wellbeing. - All EI components affect wellbeing in exactly the same way. } </quiz> <quiz display="simple"> Quiz 4. Why might recognising an emotion not be enough to support wellbeing? |type="()"} + A person may recognise an emotion but still respond to it poorly. - Recognising emotions prevents people from regulating them. - Emotion perception only involves recognising other people's emotions. - Recognising emotions automatically removes negative feelings. } </quiz> '''Table 2.''' ''Emotional intelligence components and wellbeing'' {| class="wikitable" !EI component !What it involves !Relevance to wellbeing |- |'''Emotion perception''' |Recognising emotions |Supports emotional awareness |- |'''Using emotions''' |Using emotions to guide thinking |Supports attention and judgement |- |'''Emotion understanding''' |Understanding causes and changes in emotions |Supports understanding and responding |- |'''Emotion management''' |Regulating emotional responses |Supports coping and emotional functioning |} == How can emotional intelligence be developed to support emotional wellbeing? == If emotional intelligence contributes to wellbeing, an important practical question is whether these emotional abilities can be developed. Emotional intelligence interventions have attempted to improve skills such as emotional awareness, understanding emotions, emotion regulation, and interpersonal communication. However, evidence that EI can be improved does not necessarily mean that increasing EI will automatically improve emotional wellbeing. === Can emotional intelligence be developed? === Emotional intelligence is not necessarily a completely fixed characteristic. Training programs have attempted to develop emotional abilities through education, practice, feedback, and exercises focused on recognising and managing emotions. However, the effectiveness of training may depend on how emotional intelligence is conceptualised and measured. Changes in self-reported EI, for example, may indicate that people feel more confident in their emotional abilities without necessarily demonstrating equivalent improvements on performance-based measures. Research evaluating EI interventions is therefore important for determining whether emotional abilities can genuinely be improved and whether any improvements continue after training has ended (Hodzic et al., 2017). ==== Emotional intelligence interventions ==== EI interventions may target several skills rather than emotional intelligence as a single ability. Activities can focus on recognising emotional cues, developing emotional vocabulary, understanding emotional triggers, considering other people's perspectives, practising emotion-regulation strategies, and improving emotional communication. These approaches are particularly relevant to emotional wellbeing if improvements in emotional skills help people respond more effectively to stress and difficult emotional experiences. However, intervention studies need to examine more than whether EI scores increase. They should also assess whether changes are accompanied by meaningful improvements in wellbeing. ===== Do improvements in emotional intelligence improve wellbeing? ===== An important distinction is whether EI training improves emotional intelligence itself and whether those improvements subsequently lead to better wellbeing. An intervention could increase participants' knowledge about emotions without meaningfully changing their happiness, life satisfaction, stress, or emotional functioning. Evidence that an intervention improves both EI and wellbeing would provide stronger support for a possible causal relationship than correlational studies showing that the two are associated. Even then, researchers need to consider whether improvements are maintained over time and whether changes in wellbeing are actually explained by increased emotional intelligence (Hodzic et al., 2018; Nadler et al., 2020). ====== Limitations and practical implications ====== Although EI training may have practical value, its potential benefits should not be overstated. Emotional wellbeing is influenced by many personal, social, and environmental factors, and improving emotional skills cannot remove every source of stress or psychological difficulty. Differences between EI models, measurement methods, intervention designs, and participant groups can also make findings difficult to compare. ==Conclusion== Emotional wellbeing involves more than simply feeling happy or avoiding negative emotions. It also involves how people understand, respond to, and manage their emotional experiences. Overall, emotional intelligence may support emotional wellbeing by helping people recognise, understand, and regulate emotions and respond more effectively to stressful and interpersonal experiences. Research generally shows that higher EI is associated with better indicators of wellbeing, although the strength of this relationship varies depending on how EI and wellbeing are defined and measured. Importantly, emotional intelligence should not be viewed as a guarantee or universal cause of emotional wellbeing. Wellbeing is influenced by many factors, and emotionally intelligent people will still experience stress, disappointment, conflict, and other difficult emotions. Sophie's situation demonstrates this distinction. Her emotional abilities do not prevent her from feeling disappointed or overwhelmed; instead, they may help her recognise what she is experiencing, understand why she feels that way, regulate her response, and choose behaviours that better support her wellbeing ==See also Internal Links == * [[Motivation and emotion/Textbook/Emotion/Emotion management|Managing emotions]] * [https://en.wikipedia.org/wiki/Subjective_well-being?wprov=srpw1_1 Subjective wellbeing] (Book chapter, 2026) * [[Motivation and emotion/Book/2011/Emotional intelligence|Emotional intelligence]] (Book chapter, 2011) * [[wikibooks:Foundations_of_Education_and_Instructional_Assessment/Effective_Teaching/Intelligence#Introduction_to_Emotional_Intelligence|How are all children smart?]] (Wikibooks) ==References== {{Hanging indent|1= Antonopoulou, H. (2024, April 11). The value of emotional intelligence: Self-awareness, self-regulation, motivation, and empathy as key... Technium Education and Humanities . ResearchGate. https://www.researchgate.net/publication/379764627_The_Value_of_Emotional_Intelligence_Self-Awareness_Self-Regulation_Motivation_and_Empathy_as_Key_Components Al-Hendawi, M., Alodat, A., Al-Zoubi, S., & Bulut, S. (2024). A PERMA model approach to well-being: A psychometric properties study. BMC Psychology, 12(1). https://doi.org/10.1186/s40359-024-01909-0 Blasco-Belled, A., Rogoza, R., Torrelles-Nadal, C., & Alsinet, C. (2019). Emotional intelligence structure and its relationship with life satisfaction and happiness: New findings from the bifactor model. Journal of Happiness Studies, 21(6), 2031–2049. https://doi.org/10.1007/s10902-019-00167-x Chapman, B. P. (2005). Emotional intelligence at mid life: A cross sectional investigation of structural variance, social correlates, and relationship to established personality and ability taxonomies. Proquest.Com. https://www.proquest.com/psychology/docview/305400900/8D98674B36744231PQ/2?accountid=28889&sourcetype=Dissertations%20&%20Theses Chen, C., Kotozaki , Y., Okubo , R., & Nakagawa , S. (2023, July 13). Editorial: New insights into stress coping and resilience . Canberra.Edu.Au. https://pmc-ncbi-nlm-nih-gov.ezproxy.canberra.edu.au/articles/PMC10374303/ Hidalgo-Fuentes, S., Martínez-Álvarez, I., Sospedra-Baeza, M. J., Martí-Vilar, M., Merino-Soto, C., & Toledano-Toledano, F. (2024). Emotional intelligence and perceived social support: Its relationship with subjective well-being. Healthcare (Basel, Switzerland), 12(6), 634. https://doi.org/10.3390/healthcare12060634 Hodzic, S., Scharfen, J., Ripoll, P., Holling, H., & Zenasni, F. (2017). How efficient are emotional intelligence trainings: A meta-analysis. Emotion Review, 10(2), 138–148. https://doi.org/10.1177/1754073917708613 Huta, V., & Waterman, A. S. (2014). Eudaimonia and its distinction from hedonia: Developing a classification and terminology for understanding conceptual and operational definitions. Journal of Happiness Studies, 15(6), 1425–1456. https://doi.org/10.1007/s10902-013-9485-0 Lane, R. D., & Smith, R. (2021). Levels of emotional awareness: Theory and measurement of a socio-emotional skill. Journal of Intelligence, 9(3), 42. https://doi.org/10.3390/jintelligence9030042 Martins, A., Ramalho, N., & Morin, E. (2010). A comprehensive meta-analysis of the relationship between emotional intelligence and health. Personality and Individual Differences, 49(6), 554–564. https://doi.org/10.1016/j.paid.2010.05.029 MacCann , C., Double , K. S., & E Clarke , I. (2026). Lower avoidant coping mediates the relationship of emotional intelligence with well-being and ill-being. Canberra.Edu.Au. https://pmc-ncbi-nlm-nih-gov.ezproxy.canberra.edu.au/articles/PMC9396212/ Nadler, R., Carswell , J., & Minda, J. P. (2020, February). Online mindfulness training increases well-being, trait emotional intelligence, and workplace competency ratings: A randomized waitlist-controlled trial. Canberra.Edu.Au. https://pmc-ncbi-nlm-nih-gov.ezproxy.canberra.edu.au/articles/PMC7048000/ Sánchez-Álvarez, N., Extremera, N., & Fernández-Berrocal, P. (2015). The relation between emotional intelligence and subjective well-being: A meta-analytic investigation. The Journal of Positive Psychology, 11(3), 276–285. https://doi.org/10.1080/17439760.2015.1058968 Tzieropoulos, H., Peralta, R. G. de, Bossaerts, P., & Andino, S. L. G. (2011). The impact of disappointment in decision making: Inter-individual differences and electrical neuroimaging. Frontiers in Human Neuroscience, 4(235). https://doi.org/10.3389/fnhum.2010.00235 }} ==External links== * [https://www.ted.com/talks/maximilian_park_emotional_intelligence_from_a_teenage_perspective Emotional Intelligence From a Teenage Perspective] * [https://rickhanson.com/being-well-podcast-emotional-intelligence-improving-self-awareness-self-regulation-and-empathy-2/ Being Well Podcast: Emotional Intelligence: Improving Self-Awareness, Self-Regulation, and Empathy] * [https://www.youtube.com/watch?v=4KbSRXP0wik Emotion, Stress, and Health: Crash Course Psychology #26] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Emotional intelligence]] [[Category:Motivation and emotion/Book/Well-being]] dxanvtfqnm7nl2oj2vqieixquede9t1 0 331105 2835280 2830651 2026-10-01T07:25:24Z U3261376 3106964 Overview and references 2835280 wikitext text/x-wiki {{title|Sex work motivation:<br>What motivates sex work and how does this impact worker experiences?}} __TOC__ == Overview == {{RoundBoxTop|theme=5}} [[File:“Sex workers rights are human rights” - Europride 2019.jpg|thumb|200px|'''Figure 1'''. Prostitution in Sao Paulo, Brazil]] '''What would you do if you found yourself in this scenario?''' Feeling lost and left with little money of your own, but you have to make ends meet. What will you do when you have to pay your rent? What if you have a child? Would you turn to sex work to make ends meet? If you did... would that make your rights to a safe and trustworthy work environment just disappear? Sex work itself is illegal. Having been driven to such means to make ends meet, you must register as self-employed to pay taxes, buy a house, or even just be considered an employee. [https://doi.org/10.1080/14427591.2020.1830841. (Huglstad et al., 2020)]. Sex workers rights activists proclaim that sex work is work, that they are not victims in need of help, and that they are entitled to any basic human right (see Figure 1). That in itself poses another scenario: What drives people into sex work? Is it finance and convenience? Or is it pleasure and fun? {{RoundBoxBottom}} Sex work or prostitution is a broad topic which includes many elements of sexual activities. In 2005, Harcourt defined sex work, "or prostitution, [as] the provision of sexual services for money or its equivalent," ([https://pmc.ncbi.nlm.nih.gov/articles/PMC1744977/pdf/v081p00201.pdf Harcourt, 2005]). To understand sex work as a concept it is important to first understand why people may turn to sex work for an income to begin with. This topic has been discussed at nauseum however often in a negative and clouded light. As stated in The Journal of Sex Research in 2013, it wasn't until the 1990's that literature that looked into this topic stopped looking at prostitutes as "predominantly... ‘‘evil characters’’ or ‘‘sick personalities.’’" ([https://www.tandfonline.com/doi/pdf/10.1080/00224499.2012.696285?casa_token=wgasXeCYwFAAAAAA:0Iuwx4QzcbYP0ZAj6GISEX5oDHr4t-phuo4VUxmwfMIVjTrLXaTBhIoYpXtC9r0WaeYaxII3ObSZ Vanwesenbeeck, 2013]) and carrying a lense of ""simmering abhorrence, incomprehension, and fascination" (Vanwesenbeeck, 2013) towards these individuals. Some of the main concepts that will be unpacked below that motivates people to go into sex work are commonly, "financial, sexual, recreational motives, and coercion (i.e., trafficking)" (Vanwesenbeeck, 2013), and can often lead to negative workplace satisfaction. External influences like the adult entertainment industry and whorephobia can also heavily influence an individual's workplace satisfaction when working in the prostitution industry. To learn the in depth relationship between motivation to join sex work and the quality of said workplace satisfaction continue reading below. {{RoundBoxTop|theme=5}} '''Focus questions''' * What are the main driving forces causing people to turn to sex work? * What is the effect of the adult entertainment industry on sex workers? * What is the condition of work place satisfaction for sex workers? * How does whorephobia and others' actions towards sex workers effect their work place? * Do those who turn to sex work for pleasure have different experiences to those who do so for money alone? {{RoundBoxBottom}} == Driving forces pushing people towards [[Sex education|sex]] work == - Do those who turn to sex work for pleasure have different experiences to those who do so for money alone? === Age as a factor === - why do young people enter the sex work industry, how does that change workplace satisfaction? - how does parenting influence age related sex work? - do older individuals in the sex work industry experience more angism in their workplace? === Maslow's hierarchy of needs === - looking at maslows hierarchy of needs, what may cause people to turn to sex work? - does peoples standing on the hierarchy influence their workplace satisfaction? === Socioeconomic factors === - is sex work more prevelent in low socioeconomic places/citys around the world? - intrinsic vs extrinsic factors - how does their treatment change from higher to lower socioeconomic places == How motivations to join the sex work industry differ from men to women == {| class="wikitable" |+Percentages showing [[doi:10.1017/hyp.2024.56.|gender differences]] in paying for vs working in sex ! !Participate in sex work !Pay for sex work |- |Men |20% |12% |- |Women |80% |1% |} === Male sex workers === - why are they less prevelent in the public eye? - why are they not degraded as much as female workers? - do men turn to sex work to fulfill their own physical needs? === Female sex workers === - why are they more prevelent in the public eye? - why are they degraded more then male workers? - do women turn to sex work to fulfill their own physical needs? == The adult entertainment industry and its relationship to sex workers == - does this carer add unrealistic expectations towards sex workers and what people will ask to recieve? - looking into detail about how the adult entertainment industry can glorify sex work and how that may motivate people to join the industry. == Work place satisfaction for sex workers == - is there an element of sexual satisfaction which motivates sex workers? - is there a difference between men and women? - how to sexworkers respond to violence in their line of work and how may that motivate their actions? == [https://www.jrc-concordia.ca/wp-content/uploads/2017/01/Journal-of-Religion-and-Culture-Vol-27-no-1.pdf#page=13 Whorephobia] and how it influences work place satisfaction == - how do unfavorable opinions of sex workers effect motivation and how does that relate to workplace satisfaction? - how does the prevelence of this violence motivate sex workers to continue in their chosen carer path? - how does whorephobia effect workplace satisfaction?<quiz display="simple"> {More men then women experience sexual violence as a sex worker: |type="()"} - True + False {There are more women in the sex trade then there are men: |type="()"} - True + False </quiz> ==Conclusion== Through this chapter we have spoken about the different motivations that drives people into sex work and how that can influence work place experiences. We have done this by assesing how age and gender can influence motivations as well as what circumstances can effect those drives. - summerise the different motivations that lead to sex work, considering gender and age. - summerise how socioeconomic factors influence sex worker experiences, including prejudices. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== * [[Maslow's hierarchy of needs]] (Wikiversity) * [[Motivation and emotion/Book/2015/Sex worker motivation|Sex work motivation]] (Book chapter, 2015) ==References == {{Hanging indent|1=Arnold, K. A., Turner, N., Barling, J., & Iverson, R. D. (2020). Feeling safe while doing sex work: Motivation for entering sex work moderates the relationship between perceptions of physical danger and desire to leave sex work. Safety science, 129, 104795.[https://pdf.sciencedirectassets.com/271730/1-s2.0-S0925753520X00063/1-s2.0-S0925753520301922/main.pdf?X-Amz-Security-Token=IQoJb3JpZ2luX2VjEDgaCXVzLWVhc3QtMSJIMEYCIQDLwNUlkBLTVH2W9sUG%2FL8xBiniafqj2YjDThRYfM8j7gIhAPpb6usou%2FCfun2GlN94HXvsSkZFNyb27ndcS5LYkmOqKrIFCAEQBRoMMDU5MDAzNTQ2ODY1IgwVqu3mdLMxIbQQT4EqjwVyEzAMhHQLz8i1mRyce46T7kq8nFGMPfsWbvGbIjwD5sTztgejH2H6uoazHE3ceLn%2BHJAMU2gcjulIYqlqCSyvPuWe%2BScfjOHfBfQZnctFdUl2oWqaahIi9YzAVcTWeftoZk%2FylcCfLerGklhqD7HwVv2vZdBzsx94xmqQ1V1uUbIbAIkJ30NfSj00z1cSaUL1q96wM120kL%2By3Fd%2FYRnMyLzgn343yVJM%2BYWksKgOiezOVEa%2BhmIbNUYzcpb%2Fkcah8UWIgZWXjdLp2fZTJB2yCYbj091PqbNLxbKvPvqaCnGI%2BSTaCPpupfKIdR02m2jepxiZI8%2FZrLGy71f0vYzU%2Be120AQZZCPdjTZZAOP9xB%2Bvfpp48EyclSYmN0rSn2bZcMSiqosJl%2Bz6BiiW3J9SmbZXGNWeECGltEiG%2FP%2FRiZ0uB94c2nIGVzBsfJ4fe7UAD3mlWR9UBCT5FirlPE3Dzap%2BH1xnOe%2BGN481xmH1YSoL3FACDW8J5HUez%2BURv5vTzFDq4nON4cFWhMdgPNfu8v%2BjU35utqWccWAfsows5CFE%2FdiNDUQa7EI1XwF00wtRp2k06DjOWBl%2FggL2duXPWFHHaJnOEovHXAGzQUl%2FzBocvEbkU%2BstJU3AjUwCqbrDZRVZay0dd7OLQ6NCZTFxvZrhEoOwYukzgYt02XtXs23oNKc8QK8jPBsjSx8K1Xj9V9tPB5eBTptias5DuJnme5GPMo0H0rehhAFIbH1iz5aLEJ2WFAs2YMajNB9b8K9hsdcsufqw3IWvDgGjJl491SPFYv4AkHpfF%2B2OEEmH9hDMp3rnzv686gQ5u2%2FmSKrDsChJ2JSpJUuTnHdHBZrk%2Fwzx%2BpsfpZ4zLVgKx0K6MJOGtdQGOrAB7mHiroFpJKweD4wGdVv4twWKj65wn3ZS715WCDMXnol3ZjKerxKwtTiAS8MYNXREK5yRc6R%2BCtHqgkfO1QIL6y35fyD0iOWFO6ZYrI1IePcEupQe4Ao%2B8i5%2Bz9PydRXrVVCjz1A9o6ZcLX9dN59jVDboJOpZsOpXxuErU9LEKNKGTqVoHfJq%2FpKSdZkltmLsDvSAgBZORP2gpikUUQyl6A0CxzJ3SGD1ZrqXN39XlWY%3D&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20260825T084050Z&X-Amz-SignedHeaders=host&X-Amz-Expires=300&X-Amz-Credential=ASIAQ3PHCVTYZDNOMNKH%2F20260825%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=222054776072dd684a9220ca5e137f808570de2f4b46a74fc1fac36b8741d31e&hash=9077aea1050680fe483f80515f312051569ddf0b7a50ba90c1511bc6ef136d06&host=68042c943591013ac2b2430a89b270f6af2c76d8dfd086a07176afe7c76c2c61&pii=S0925753520301922&tid=spdf-2823bc10-4a39-4f2b-8a32-7409653a6f56&sid=6bbf6c2f3a5ff545d91b09f2929365875304gxrqa&type=client&tsoh=d3d3LnNjaWVuY2VkaXJlY3QuY29t&rh=d3d3LnNjaWVuY2VkaXJlY3QuY29t&ua=1b130057565d500d535050&rr=a3094b5109a37504&cc=au] Footer, K. H. A., White, R. H., Park, J. N., Decker, M. R., Lutnick, A., & Sherman, S. G. (2020). Entry to Sex Trade and Long-Term Vulnerabilities of Female Sex Workers Who Enter the Sex Trade Before the Age of Eighteen. Journal of Urban Health, 97(3), 406–417. https://pmc.ncbi.nlm.nih.gov/articles/PMC7305278/ Harcourt, C. (2005). The many faces of sex work. Sexually Transmitted Infections, 81(3), 201–206. https://doi.org/10.1136/sti.2004.012468 ‌ Huglstad, M., Halvorsen, I. L. I., Jonsson, H., & Nielsen, K. T. (2020). “Some of us actually choose to do this”: The meanings of sex work from the perspective of female sex workers in Denmark. Journal of Occupational Science, 29(1), 1–14. https://doi.org/10.1080/14427591.2020.1830841. Ine Vanwesenbeeck (2013) Prostitution Push and Pull: Male and Female Perspectives, Journal of Sex Research, 50:1, 11-16, https://doi.org/10.1080/00224499.2012.696285 McNamara, R. (2016). The trouble with whorephobia. Journal of Religion and Culture, 27(1), 13-34. McKeever, N. (2025). Is Sex Work Inherently Gendered? Hypatia, 40(3), 633–652. doi:10.1017/hyp.2024.56 ‌Redwood, R. (2018). Myths and Realities of Male Sex Work. Red light labour: Sex work regulation, agency, and resistance, 167-180.[https://books.google.com.au/books?hl=en&lr=&id=8GJoDwAAQBAJ&oi=fnd&pg=PA167&dq=Myths+and+Realities+of+Male+Sex+Work&ots=mQOUglmuLU&sig=XHi0ybe124LABeHMulfVUMeYsxw#v=onepage&q=Myths%20and%20Realities%20of%20Male%20Sex%20Work&f=false] Sex worker - Wikipedia. (2023). Wikipedia.Org. https://en.wikipedia.org/wiki/Sex_worker}} ==External links== * [[doi:10.1017/hyp.2024.56|Is Sex Work Inherently Gendered?]] (Cambridge University Press){{ic|Use in references instead}} * [https://www.jrc-concordia.ca/wp-content/uploads/2017/01/Journal-of-Religion-and-Culture-Vol-27-no-1.pdf#page=13 The Trouble with Whorephobia] (Journal of Religion and Culture){{ic|Use in references instead}} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Sex]] [[Category:Motivation and emotion/Book/Work motivation]] 0crbvp6arf8dwyil15zgvsb7an7hwe3 2835281 2835280 2026-10-01T07:44:30Z U3261376 3106964 2835281 wikitext text/x-wiki {{title|Sex work motivation:<br>What motivates sex work and how does this impact worker experiences?}} __TOC__ == Overview == {{RoundBoxTop|theme=5}} [[File:“Sex workers rights are human rights” - Europride 2019.jpg|thumb|200px|'''Figure 1'''. Prostitution in Sao Paulo, Brazil]] '''What would you do if you found yourself in this scenario?''' Feeling lost and left with little money of your own, but you have to make ends meet. What will you do when you have to pay your rent? What if you have a child? Would you turn to sex work to make ends meet? If you did... would that make your rights to a safe and trustworthy work environment just disappear? Sex work itself is illegal. Having been driven to such means to make ends meet, you must register as self-employed to pay taxes, buy a house, or even just be considered an employee. [https://doi.org/10.1080/14427591.2020.1830841. (Huglstad et al., 2020)]. Sex workers rights activists proclaim that sex work is work, that they are not victims in need of help, and that they are entitled to any basic human right (see Figure 1). That in itself poses another scenario: What drives people into sex work? Is it finance and convenience? Or is it pleasure and fun? {{RoundBoxBottom}} [[Sex education|Sex]] work or [https://www.jstor.org/stable/pdf/10.1086/324390.pdf?casa_token=lfbXJZ0pqcQAAAAA:Y2KROCBvBcyTR_OkV9GU9nGAnh5lp0VKsrro0wiLqGF_MeXybi6-z3pvrxj97OM6GMvGv6r_Zbmt_s9RvHKDiUw3JzDhAPWvsSz3uzNI4nXa_mNdM5o prostitution] is a broad topic which includes many elements of sexual activities. In 2005, Harcourt defined sex work, "or prostitution, [as] the provision of sexual services for money or its equivalent," (Harcourt, 2005). To understand sex work as a concept it is important to first understand why people may turn to sex work for an income to begin with. This topic has been discussed at nauseum however often in a negative and clouded light. As stated in The Journal of Sex Research in 2013, it wasn't until the 1990's that literature that looked into this topic stopped looking at prostitutes as "predominantly... ‘‘evil characters’’ or ‘‘sick personalities.’’" (Vanwesenbeeck, 2013) and carrying a lense of ""simmering abhorrence, incomprehension, and fascination" (Vanwesenbeeck, 2013) towards these individuals. Some of the main concepts that will be unpacked below that motivates people to go into sex work are commonly, "financial, sexual, recreational motives, and coercion (i.e., trafficking)" (Vanwesenbeeck, 2013), and can often lead to negative workplace satisfaction. External influences like the adult entertainment industry and whorephobia can also heavily influence an individual's workplace satisfaction when working in the prostitution industry. To learn the in depth relationship between motivation to join sex work and the quality of said workplace satisfaction continue reading below. {{RoundBoxTop|theme=5}} '''Focus questions''' * What are the main driving forces causing people to turn to sex work? * What is the effect of the adult entertainment industry on sex workers? * What is the condition of work place satisfaction for sex workers? * How does whorephobia and others' actions towards sex workers effect their work place? * Do those who turn to sex work for pleasure have different experiences to those who do so for money alone? {{RoundBoxBottom}} == Driving forces pushing people towards sex work == - Do those who turn to sex work for pleasure have different experiences to those who do so for money alone? === Age as a factor === - why do young people enter the sex work industry, how does that change workplace satisfaction? - how does parenting influence age related sex work? - do older individuals in the sex work industry experience more angism in their workplace? === Maslow's hierarchy of needs === - looking at maslows hierarchy of needs, what may cause people to turn to sex work? - does peoples standing on the hierarchy influence their workplace satisfaction? === Intrinsic vs extrinsic motivation === - intrinsic vs extrinsic factors - how does their treatment change from higher to lower socioeconomic places == How motivations to join the sex work industry differ from men to women == {| class="wikitable" |+Percentages showing [https://www.annualreviews.org/docserver/fulltext/psych/65/1/annurev-psych-010213-115057.pdf?expires=1790841225&id=id&accname=au&checksum=112378A7023548A83B7DDDA7288D0EA0 gender differences] in paying for vs working in sex ! !Participate in sex work !Pay for sex work |- |Men |20% |12% |- |Women |80% |1% |} === Male sex workers === - why are they less prevelent in the public eye? - why are they not degraded as much as female workers? - do men turn to sex work to fulfill their own physical needs? === Female sex workers === - why are they more prevelent in the public eye? - why are they degraded more then male workers? - do women turn to sex work to fulfill their own physical needs?<quiz display="simple"> {Knowing what motivates people to go into sex work, if you found yourself in their shoes would you do it too?: |type="()"} + Yes - No </quiz> == The adult entertainment industry and its relationship to sex workers == - does this carer add unrealistic expectations towards sex workers and what people will ask to recieve? - looking into detail about how the adult entertainment industry can glorify sex work and how that may motivate people to join the industry. == Work place satisfaction for sex workers == - is there an element of sexual satisfaction which motivates sex workers? - is there a difference between men and women? - how to sexworkers respond to violence in their line of work and how may that motivate their actions? == Whorephobia and how it influences work place satisfaction == - how do unfavorable opinions of sex workers effect motivation and how does that relate to workplace satisfaction? - how does the prevelence of this violence motivate sex workers to continue in their chosen carer path? - how does [https://www.jrc-concordia.ca/wp-content/uploads/2017/01/Journal-of-Religion-and-Culture-Vol-27-no-1.pdf#page=13 whorephobia] effect workplace satisfaction?<quiz display="simple"> {More men then women experience sexual violence as a sex worker: |type="()"} - True + False {There are more women in the sex trade then there are men: |type="()"} - True + False </quiz> ==Conclusion== Through this chapter we have spoken about the different motivations that drives people into sex work and how that can influence work place experiences. We have done this by assesing how age and gender can influence motivations as well as what circumstances can effect those drives. - summerise the different motivations that lead to sex work, considering gender and age. - summerise how socioeconomic factors influence sex worker experiences, including prejudices. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== * [[Maslow's hierarchy of needs]] (Wikiversity) * [[Sex education]] (Wikiversity) * [[Motivation and emotion/Book/2015/Sex worker motivation|Sex work motivation]] (Book chapter, 2015) ==References == {{Hanging indent|1=Arnold, K. A., Turner, N., Barling, J., & Iverson, R. D. (2020). Feeling safe while doing sex work: Motivation for entering sex work moderates the relationship between perceptions of physical danger and desire to leave sex work. Safety science, 129, 104795.[https://pdf.sciencedirectassets.com/271730/1-s2.0-S0925753520X00063/1-s2.0-S0925753520301922/main.pdf?X-Amz-Security-Token=IQoJb3JpZ2luX2VjEDgaCXVzLWVhc3QtMSJIMEYCIQDLwNUlkBLTVH2W9sUG%2FL8xBiniafqj2YjDThRYfM8j7gIhAPpb6usou%2FCfun2GlN94HXvsSkZFNyb27ndcS5LYkmOqKrIFCAEQBRoMMDU5MDAzNTQ2ODY1IgwVqu3mdLMxIbQQT4EqjwVyEzAMhHQLz8i1mRyce46T7kq8nFGMPfsWbvGbIjwD5sTztgejH2H6uoazHE3ceLn%2BHJAMU2gcjulIYqlqCSyvPuWe%2BScfjOHfBfQZnctFdUl2oWqaahIi9YzAVcTWeftoZk%2FylcCfLerGklhqD7HwVv2vZdBzsx94xmqQ1V1uUbIbAIkJ30NfSj00z1cSaUL1q96wM120kL%2By3Fd%2FYRnMyLzgn343yVJM%2BYWksKgOiezOVEa%2BhmIbNUYzcpb%2Fkcah8UWIgZWXjdLp2fZTJB2yCYbj091PqbNLxbKvPvqaCnGI%2BSTaCPpupfKIdR02m2jepxiZI8%2FZrLGy71f0vYzU%2Be120AQZZCPdjTZZAOP9xB%2Bvfpp48EyclSYmN0rSn2bZcMSiqosJl%2Bz6BiiW3J9SmbZXGNWeECGltEiG%2FP%2FRiZ0uB94c2nIGVzBsfJ4fe7UAD3mlWR9UBCT5FirlPE3Dzap%2BH1xnOe%2BGN481xmH1YSoL3FACDW8J5HUez%2BURv5vTzFDq4nON4cFWhMdgPNfu8v%2BjU35utqWccWAfsows5CFE%2FdiNDUQa7EI1XwF00wtRp2k06DjOWBl%2FggL2duXPWFHHaJnOEovHXAGzQUl%2FzBocvEbkU%2BstJU3AjUwCqbrDZRVZay0dd7OLQ6NCZTFxvZrhEoOwYukzgYt02XtXs23oNKc8QK8jPBsjSx8K1Xj9V9tPB5eBTptias5DuJnme5GPMo0H0rehhAFIbH1iz5aLEJ2WFAs2YMajNB9b8K9hsdcsufqw3IWvDgGjJl491SPFYv4AkHpfF%2B2OEEmH9hDMp3rnzv686gQ5u2%2FmSKrDsChJ2JSpJUuTnHdHBZrk%2Fwzx%2BpsfpZ4zLVgKx0K6MJOGtdQGOrAB7mHiroFpJKweD4wGdVv4twWKj65wn3ZS715WCDMXnol3ZjKerxKwtTiAS8MYNXREK5yRc6R%2BCtHqgkfO1QIL6y35fyD0iOWFO6ZYrI1IePcEupQe4Ao%2B8i5%2Bz9PydRXrVVCjz1A9o6ZcLX9dN59jVDboJOpZsOpXxuErU9LEKNKGTqVoHfJq%2FpKSdZkltmLsDvSAgBZORP2gpikUUQyl6A0CxzJ3SGD1ZrqXN39XlWY%3D&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20260825T084050Z&X-Amz-SignedHeaders=host&X-Amz-Expires=300&X-Amz-Credential=ASIAQ3PHCVTYZDNOMNKH%2F20260825%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=222054776072dd684a9220ca5e137f808570de2f4b46a74fc1fac36b8741d31e&hash=9077aea1050680fe483f80515f312051569ddf0b7a50ba90c1511bc6ef136d06&host=68042c943591013ac2b2430a89b270f6af2c76d8dfd086a07176afe7c76c2c61&pii=S0925753520301922&tid=spdf-2823bc10-4a39-4f2b-8a32-7409653a6f56&sid=6bbf6c2f3a5ff545d91b09f2929365875304gxrqa&type=client&tsoh=d3d3LnNjaWVuY2VkaXJlY3QuY29t&rh=d3d3LnNjaWVuY2VkaXJlY3QuY29t&ua=1b130057565d500d535050&rr=a3094b5109a37504&cc=au] Footer, K. H. A., White, R. H., Park, J. N., Decker, M. R., Lutnick, A., & Sherman, S. G. (2020). Entry to Sex Trade and Long-Term Vulnerabilities of Female Sex Workers Who Enter the Sex Trade Before the Age of Eighteen. Journal of Urban Health, 97(3), 406–417. https://pmc.ncbi.nlm.nih.gov/articles/PMC7305278/ Harcourt, C. (2005). The many faces of sex work. Sexually Transmitted Infections, 81(3), 201–206. https://doi.org/10.1136/sti.2004.012468 ‌ Huglstad, M., Halvorsen, I. L. I., Jonsson, H., & Nielsen, K. T. (2020). “Some of us actually choose to do this”: The meanings of sex work from the perspective of female sex workers in Denmark. Journal of Occupational Science, 29(1), 1–14. https://doi.org/10.1080/14427591.2020.1830841. Ine Vanwesenbeeck (2013) Prostitution Push and Pull: Male and Female Perspectives, Journal of Sex Research, 50:1, 11-16, https://doi.org/10.1080/00224499.2012.696285 McNamara, R. (2016). The trouble with whorephobia. Journal of Religion and Culture, 27(1), 13-34. McKeever, N. (2025). Is Sex Work Inherently Gendered? Hypatia, 40(3), 633–652. doi:10.1017/hyp.2024.56 ‌Redwood, R. (2018). Myths and Realities of Male Sex Work. Red light labour: Sex work regulation, agency, and resistance, 167-180.[https://books.google.com.au/books?hl=en&lr=&id=8GJoDwAAQBAJ&oi=fnd&pg=PA167&dq=Myths+and+Realities+of+Male+Sex+Work&ots=mQOUglmuLU&sig=XHi0ybe124LABeHMulfVUMeYsxw#v=onepage&q=Myths%20and%20Realities%20of%20Male%20Sex%20Work&f=false] Sex worker - Wikipedia. (2023). Wikipedia.Org. https://en.wikipedia.org/wiki/Sex_worker}} ==External links== [https://www.jstor.org/stable/pdf/10.1086/324390.pdf?casa_token=lfbXJZ0pqcQAAAAA:Y2KROCBvBcyTR_OkV9GU9nGAnh5lp0VKsrro0wiLqGF_MeXybi6-z3pvrxj97OM6GMvGv6r_Zbmt_s9RvHKDiUw3JzDhAPWvsSz3uzNI4nXa_mNdM5o A Theory of Prostitution] (The University of Chicago Press) [https://www.annualreviews.org/docserver/fulltext/psych/65/1/annurev-psych-010213-115057.pdf?expires=1790841225&id=id&accname=au&checksum=112378A7023548A83B7DDDA7288D0EA0 Gender Similarities and Differences] (The Annual Review of Psychology) ‌ [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Sex]] [[Category:Motivation and emotion/Book/Work motivation]] s35eabbha1ijftc6xe5ols7rqnyvr2w 2835283 2835281 2026-10-01T08:07:04Z U3261376 3106964 2835283 wikitext text/x-wiki {{title|Sex work motivation:<br>What motivates sex work and how does this impact worker experiences?}} __TOC__ == Overview == {{RoundBoxTop|theme=5}} [[File:“Sex workers rights are human rights” - Europride 2019.jpg|thumb|200px|'''Figure 1'''. Prostitution in Sao Paulo, Brazil]] '''What would you do if you found yourself in this scenario?''' Feeling lost and left with little money of your own, but you have to make ends meet. What will you do when you have to pay your rent? What if you have a child? Would you turn to sex work to make ends meet? If you did... would that make your rights to a safe and trustworthy work environment just disappear? Sex work itself is illegal. Having been driven to such means to make ends meet, you must register as self-employed to pay taxes, buy a house, or even just be considered an employee. [https://doi.org/10.1080/14427591.2020.1830841. (Huglstad et al., 2020)]. Sex workers rights activists proclaim that sex work is work, that they are not victims in need of help, and that they are entitled to any basic human right (see Figure 1). That in itself poses another scenario: What drives people into sex work? Is it finance and convenience? Or is it pleasure and fun? {{RoundBoxBottom}} [[Sex education|Sex]] work or [https://www.jstor.org/stable/pdf/10.1086/324390.pdf?casa_token=lfbXJZ0pqcQAAAAA:Y2KROCBvBcyTR_OkV9GU9nGAnh5lp0VKsrro0wiLqGF_MeXybi6-z3pvrxj97OM6GMvGv6r_Zbmt_s9RvHKDiUw3JzDhAPWvsSz3uzNI4nXa_mNdM5o prostitution] is a broad topic which includes many elements of sexual activities. In 2005, Harcourt defined sex work, "or prostitution, [as] the provision of sexual services for money or its equivalent," ([https://pmc.ncbi.nlm.nih.gov/articles/PMC1744977/pdf/v081p00201.pdf Harcourt, 2005]). To understand sex work as a concept it is important to first understand why people may turn to sex work for an income to begin with. This topic has been discussed at nauseum however often in a negative and clouded light. As stated in The Journal of Sex Research in 2013, it wasn't until the 1990's that literature that looked into this topic stopped looking at prostitutes as "predominantly... ‘‘evil characters’’ or ‘‘sick personalities.’’" ([https://www.tandfonline.com/doi/pdf/10.1080/00224499.2012.696285?casa_token=wgasXeCYwFAAAAAA:0Iuwx4QzcbYP0ZAj6GISEX5oDHr4t-phuo4VUxmwfMIVjTrLXaTBhIoYpXtC9r0WaeYaxII3ObSZ Vanwesenbeeck, 2013]) and carrying a lense of ""simmering abhorrence, incomprehension, and fascination" (Vanwesenbeeck, 2013) towards these individuals. Some of the main concepts that will be unpacked below that motivates people to go into sex work are commonly, "financial, sexual, recreational motives, and coercion (i.e., [https://www.jstor.org/stable/pdf/30048506.pdf?casa_token=pqlPp6XrnF0AAAAA:SFSvr6r_WKbLtO638dPPYk35oZFz9anPcub1Be7iUjk9AMX7a4h73yPLMJ6efSSxWVK7Az4Upc3UgohFYtht3QViGNIyTXPWCkBaY5lhRS_RGNFzUoA trafficking])" (Vanwesenbeeck, 2013), and can often lead to negative workplace satisfaction. External influences like the adult entertainment industry and whorephobia can also heavily influence an individual's workplace satisfaction when working in the prostitution industry. To learn the in depth relationship between motivation to join sex work and the quality of said workplace satisfaction continue reading below. {{RoundBoxTop|theme=5}} '''Focus questions''' * What are the main driving forces causing people to turn to sex work? * What is the effect of the adult entertainment industry on sex workers? * What is the condition of work place satisfaction for sex workers? * How does whorephobia and others' actions towards sex workers effect their work place? * Do those who turn to sex work for pleasure have different experiences to those who do so for money alone? {{RoundBoxBottom}} == Driving forces pushing people towards sex work == - Do those who turn to sex work for pleasure have different experiences to those who do so for money alone? === Age as a factor === - why do young people enter the sex work industry, how does that change workplace satisfaction? - how does parenting influence age related sex work? - do older individuals in the sex work industry experience more angism in their workplace? === Maslow's hierarchy of needs === - looking at maslows hierarchy of needs, what may cause people to turn to sex work? - does peoples standing on the hierarchy influence their workplace satisfaction? === Intrinsic vs extrinsic motivation === - intrinsic vs extrinsic factors - how does their treatment change from higher to lower socioeconomic places == How motivations to join the sex work industry differ from men to women == {| class="wikitable" |+Percentages showing [https://www.annualreviews.org/docserver/fulltext/psych/65/1/annurev-psych-010213-115057.pdf?expires=1790841225&id=id&accname=au&checksum=112378A7023548A83B7DDDA7288D0EA0 gender differences] in paying for vs working in sex ! !Participate in sex work !Pay for sex work |- |Men |20% |12% |- |Women |80% |1% |} === Male sex workers === - why are they less prevelent in the public eye? - why are they not degraded as much as female workers? - do men turn to sex work to fulfill their own physical needs? === Female sex workers === - why are they more prevelent in the public eye? - why are they degraded more then male workers? - do women turn to sex work to fulfill their own physical needs?<quiz display="simple"> {Knowing what motivates people to go into sex work, if you found yourself in their shoes would you do it too?: |type="()"} + Yes - No </quiz> == The adult entertainment industry and its relationship to sex workers == - does this carer add unrealistic expectations towards sex workers and what people will ask to recieve? - looking into detail about how the adult entertainment industry can glorify sex work and how that may motivate people to join the industry. == Work place satisfaction for sex workers == - is there an element of sexual satisfaction which motivates sex workers? - is there a difference between men and women? - how to sexworkers respond to violence in their line of work and how may that motivate their actions? == Whorephobia and how it influences work place satisfaction == - how do unfavorable opinions of sex workers effect motivation and how does that relate to workplace satisfaction? - how does the prevelence of this violence motivate sex workers to continue in their chosen carer path? - how does [https://www.jrc-concordia.ca/wp-content/uploads/2017/01/Journal-of-Religion-and-Culture-Vol-27-no-1.pdf#page=13 whorephobia] effect workplace satisfaction?<quiz display="simple"> {More men then women experience sexual violence as a sex worker: |type="()"} - True + False {There are more women in the sex trade then there are men: |type="()"} - True + False </quiz> ==Conclusion== Through this chapter we have spoken about the different motivations that drives people into sex work and how that can influence work place experiences. We have done this by assesing how age and gender can influence motivations as well as what circumstances can effect those drives. - summerise the different motivations that lead to sex work, considering gender and age. - summerise how socioeconomic factors influence sex worker experiences, including prejudices. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== * [[Maslow's hierarchy of needs]] (Wikiversity) * [[Sex education]] (Wikiversity) * [[Motivation and emotion/Book/2015/Sex worker motivation|Sex work motivation]] (Book chapter, 2015) ==References == {{Hanging indent|1=Arnold, K. A., Turner, N., Barling, J., & Iverson, R. D. (2020). Feeling safe while doing sex work: Motivation for entering sex work moderates the relationship between perceptions of physical danger and desire to leave sex work. Safety science, 129, 104795.[https://pdf.sciencedirectassets.com/271730/1-s2.0-S0925753520X00063/1-s2.0-S0925753520301922/main.pdf?X-Amz-Security-Token=IQoJb3JpZ2luX2VjEDgaCXVzLWVhc3QtMSJIMEYCIQDLwNUlkBLTVH2W9sUG%2FL8xBiniafqj2YjDThRYfM8j7gIhAPpb6usou%2FCfun2GlN94HXvsSkZFNyb27ndcS5LYkmOqKrIFCAEQBRoMMDU5MDAzNTQ2ODY1IgwVqu3mdLMxIbQQT4EqjwVyEzAMhHQLz8i1mRyce46T7kq8nFGMPfsWbvGbIjwD5sTztgejH2H6uoazHE3ceLn%2BHJAMU2gcjulIYqlqCSyvPuWe%2BScfjOHfBfQZnctFdUl2oWqaahIi9YzAVcTWeftoZk%2FylcCfLerGklhqD7HwVv2vZdBzsx94xmqQ1V1uUbIbAIkJ30NfSj00z1cSaUL1q96wM120kL%2By3Fd%2FYRnMyLzgn343yVJM%2BYWksKgOiezOVEa%2BhmIbNUYzcpb%2Fkcah8UWIgZWXjdLp2fZTJB2yCYbj091PqbNLxbKvPvqaCnGI%2BSTaCPpupfKIdR02m2jepxiZI8%2FZrLGy71f0vYzU%2Be120AQZZCPdjTZZAOP9xB%2Bvfpp48EyclSYmN0rSn2bZcMSiqosJl%2Bz6BiiW3J9SmbZXGNWeECGltEiG%2FP%2FRiZ0uB94c2nIGVzBsfJ4fe7UAD3mlWR9UBCT5FirlPE3Dzap%2BH1xnOe%2BGN481xmH1YSoL3FACDW8J5HUez%2BURv5vTzFDq4nON4cFWhMdgPNfu8v%2BjU35utqWccWAfsows5CFE%2FdiNDUQa7EI1XwF00wtRp2k06DjOWBl%2FggL2duXPWFHHaJnOEovHXAGzQUl%2FzBocvEbkU%2BstJU3AjUwCqbrDZRVZay0dd7OLQ6NCZTFxvZrhEoOwYukzgYt02XtXs23oNKc8QK8jPBsjSx8K1Xj9V9tPB5eBTptias5DuJnme5GPMo0H0rehhAFIbH1iz5aLEJ2WFAs2YMajNB9b8K9hsdcsufqw3IWvDgGjJl491SPFYv4AkHpfF%2B2OEEmH9hDMp3rnzv686gQ5u2%2FmSKrDsChJ2JSpJUuTnHdHBZrk%2Fwzx%2BpsfpZ4zLVgKx0K6MJOGtdQGOrAB7mHiroFpJKweD4wGdVv4twWKj65wn3ZS715WCDMXnol3ZjKerxKwtTiAS8MYNXREK5yRc6R%2BCtHqgkfO1QIL6y35fyD0iOWFO6ZYrI1IePcEupQe4Ao%2B8i5%2Bz9PydRXrVVCjz1A9o6ZcLX9dN59jVDboJOpZsOpXxuErU9LEKNKGTqVoHfJq%2FpKSdZkltmLsDvSAgBZORP2gpikUUQyl6A0CxzJ3SGD1ZrqXN39XlWY%3D&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20260825T084050Z&X-Amz-SignedHeaders=host&X-Amz-Expires=300&X-Amz-Credential=ASIAQ3PHCVTYZDNOMNKH%2F20260825%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=222054776072dd684a9220ca5e137f808570de2f4b46a74fc1fac36b8741d31e&hash=9077aea1050680fe483f80515f312051569ddf0b7a50ba90c1511bc6ef136d06&host=68042c943591013ac2b2430a89b270f6af2c76d8dfd086a07176afe7c76c2c61&pii=S0925753520301922&tid=spdf-2823bc10-4a39-4f2b-8a32-7409653a6f56&sid=6bbf6c2f3a5ff545d91b09f2929365875304gxrqa&type=client&tsoh=d3d3LnNjaWVuY2VkaXJlY3QuY29t&rh=d3d3LnNjaWVuY2VkaXJlY3QuY29t&ua=1b130057565d500d535050&rr=a3094b5109a37504&cc=au] Footer, K. H. A., White, R. H., Park, J. N., Decker, M. R., Lutnick, A., & Sherman, S. G. (2020). Entry to Sex Trade and Long-Term Vulnerabilities of Female Sex Workers Who Enter the Sex Trade Before the Age of Eighteen. Journal of Urban Health, 97(3), 406–417. https://pmc.ncbi.nlm.nih.gov/articles/PMC7305278/ Harcourt, C. (2005). The many faces of sex work. Sexually Transmitted Infections, 81(3), 201–206. https://doi.org/10.1136/sti.2004.012468 ‌ Huglstad, M., Halvorsen, I. L. I., Jonsson, H., & Nielsen, K. T. (2020). “Some of us actually choose to do this”: The meanings of sex work from the perspective of female sex workers in Denmark. Journal of Occupational Science, 29(1), 1–14. https://doi.org/10.1080/14427591.2020.1830841. Ine Vanwesenbeeck (2013) Prostitution Push and Pull: Male and Female Perspectives, Journal of Sex Research, 50:1, 11-16, https://doi.org/10.1080/00224499.2012.696285 McNamara, R. (2016). The trouble with whorephobia. Journal of Religion and Culture, 27(1), 13-34. McKeever, N. (2025). Is Sex Work Inherently Gendered? Hypatia, 40(3), 633–652. doi:10.1017/hyp.2024.56 ‌Redwood, R. (2018). Myths and Realities of Male Sex Work. Red light labour: Sex work regulation, agency, and resistance, 167-180.[https://books.google.com.au/books?hl=en&lr=&id=8GJoDwAAQBAJ&oi=fnd&pg=PA167&dq=Myths+and+Realities+of+Male+Sex+Work&ots=mQOUglmuLU&sig=XHi0ybe124LABeHMulfVUMeYsxw#v=onepage&q=Myths%20and%20Realities%20of%20Male%20Sex%20Work&f=false] Sex worker - Wikipedia. (2023). Wikipedia.Org. https://en.wikipedia.org/wiki/Sex_worker}} ==External links== [https://www.jstor.org/stable/pdf/10.1086/324390.pdf?casa_token=lfbXJZ0pqcQAAAAA:Y2KROCBvBcyTR_OkV9GU9nGAnh5lp0VKsrro0wiLqGF_MeXybi6-z3pvrxj97OM6GMvGv6r_Zbmt_s9RvHKDiUw3JzDhAPWvsSz3uzNI4nXa_mNdM5o A Theory of Prostitution] (The University of Chicago Press) [https://www.annualreviews.org/docserver/fulltext/psych/65/1/annurev-psych-010213-115057.pdf?expires=1790841225&id=id&accname=au&checksum=112378A7023548A83B7DDDA7288D0EA0 Gender Similarities and Differences] (The Annual Review of Psychology) [https://www.jstor.org/stable/pdf/30048506.pdf?refreqid=fastly-default%3Abdd06e603789b9df6429bacfd93907fe&ab_segments=&initiator=&acceptTC=1 Human Trafficking] (JSTOR)‌ [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Sex]] [[Category:Motivation and emotion/Book/Work motivation]] kfs9505gk6f9t3iqizp2xnfp6q5l3mp 0 331149 2835247 2835137 2026-10-01T01:12:04Z U3254168 3106320 2835247 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Jurors only.{{expand}}]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). Kahhale et al. (2026) proposed that individual differences influence how much empathy a person feels or can feel. In line with this, Garvey (2000) proposed empathy as a [[wiktionary:character_trait|character trait]].<quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == * Evidence of the influence of victim impact statements is inconsistent. In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements influenced sentencing. Research by Phalen et al., (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. * Having similar experiences to victims, such as sexual abuse, leads to higher empathy, a higher likelihood of finding the defendant guilty and harsher sentences (Kahhale et al., 2026). * Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). * Jurors are more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == * When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. * Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). * Haegerich & Bottoms (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (INSERT REFERENCE). * Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between emotion display, identity and behaviour in that people use evaluation, potency and activity to interpret identities (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. Journal of Experimental Social Psychology, 13(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] rvjsxd8fgguxfuerc4zivsdjba3jmjs 2835251 2835247 2026-10-01T02:03:44Z U3254168 3106320 /* Empathy with defendants */ 2835251 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Jurors only.{{expand}}]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). Kahhale et al. (2026) proposed that individual differences influence how much empathy a person feels or can feel. In line with this, Garvey (2000) proposed empathy as a [[wiktionary:character_trait|character trait]].<quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == * Evidence of the influence of victim impact statements is inconsistent. In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements influenced sentencing. Research by Phalen et al., (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. * Having similar experiences to victims, such as sexual abuse, leads to higher empathy, a higher likelihood of finding the defendant guilty and harsher sentences (Kahhale et al., 2026). * Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). * Jurors are more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == * When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. * Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). * Haegerich & Bottoms (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (INSERT REFERENCE). * Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). * The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examine this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examine the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. Zhang et al.'s (2025) study found that third-party punishers decisions to punish are primarily influenced by perceptions of fairness, however the decision of the intensity of punishment is determined by empathy, consistent with the empathy-altruism hypothesis. <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between emotion display, identity and behaviour in that people use evaluation, potency and activity to interpret identities (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. Journal of Experimental Social Psychology, 13(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] 4gbyocbk9jvksbs6f2y2nsiq6lfpjc8 2835253 2835251 2026-10-01T02:22:16Z U3254168 3106320 /* Empathy with defendants */ 2835253 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Jurors only.{{expand}}]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). Kahhale et al. (2026) proposed that individual differences influence how much empathy a person feels or can feel. In line with this, Garvey (2000) proposed empathy as a [[wiktionary:character_trait|character trait]].<quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == * Evidence of the influence of victim impact statements is inconsistent. In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements influenced sentencing. Research by Phalen et al., (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. * Having similar experiences to victims, such as sexual abuse, leads to higher empathy, a higher likelihood of finding the defendant guilty and harsher sentences (Kahhale et al., 2026). * Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). * Jurors are more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == * When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. * Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). * Haegerich & Bottoms (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (INSERT REFERENCE). * Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). * The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examine this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examine the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the Ultimatum Game, which was originally proposed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder (Güth et al., 1982). The proposer is given money, of which they have to offer some to the responder and the responder has to take it or leave it. If the responder accepts, the money is split as the proposer proposed. If the responder rejects, neither player gets anything. Zhang et al.'s (2025) study was conducted with 31 university students, who observed a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split in the Ultimatum Game, where the unfair variable consisted of an uneven split, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participant received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment. <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between emotion display, identity and behaviour in that people use evaluation, potency and activity to interpret identities (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. Journal of Experimental Social Psychology, 13(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] n1kelavqbss4f0awt2f5980g4fg71p4 2835254 2835253 2026-10-01T02:23:37Z U3254168 3106320 /* Empathy with defendants */ 2835254 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Jurors only.{{expand}}]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). Kahhale et al. (2026) proposed that individual differences influence how much empathy a person feels or can feel. In line with this, Garvey (2000) proposed empathy as a [[wiktionary:character_trait|character trait]].<quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == * Evidence of the influence of victim impact statements is inconsistent. In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements influenced sentencing. Research by Phalen et al., (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. * Having similar experiences to victims, such as sexual abuse, leads to higher empathy, a higher likelihood of finding the defendant guilty and harsher sentences (Kahhale et al., 2026). * Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). * Jurors are more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (INSERT REFERENCE). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examine this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examine the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the Ultimatum Game, which was originally proposed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder (Güth et al., 1982). The proposer is given money, of which they have to offer some to the responder and the responder has to take it or leave it. If the responder accepts, the money is split as the proposer proposed. If the responder rejects, neither player gets anything. Zhang et al.'s (2025) study was conducted with 31 university students, who observed a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split in the Ultimatum Game, where the unfair variable consisted of an uneven split, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participant received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment. <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between emotion display, identity and behaviour in that people use evaluation, potency and activity to interpret identities (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. Journal of Experimental Social Psychology, 13(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] 20afhus72swld6nq5cxmadq8e3udnwt 2835256 2835254 2026-10-01T02:33:43Z U3254168 3106320 2835256 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Jurors only.{{expand}}]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). Kahhale et al. (2026) proposed that individual differences influence how much empathy a person feels or can feel. In line with this, Garvey (2000) proposed empathy as a [[wiktionary:character_trait|character trait]].<quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == * Evidence of the influence of victim impact statements is inconsistent. In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements influenced sentencing. Research by Phalen et al., (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. * Having similar experiences to victims, such as sexual abuse, leads to higher empathy, a higher likelihood of finding the defendant guilty and harsher sentences (Kahhale et al., 2026). * Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). * Jurors are more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (INSERT REFERENCE). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the Ultimatum Game, which was originally proposed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given money, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the money is split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split in the Ultimatum Game, where the unfair variable consisted of an uneven split, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between emotion display, identity and behaviour in that people use evaluation, potency and activity to interpret identities (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. Journal of Experimental Social Psychology, 13(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] 27cpburjva9s3oz8y633lox1mvucn32 2835257 2835256 2026-10-01T02:34:20Z U3254168 3106320 /* Attribution theory */ 2835257 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Jurors only.{{expand}}]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). Kahhale et al. (2026) proposed that individual differences influence how much empathy a person feels or can feel. In line with this, Garvey (2000) proposed empathy as a [[wiktionary:character_trait|character trait]].<quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == * Evidence of the influence of victim impact statements is inconsistent. In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements influenced sentencing. Research by Phalen et al., (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. * Having similar experiences to victims, such as sexual abuse, leads to higher empathy, a higher likelihood of finding the defendant guilty and harsher sentences (Kahhale et al., 2026). * Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). * Jurors are more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the Ultimatum Game, which was originally proposed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given money, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the money is split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split in the Ultimatum Game, where the unfair variable consisted of an uneven split, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between emotion display, identity and behaviour in that people use evaluation, potency and activity to interpret identities (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. Journal of Experimental Social Psychology, 13(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] 867muu0x4u0ep9295g0u6ba6mw0j6dl 2835262 2835257 2026-10-01T03:12:10Z U3254168 3106320 /* Empathy with victims */ 2835262 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Jurors only.{{expand}}]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). Kahhale et al. (2026) proposed that individual differences influence how much empathy a person feels or can feel. In line with this, Garvey (2000) proposed empathy as a [[wiktionary:character_trait|character trait]].<quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathy with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim after a verdict is reached but before sentencing, where the victim details the impact of their experience (). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). However evidence of the influence of victim impact statements on empathy and jury decision-making is inconsistent. In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements influenced sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. Despite inconsistent findings of the impact of victim impact statements there is evidence that having similar experiences to victims, such as sexual abuse, leads to higher empathy, a higher likelihood of finding the defendant guilty and harsher sentences (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the Ultimatum Game, which was originally proposed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given money, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the money is split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split in the Ultimatum Game, where the unfair variable consisted of an uneven split, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between emotion display, identity and behaviour in that people use evaluation, potency and activity to interpret identities (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. Journal of Experimental Social Psychology, 13(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] g67jad85yo0p485k4id24f9t8ietxgh 2835263 2835262 2026-10-01T03:14:00Z U3254168 3106320 /* Empathy with victims */ 2835263 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Jurors only.{{expand}}]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). Kahhale et al. (2026) proposed that individual differences influence how much empathy a person feels or can feel. In line with this, Garvey (2000) proposed empathy as a [[wiktionary:character_trait|character trait]].<quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathy with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim after a verdict is reached but before sentencing, where the victim details the impact of their experience (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). However evidence of the influence of victim impact statements on empathy and jury decision-making is inconsistent. In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements influenced sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. Despite inconsistent findings of the impact of victim impact statements there is evidence that having similar experiences to victims, such as sexual abuse, leads to higher empathy, a higher likelihood of finding the defendant guilty and harsher sentences (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the Ultimatum Game, which was originally proposed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given money, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the money is split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split in the Ultimatum Game, where the unfair variable consisted of an uneven split, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between emotion display, identity and behaviour in that people use evaluation, potency and activity to interpret identities (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. Journal of Experimental Social Psychology, 13(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] 3j0el63aojlfi4m8fk757q0y7b3ouoh 2835265 2835263 2026-10-01T03:27:06Z U3254168 3106320 /* Empathy with victims */ 2835265 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Jurors only.{{expand}}]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). Kahhale et al. (2026) proposed that individual differences influence how much empathy a person feels or can feel. In line with this, Garvey (2000) proposed empathy as a [[wiktionary:character_trait|character trait]].<quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the Ultimatum Game, which was originally proposed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given money, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the money is split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split in the Ultimatum Game, where the unfair variable consisted of an uneven split, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between emotion display, identity and behaviour in that people use evaluation, potency and activity to interpret identities (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. Journal of Experimental Social Psychology, 13(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] 17xif5k6bweorq56eaqb71qkmsie0ee 0 331231 2835171 2833227 2026-09-30T12:47:52Z SJPiper 3107750 /* Overview */ 2835171 wikitext text/x-wiki {{title|Artificial intelligence and academic motivation:<br>How does artificial intelligence influence students’ motivation to learn, engage, and achieve?}} __TOC__ ==Overview== {{RoundBoxTop|theme=5}} [[File:Artificial intelligence in education.jpg|thumb|'''Figure 1'''. An image of an AI robot teaching a young student]] ;Imagine this... You're sitting at your desk. On your desk is your open laptop with an empty blank page which is for an assignment that is due tomorrow night. You've been putting it off for weeks now, knowing you will have to do several hours to research, plan and write it out. You just felt too unmotivated to write it, thinking you would do it the next day which happened to become a regular occurance. You're just not sure what to do. You only have tonight and not many hours left. You then think about your friends, they had recently gotten into using AI to help write a lot of their work. They had always recommended you to use it, but you were never that interested in it, prefering to use your own work. However, the situation was dire, and the sound of AI seemed very good right now. You get onto ChatGPT and start to enter in the assignment questions. After a few hours you're done. You finished your assignment on time. AI had significantly helped write and perfect a lot of the material. You find that it was so much easier to just do this than to bother to research for days on end. Maybe you'd do this next time too. {{RoundBoxBottom}} * [[w:Artificial_intelligence|Artifical Intelligence]] (AI) is often {{fact}} defined as technology that stimulates human intelligent behaviours, and is trained to learn human behaviours such as learning, judgement, and decision-making (Zhan & Lu, 2021). AI is rapidly developing and creating new advancements regularly in recent years, particularly in various aspects in the education systems (Pertiwi et al., 2024). AI has been making its way into classrooms to help further aid learning in everyday student learning habits to help with overall student achievement and motivation to learn. * It is important to understand the recent emerging involvement of AI in academic settings as it while there are positive effects of using AI platforms, there are still issues to be addressed such as over reliance of the platforms. Being too over reliant on generative AI can lead to the habitual avoidance of using ones cognitive and critical thinking skills, particulary in the development of children (Fan et al., 2024). * It is also important for us {{ic|Use 3rd person point of view}} all to understand what motivates students to learn in the first place, and by doing that undertand how we can ethically keep utilising the use of AI in everyday academic settings. By doing so, it is possible to promote students motivation to learn, and be able to raise their overall learning achievement (Hmoud et al., 2024). {{RoundBoxTop|theme=5}} '''Focus questions''' * What factors influence students' motivation to learn? * What are the positive and negative effects of AI on students' motivation? * How has AI changed the way students approach learning? * How does reliance on AI influence students' learning habits? {{RoundBoxBottom}} == What motivates students? == {{ic|Include an introductory paragraph before branching into sub-sections}} === Understanding motivation === * [[Motivation]] is split into two main sub-categories (Legault, 2016). * Entrinsic motivation is often defined as when people perform a task in order to attain an outcome that is separable from the action itself, like getting a reward (Legault, 2016). * Intrinsic motivation is defined as when people are curious and interested, while seeking out challenges and developing their skills and knowlege without the presence of a reward (Domenico & Ryan, 2017; Legault, 2016). === Known factors influencing motivation to learn === * School management has been found to be highly influential on students learning in school, showing that encouragement to be diligent and loving to do what you are doing is beneficial in motivation in shcool settings (Hodis & Hodis, 2022.) * Another motivation is having good social support around people encourages them to motivate not only themselves, but also each other (Hodis & Hodis, 2022). Having negative influences around you decreases motivation. * One of the most important factors that can increase motivation is simply having a well educated teacher that encourage students in a positive manner. When students are young, it is also beneficial to have educated parents who try to ecourage learning in children in settings out of school (Hodis & Hodis, 2022). <quiz display="simple"> {Quiz: "A desire to engage in an activity because it is personally interesting, enjoyable, or satisfying, rather than because of external rewards or pressures". Which type of motivation is this? |type="()"} - Achievement Motivation - Extrinsic Motivation + Intrinsic Motivation - Affiliation Motivation </quiz> == Effects of AI on student motivation == {{ic|Include an introductory paragraph before branching into sub-sections}} === Positive effects of using AI === * Research had{{g}} shown that generative AI powered systems that are acting as effective agents can support and and help improve learning and regulation processes in students (Fan et al., 2025) * AI has been found to engage students in meaningful ways by fostering curiosity, autonomy, and instrinsic motivation in their learning journies (Pertiwi et al., 2024). * Can reduce overall learner anxiety (Hmoud et al., 2024). === Negative effects of using AI === * Reinforces state of metacognitive laziness and adds to the lack of development in the use of critical thinking skills, making students become over-reliant using AI (Fan et al., 2025). * Though can generate content from existing data and providing people with high-quality materials, it cannot provide contextualised in person explanations that a teachr can provide, so it cannot fully replace teachers. (Fan et al., 2025). * Potential privacy and security issues (Oseni, 2021) {{ic|How does this relate to motivation?}}. == Impact of AI on student learning == {{ic|Include an introductory paragraph before branching into sub-sections}} === Students approach to learning === *Students currently prioritise learning that is increasingly fast and optimaly (Zhai et al., 2024). *Students have instant support for understanding any question through AI chatbots (Hmoud et al., 2024). *Students are becoming more engaged since AI started to become implemented (Vieriu & Petra, 2025). === Change of approach to learning due to AI === * Students have the ability to access most information online with the click of a finge due to AI, unlike before where most information is told trough textbooks and teachers (Parhanuddin et al., 2025). * Learning is more personalised and suited to each individual (Parhanuddin e al., 2025). * Ideas can be brainstormed through AI (Vieriu & Petra, 2025). == AI reliance on student learning habits == {{ic|Include an introductory paragraph before branching into sub-sections}} === Are students becoming too reliant? === * A study found that there is overreliance in using AI, and that this overreliance tends to impact cognitive abilities as individuals increasingly choose fast and optimal solutions over solutions that are slower from practicality (Zhai et al., 2024). * By using AI too much, students can gain an overdependance on specific abilities such as decision-making, critical thinking, and analytical reasoning (Zhai et al., 2024). * Through this trend which continues to develop and transform as AI is becoming more prelavent, potential erosion of critical cognitive skills may happen an worsen (Zhai et al., 2024). === What do learning habits look like today? === * More personalised learning due to the implementation of AI, targeting each inidviduals students specific needs to help acheive higher achievements (Parhanuddin et al., 2025). * Studying with more digital tools that integrate AI, rather than just focusing on paper text books (Parhanuddin et al., 2025). * Collaboration with peers and online chat (Hmoud et al., 2024). == Conclusion == * AI has shown both positive and negative effects on students and the entire academic setting. * Learning ways have changed and developed to involve AI, which contiues to change as AI does. * Further study should be conducted to better help each academic setting understand how they can ethically involve the use of AI to be beneficial for learning so that students are still using critical thinking skills. == See also == * [[w:Artificial_intelligence|Artifical Intelligence]] (Wikipedia) * [[Motivation]] (Wikiversity) * [[wikipedia:Intrinsic_motivation_(artificial_intelligence)|Intrinsic motivation in artificial intelligence]] (Wikipedia) == References == {{Hanging indent|1= Di Domenico, S. I., & Ryan, R. M. (2017). The emerging neuroscience of intrinsic motivation: A new frontier in self-determination research. Frontiers in Human Neuroscience, 11, 145. https://doi.org/10.3389/fnhum.2017.00145 Fan, Y., Tang, L., Le, H., Shen, K., Tan, S., Zhao, Y., ... & Gašević, D. (2025). Beware of metacognitive laziness: Effects of generative artificial intelligence on learning motivation, processes, and performance. British Journal of Educational Technology, 56(2), 489-530. https://doi.org/10.1111/bjet.13544 Hmoud, M., Swaity, H., Hamad, N., Karram, O., & Daher, W. (2024). Higher education students’ task motivation in the generative artificial intelligence context: The case of ChatGPT. Information, 15(1), 33. https://doi.org/10.3390/info15010033 Hodis, F. A., & Hodis, G. M. (2022). Key factors that influence students’ motivation to learn: Implications for teaching. Set: Research Information for Teachers, 2, 37-41. https://doi.org/10.18296/set.1509 Legault, L. (2016). Intrinsic and extrinsic motivation. Encyclopedia of personality and individual differences, 10, 978-3. https://doi.org/10.1007/978-3-319-28099-8_1139-1 Oseni, A., Moustafa, N., Janicke, H., Liu, P., Tari, Z., & Vasilakos, A. (2021). Security and privacy for artificial intelligence: Opportunities and challenges. arXiv preprint arXiv:2102.04661. https://doi.org/10.1145/1122445.1122456 Parhanuddin, L., Tohri, A., & Suhardi, M. (2025). The Effect of AI (Artificial Intelligence) in Education on Student Motivation: A Systematic Literature Review. Journal for Lesson and Learning Studies, 8(1), 1-10. https://doi.org/10.23887/jlls.v8i1.91141 Pertiwi, R. W. L., Kulsum, L. U., & Hanifah, I. A. (2024). Evaluating the impact of artificial intelligence-based learning methods on students' motivation and academic achievement. International Journal of Post Axial: Futuristic Teaching and Learning, 49-58. https://doi.org/10.59944/postaxial.v2i1.279 Vieriu, A. M., & Petrea, G. (2025). The impact of artificial intelligence (AI) on students’ academic development. Education Sciences, 15(3), 343. https://doi.org/10.3390/educsci15030343 Zhai, C., Wibowo, S., & Li, L. D. (2024). The effects of over-reliance on AI dialogue systems on students' cognitive abilities: a systematic review. Smart Learning Environments, 11(1), 28. https://doi.org/10.1186/s40561-024-00316-7 Zhang, C., & Lu, Y. (2021). Study on artificial intelligence: The state of the art and future prospects. Journal of Industrial Information Integration, 23, 100224. https://doi.org/10.1016/j.jii.2021.100224 }} == External links == * [https://www.ted.com/talks/sal_khan_how_ai_could_save_not_destroy_education How AI could save (not destroy) education] (TED talk) * [https://www.abc.net.au/religion/ai-has-accelerated-demise-of-critical-thinking-in-universities/106867608 How AI has accelerated the demise of critical thinking in universities] (ABC News) [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Artificial intelligence]] [[Category:Motivation and emotion/Book/Academic]] bq9k46nixdldp2mqda2s83u7qprhjgv 0 331262 2835276 2835129 2026-10-01T05:58:42Z Jtneill 10242 + ;Scenario 2835276 wikitext text/x-wiki {{title|Dark empathy:<br>What is dark empathy, what are its consequences, and what can be done to address it?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}}{{ic|Make it more clear how this connects to dark empathy}} ;Scenario Imagine your extroverted friend, Nikki, has lost their confidence and is isolating herself. After months of attempting to catch up for coffee, she shows up late and spends most of the time glued to her phone. She apologizes as she sends messages every 10 minutes to let her partner know what she is doing. You ask her how she has been and she spends all her time talking about her partner and mentions she is no longer participating in her usual hobbies. You have noticed that since she met her partner, Fedrick, she rarely goes anywhere without him. She says he has the same interests as her and enjoys spending time with her. After an hour, Fedrick turns up at the cafe to join the conversation. His stories are often focused on himself and his shared trauma with Nikki. You are starting to suspect that Fedrick has been manipulating Nikki and your friend seems unhappy despite telling you otherwise. {{RoundBoxBottom}} * Dark empathy is a developed skill that uses the understanding of emotion and people's vulnerabilities against them to control and manipulate for their advantage {{citation needed}} {{expand}} * Understanding why and how people use dark empathy is important to preventing and addressing the concern {{citation needed}} {{grammar}} * Research indicates understanding emotional intelligence, the dark triad, theory of mind, and the schemas could assist with understanding the motivation behind dark empathy {{citation needed}} {{RoundBoxTop|theme=3}} ;Focus questions *How do we develop empathy? *What drives an individual to use empathy to control and manipulate other people in their life? *How can psychological theory develop strategies to understand and assist individuals mitigate the negative effects of empathy? {{RoundBoxBottom}} == The development of empathy == * [[Empathy]] is the ability to share feelings and thoughts of others while remaining self-other determination (Håkansson Eklund & Summer Meranius, 2021). *Empathy is not an innate, rather learned and developed. It can be cultivated through techniques to understand other's feelings and foster pro-social behaviour (Abramson, A, 2021) {{check citation consistency with APA7}} *Although, empathy does not have have a natural morality which means the individual has to choose how to use their understanding of other's emotions and feelings {{citation needed}}. === Types of empathy === Empathy is a large element of [[emotional intelligence]] in an understanding and sharing feeling with others {{citation needed}}. Empathy has bright and dark sides as well two types: * Affective empathy is physical and emotional sharing of feelings **This empathy is experiencing with the other person which is found more commonly in bright empathy () * Cognitive empathy is the intellectual understanding of another’s emotions and thoughts without feeling their pain. **This empathy is the understanding, yet keeping that self-other determination which makes it easier for manipulating by utilising emotions against another [[File:The Dark Triad Traits.svg|thumb|'''Figure 1.''' The dark triad and subsets of the three elements ]] === The dark tetrad === * Dark personality traits were called the 'dark triad' (Paulhus & Williams, 2002). An expansion on these traits were to include a fourth element, sadism (Mededovic & Petrovic, 2015). There are four elements to the dark tetrad: ** Narcissism ** Machiavellianism ** Psychopathy ** Sadism === Making of a dark empath === *Dark Empathy is understanding those feelings and harnessing against others {{citation needed}} * Development of dark empathy is when an individual has high levels of dark traits (narcissism, machiavellianism, psychopathy, and sadism) and alongside retained high cognitive and affective empathy capacity (Gojković et al., 2022) * Research assessing individuals with high levels of dark traits concluded these personality types do not share ethics and morality meaning they are more likely to be honest and fair towards others (Mededovic & Petrovic, 2015) * Dark empathy isn't a psychological diagnosis, yet a term how an individual differences from other diagnoses from the dark triad {{grammar}} {{citation needed}} {{clarify}} * Dark empathy is found in individuals with high dark triad traits and cognitive empathy {{citation needed}}. Cognitive empathy rather than affective empathy allows the individual to understanding emotions and thoughts without having to feel the emotions which in turn makes it easier to manipulate others * '''An individual with affective dissonance is another indicator of dark empathy.''' It is having twisted or contradictory emotional reactions, such as feeling happy when someone else is suffering that is present in those with high dark traits (Gojković et al., 2022). *Research demonstrates that experiencing trauma as a child where you had to predict and understand other's emotions to keep safe may lead to the development of dark empathy {{citation needed}} == Consequences of dark empathy == *The person using dark empathy and those they are manipulating are both impacted by the behaviour and will harm their wellbeing {{citation needed}} *While the use of empathy may bring people together through a shared emotion and experience, dark empathy isolates from community {{grammar}} {{citation needed}} === Effects on victims of dark empathy === *The immediate impacts are startle and unlikely to be noticed, yet over time an individual will develop chronic anxiety, lower self-esteem and emotional dependency {{citation needed}} === Outcome for dark empaths === *An individual using dark empathy will find the control and manipulation effective and after time keeping up this level of deception is exhausting. {{citation needed}} *It will impact their mental health potentially leading to depression, mood instability, difficulty maintaining long-term relationships and identity confusion {{citation needed}} == Address dark empathy == *Dark empathy is not easily recognised in others {{citation needed}} *A narcissist or sociopath may use understanding of schemas to influence others while a dark empath uses their empathy to control and most likely enjoy other's vulnerable emotions {{citation needed}} === Regaining themselves: recovering from a dark empathy === *Recognise the patterns used by the dark empath {{citation needed}} *Prioritise your self and trust your instincts {{citation needed}} *Set healthy emotional boundaries in this relationship *Seek therapy particularly CBT {{citation needed}} *Seperation from the dark empath {{citation needed}} === Unravelling from dark empathy === *Recognising and acknowledging the pattern of behaviour of controlling those around them and the impacts on theirs and other’s wellbeing {{citation needed}} *Attending therapy is the best way to address and understand the behaviours {{citation needed}}. Some therapies that would be appropriate and effective for dark empaths are: **Trauma-informed therapy **[[w:Cognitive_behavioral_therapy|Cognitive Behaviour Therapy]] (CBT) **[[w:Schema_therapy|Schema therapy]] **Emotional regulation and accountability training {{citation needed}}. == Conclusion == * Emotional intelligence does not come with morality {{citation needed}} * The dark triad is an indicator of dark empathy if individual have high dark traits and affective cognitive empathy {{citation needed}} * Cognitive empathy and trauma patterns can develop the drive for using dark empathy {{citation needed}} * Effective identification and therapy will assist with managing an individual using empathy against others {{citation needed}} ==Figures== [[File:Thought bubble.svg|right|140px|thumb|'''Figure 2'''. Example of an image with a descriptive caption.]] * For the book chapter, use several figures to illustrate concepts, add interest, and to serve as examples * For the topic development, use at least one figure (even if not ideal) to show that you know how to embed, caption, and cite a figure * Figures can show any kind of media such as photos, diagrams, graphs, video, audio, and so on * Embed figures throughout the chapter, starting with the scenario in the Overview section * Provide descriptive figure captions (use '''Figure #''' and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Learning features help to bring book chapters to life and can be embedded throughout the chapter. Here are some options: {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples that illustrate concepts in action * Present using [[#Feature boxes|feature boxes]]; can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Can be real or fictional; if real, provide citation(s) {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing the Relationship Between Known/Unknown and Self/Other {| class="wikitable" style="margin: auto;" |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * One or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as the take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display=simple> {The purpose of quizzes is to provide an interactive learning feature: |type="()"} + True - False {Long and complex quiz questions are recommended: |type="()"} - True + False </quiz> ==Conclusion== * Arguably the most important section * Provide at least three bullet-points for this section even at the topic development stage, based on preliminary thinking * For the book chapter, develop clear take-home message(s) that address the focus questions based on psychological theory and research * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing this problem * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== *[[Motivation and emotion/Book/2020/Dark triad personality and emotion|Dark triad personality and emotion]] (Book chapter, 2020) *[[Motivation and emotion/Book/2019/Emotional intelligence and anti-social behaviour|Emotional intelligence and antisocial behaviour]] (Book chapter, 2019) *[[Motivation and emotion/Book/2021/Emotional intelligence and the dark triad|Emotional intelligence and the dark triad]] (Book chapter, 2021) *[[wikipedia:Machiavellianism_(psychology)|Machiavellianism]] (Wikipedia) *[[wikipedia:Narcissism|Narcissism]] (Wikipedia) *[[wikipedia:Psychopathy|Psychopathy]] (Wikipedia) *[[wikipedia:Dark_triad|The Dark Triad]] (Wikipedia) ==References== {{Hanging indent|1= Abramson, A. (2021, November 1). Cultivating empathy. Monitor on Psychology, 52(8). https://www.apa.org/monitor/2021/11/feature-cultivating-empathy Gojković, V., Dostanić, J. S., & Đurić, V. (2022). Structure of darkness: The Dark Triad, the ‘Dark’ Empathy and the ‘Dark’ Narcissism. Primenjena psihologija (Online), 15(2), 237-268. https://doi.org/10.19090/pp.v15i2.2380 Håkansson Eklund, J., & Summer Meranius, M. (2021). Toward a consensus on the nature of empathy: A review of reviews. Patient education and counseling, 104(2), 300-307. https://doi.org/10.1016/j.pec.2020.08.022 Heym, N., Firth, J., Kibowski, F., Sumich, A., Egan, V., & Bloxsom, C. A. (2019). Empathy at the heart of darkness: Empathy deficits that bind the dark triad and those that mediate indirect relational aggression. Frontiers in psychiatry, 10, 95. Heym, N., Kibowski, F., Bloxsom, C. A. J., Blanchard, A., Harper, A., Wallace, L., Firth, J., & Sumich, A. (2021). The Dark Empath: Characterising dark traits in the presence of empathy. Personality and Individual Differences, 169, 110172-110172. https://doi.org/10.1016/j.paid.2020.110172 Huang, C., Wu, Z., Sha, S., Liu, C., Yang, L., Jiang, P., Zhang, H., & Yang, C. (2025). The Dark Side of Empathy: The Role of Excessive Affective Empathy in Mental Health Disorders. Biological psychiatry (1969), 98(5), 404-415. https://doi.org/10.1016/j.biopsych.2024.12.020 Kaufman, S. B., Yaden, D. B., Hyde, E., & Tsukayama, E. (2019). The Light vs. Dark Triad of Personality: Contrasting Two Very Different Profiles of Human Nature [Original Research]. Frontiers in psychology, Volume 10 - 2019. https://doi.org/10.3389/fpsyg.2019.00467 Mededovic, J., & Petrovic, B. (2015). The Dark Tetrad: Structural Properties and Location in the Personality Space. Journal of individual differences, 36(4), 228-236. https://doi.org/10.1027/1614-0001/a000179 Mikkelsen, E. N., Geraldi, J., & Clegg, S. (2026). The Dark Side of Empathy and Organization Studies. Organization studies. https://doi.org/10.1177/01708406261459079 Paulhus, D. L., & Williams, K. M. (2002). The Dark Triad of personality: Narcissism, Machiavellianism, and psychopathy. Journal of research in personality, 36(6), 556-563. https://doi.org/10.1016/S0092-6566(02)00505-6 }} {{tip|Suggestions for this section: * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) ** Hanging indent: Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: *** Use "Edit source" *** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== * [https://www.sciencefocus.com/wellbeing/dark-empaths Dark Empaths] (Science Focus) * [https://www.psychologytoday.com/au/basics/dark-triad Dark Triad] (Psychology Today) * [https://www.theguardian.com/science/2024/nov/10/narcissists-only-more-devious-the-truth-about-dark-empaths 'Narcissists - only more devious': the truth about dark empaths] (the Guardian) [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] nuvq7iwexff343m3l3sawl4dn14kske 2835277 2835276 2026-10-01T05:59:36Z Jtneill 10242 /* Types of empathy */ {{ic|Expand figure size so that it is easier to read the text.}} 2835277 wikitext text/x-wiki {{title|Dark empathy:<br>What is dark empathy, what are its consequences, and what can be done to address it?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}}{{ic|Make it more clear how this connects to dark empathy}} ;Scenario Imagine your extroverted friend, Nikki, has lost their confidence and is isolating herself. After months of attempting to catch up for coffee, she shows up late and spends most of the time glued to her phone. She apologizes as she sends messages every 10 minutes to let her partner know what she is doing. You ask her how she has been and she spends all her time talking about her partner and mentions she is no longer participating in her usual hobbies. You have noticed that since she met her partner, Fedrick, she rarely goes anywhere without him. She says he has the same interests as her and enjoys spending time with her. After an hour, Fedrick turns up at the cafe to join the conversation. His stories are often focused on himself and his shared trauma with Nikki. You are starting to suspect that Fedrick has been manipulating Nikki and your friend seems unhappy despite telling you otherwise. {{RoundBoxBottom}} * Dark empathy is a developed skill that uses the understanding of emotion and people's vulnerabilities against them to control and manipulate for their advantage {{citation needed}} {{expand}} * Understanding why and how people use dark empathy is important to preventing and addressing the concern {{citation needed}} {{grammar}} * Research indicates understanding emotional intelligence, the dark triad, theory of mind, and the schemas could assist with understanding the motivation behind dark empathy {{citation needed}} {{RoundBoxTop|theme=3}} ;Focus questions *How do we develop empathy? *What drives an individual to use empathy to control and manipulate other people in their life? *How can psychological theory develop strategies to understand and assist individuals mitigate the negative effects of empathy? {{RoundBoxBottom}} == The development of empathy == * [[Empathy]] is the ability to share feelings and thoughts of others while remaining self-other determination (Håkansson Eklund & Summer Meranius, 2021). *Empathy is not an innate, rather learned and developed. It can be cultivated through techniques to understand other's feelings and foster pro-social behaviour (Abramson, A, 2021) {{check citation consistency with APA7}} *Although, empathy does not have have a natural morality which means the individual has to choose how to use their understanding of other's emotions and feelings {{citation needed}}. === Types of empathy === Empathy is a large element of [[emotional intelligence]] in an understanding and sharing feeling with others {{citation needed}}. Empathy has bright and dark sides as well two types: * Affective empathy is physical and emotional sharing of feelings **This empathy is experiencing with the other person which is found more commonly in bright empathy () * Cognitive empathy is the intellectual understanding of another’s emotions and thoughts without feeling their pain. **This empathy is the understanding, yet keeping that self-other determination which makes it easier for manipulating by utilising emotions against another [[File:The Dark Triad Traits.svg|thumb|'''Figure 1.''' The dark triad and subsets of the three elements {{ic|Expand figure size so that it is easier to read the text.}}]] === The dark tetrad === * Dark personality traits were called the 'dark triad' (Paulhus & Williams, 2002). An expansion on these traits were to include a fourth element, sadism (Mededovic & Petrovic, 2015). There are four elements to the dark tetrad: ** Narcissism ** Machiavellianism ** Psychopathy ** Sadism === Making of a dark empath === *Dark Empathy is understanding those feelings and harnessing against others {{citation needed}} * Development of dark empathy is when an individual has high levels of dark traits (narcissism, machiavellianism, psychopathy, and sadism) and alongside retained high cognitive and affective empathy capacity (Gojković et al., 2022) * Research assessing individuals with high levels of dark traits concluded these personality types do not share ethics and morality meaning they are more likely to be honest and fair towards others (Mededovic & Petrovic, 2015) * Dark empathy isn't a psychological diagnosis, yet a term how an individual differences from other diagnoses from the dark triad {{grammar}} {{citation needed}} {{clarify}} * Dark empathy is found in individuals with high dark triad traits and cognitive empathy {{citation needed}}. Cognitive empathy rather than affective empathy allows the individual to understanding emotions and thoughts without having to feel the emotions which in turn makes it easier to manipulate others * '''An individual with affective dissonance is another indicator of dark empathy.''' It is having twisted or contradictory emotional reactions, such as feeling happy when someone else is suffering that is present in those with high dark traits (Gojković et al., 2022). *Research demonstrates that experiencing trauma as a child where you had to predict and understand other's emotions to keep safe may lead to the development of dark empathy {{citation needed}} == Consequences of dark empathy == *The person using dark empathy and those they are manipulating are both impacted by the behaviour and will harm their wellbeing {{citation needed}} *While the use of empathy may bring people together through a shared emotion and experience, dark empathy isolates from community {{grammar}} {{citation needed}} === Effects on victims of dark empathy === *The immediate impacts are startle and unlikely to be noticed, yet over time an individual will develop chronic anxiety, lower self-esteem and emotional dependency {{citation needed}} === Outcome for dark empaths === *An individual using dark empathy will find the control and manipulation effective and after time keeping up this level of deception is exhausting. {{citation needed}} *It will impact their mental health potentially leading to depression, mood instability, difficulty maintaining long-term relationships and identity confusion {{citation needed}} == Address dark empathy == *Dark empathy is not easily recognised in others {{citation needed}} *A narcissist or sociopath may use understanding of schemas to influence others while a dark empath uses their empathy to control and most likely enjoy other's vulnerable emotions {{citation needed}} === Regaining themselves: recovering from a dark empathy === *Recognise the patterns used by the dark empath {{citation needed}} *Prioritise your self and trust your instincts {{citation needed}} *Set healthy emotional boundaries in this relationship *Seek therapy particularly CBT {{citation needed}} *Seperation from the dark empath {{citation needed}} === Unravelling from dark empathy === *Recognising and acknowledging the pattern of behaviour of controlling those around them and the impacts on theirs and other’s wellbeing {{citation needed}} *Attending therapy is the best way to address and understand the behaviours {{citation needed}}. Some therapies that would be appropriate and effective for dark empaths are: **Trauma-informed therapy **[[w:Cognitive_behavioral_therapy|Cognitive Behaviour Therapy]] (CBT) **[[w:Schema_therapy|Schema therapy]] **Emotional regulation and accountability training {{citation needed}}. == Conclusion == * Emotional intelligence does not come with morality {{citation needed}} * The dark triad is an indicator of dark empathy if individual have high dark traits and affective cognitive empathy {{citation needed}} * Cognitive empathy and trauma patterns can develop the drive for using dark empathy {{citation needed}} * Effective identification and therapy will assist with managing an individual using empathy against others {{citation needed}} ==Figures== [[File:Thought bubble.svg|right|140px|thumb|'''Figure 2'''. Example of an image with a descriptive caption.]] * For the book chapter, use several figures to illustrate concepts, add interest, and to serve as examples * For the topic development, use at least one figure (even if not ideal) to show that you know how to embed, caption, and cite a figure * Figures can show any kind of media such as photos, diagrams, graphs, video, audio, and so on * Embed figures throughout the chapter, starting with the scenario in the Overview section * Provide descriptive figure captions (use '''Figure #''' and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Learning features help to bring book chapters to life and can be embedded throughout the chapter. Here are some options: {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples that illustrate concepts in action * Present using [[#Feature boxes|feature boxes]]; can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Can be real or fictional; if real, provide citation(s) {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing the Relationship Between Known/Unknown and Self/Other {| class="wikitable" style="margin: auto;" |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * One or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as the take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display=simple> {The purpose of quizzes is to provide an interactive learning feature: |type="()"} + True - False {Long and complex quiz questions are recommended: |type="()"} - True + False </quiz> ==Conclusion== * Arguably the most important section * Provide at least three bullet-points for this section even at the topic development stage, based on preliminary thinking * For the book chapter, develop clear take-home message(s) that address the focus questions based on psychological theory and research * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing this problem * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== *[[Motivation and emotion/Book/2020/Dark triad personality and emotion|Dark triad personality and emotion]] (Book chapter, 2020) *[[Motivation and emotion/Book/2019/Emotional intelligence and anti-social behaviour|Emotional intelligence and antisocial behaviour]] (Book chapter, 2019) *[[Motivation and emotion/Book/2021/Emotional intelligence and the dark triad|Emotional intelligence and the dark triad]] (Book chapter, 2021) *[[wikipedia:Machiavellianism_(psychology)|Machiavellianism]] (Wikipedia) *[[wikipedia:Narcissism|Narcissism]] (Wikipedia) *[[wikipedia:Psychopathy|Psychopathy]] (Wikipedia) *[[wikipedia:Dark_triad|The Dark Triad]] (Wikipedia) ==References== {{Hanging indent|1= Abramson, A. (2021, November 1). Cultivating empathy. Monitor on Psychology, 52(8). https://www.apa.org/monitor/2021/11/feature-cultivating-empathy Gojković, V., Dostanić, J. S., & Đurić, V. (2022). Structure of darkness: The Dark Triad, the ‘Dark’ Empathy and the ‘Dark’ Narcissism. Primenjena psihologija (Online), 15(2), 237-268. https://doi.org/10.19090/pp.v15i2.2380 Håkansson Eklund, J., & Summer Meranius, M. (2021). Toward a consensus on the nature of empathy: A review of reviews. Patient education and counseling, 104(2), 300-307. https://doi.org/10.1016/j.pec.2020.08.022 Heym, N., Firth, J., Kibowski, F., Sumich, A., Egan, V., & Bloxsom, C. A. (2019). Empathy at the heart of darkness: Empathy deficits that bind the dark triad and those that mediate indirect relational aggression. Frontiers in psychiatry, 10, 95. Heym, N., Kibowski, F., Bloxsom, C. A. J., Blanchard, A., Harper, A., Wallace, L., Firth, J., & Sumich, A. (2021). The Dark Empath: Characterising dark traits in the presence of empathy. Personality and Individual Differences, 169, 110172-110172. https://doi.org/10.1016/j.paid.2020.110172 Huang, C., Wu, Z., Sha, S., Liu, C., Yang, L., Jiang, P., Zhang, H., & Yang, C. (2025). The Dark Side of Empathy: The Role of Excessive Affective Empathy in Mental Health Disorders. Biological psychiatry (1969), 98(5), 404-415. https://doi.org/10.1016/j.biopsych.2024.12.020 Kaufman, S. B., Yaden, D. B., Hyde, E., & Tsukayama, E. (2019). The Light vs. Dark Triad of Personality: Contrasting Two Very Different Profiles of Human Nature [Original Research]. Frontiers in psychology, Volume 10 - 2019. https://doi.org/10.3389/fpsyg.2019.00467 Mededovic, J., & Petrovic, B. (2015). The Dark Tetrad: Structural Properties and Location in the Personality Space. Journal of individual differences, 36(4), 228-236. https://doi.org/10.1027/1614-0001/a000179 Mikkelsen, E. N., Geraldi, J., & Clegg, S. (2026). The Dark Side of Empathy and Organization Studies. Organization studies. https://doi.org/10.1177/01708406261459079 Paulhus, D. L., & Williams, K. M. (2002). The Dark Triad of personality: Narcissism, Machiavellianism, and psychopathy. Journal of research in personality, 36(6), 556-563. https://doi.org/10.1016/S0092-6566(02)00505-6 }} {{tip|Suggestions for this section: * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) ** Hanging indent: Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: *** Use "Edit source" *** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== * [https://www.sciencefocus.com/wellbeing/dark-empaths Dark Empaths] (Science Focus) * [https://www.psychologytoday.com/au/basics/dark-triad Dark Triad] (Psychology Today) * [https://www.theguardian.com/science/2024/nov/10/narcissists-only-more-devious-the-truth-about-dark-empaths 'Narcissists - only more devious': the truth about dark empaths] (the Guardian) [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] 7unl963av9sue36c5oc9m8tqronbnq0 1 331415 2835271 2834378 2026-10-01T04:51:50Z U3285438 3103750 /* Resource recommendations */ new section 2835271 wikitext text/x-wiki ==Comment== Hey, I am excited to see how this chapter turns out. With the use of social media, homeschooling (and something called unschooling) are becoming more popularised. Here are three sources about homeschooling and unschooling: [https://www.researchgate.net/profile/Gina-Riley-2/publication/305720522%20The%20Challenges%20and%20Benefits%20of%20Unschooling%20According%20to%20232%20Families%20Who%20Have%20Chosen%20that%20Route/links/579b8a8d08ae5d5e1e138042/The-Challenges-and-Benefits-of-Unschooling-According-to-] DOI:10.1080/2331186X.2016.1163651 https://doi.org/10.1080/02732173.2014.895640 -Kayla H --[[User:U3279062|U3279062]] ([[User talk:U3279062|discuss]] • [[Special:Contributions/U3279062|contribs]]) 08:32, 23 August 2026 (UTC) <!-- Official topic development feedback --> {{METF/2026 |1= <!-- Title --> # Title and subtitle are correctly worded and use [[w:Letter case#Sentence casing|sentence casing]] |2= <!-- Headings --> <!-- Heading structure --> <!-- 2-level --> # Promising [[Motivation and emotion/Assessment/Major project/Structure|2-level heading structure]] – could benefit from further development and/or refinement <!-- Conceptual --> # "Understanding ... " is somewhat vague; consider using a more precise heading # It is unclear from the heading structure what main theories you've identified as useful for this question <!-- Other ---> # Use default heading formatting (i.e., avoid additional formatting such as bold, italics, underline, changing the size etc.) <!-- Alignment with focus questions --> # Insufficient alignment between sub-title, focus questions, and top-level headings <!-- GenAI ---> # Are the headings based on [[Motivation and emotion/Assessment/Using generative AI|genAI content]]? If so, this needs to be acknowledged in the edit summaries, otherwise it violates academic integrity. |3= <!-- Overview--> # Basic <!-- GenAI ---> # Does this section include [[Motivation and emotion/Assessment/Using generative AI|genAI content]]? If so, it needs to be acknowledged as such in the edit summaries, otherwise it violates academic integrity. <!-- Scenario --> # Promising scenario; would benefit from further development to make it more compelling and illustrative # Consider revising the scenario from second person perspective into third person perspective # Add an image to the scenario to help attract reader interest <!-- Description -->. # Add a brief, evocative description of the problem/topic <!-- Focus questions --> <!-- Alignment and quality --> # Promising focus questions which could benefit from further development # Develop closer alignment between the sub-title, focus questions, and top-level headings # The focus questions are quite specific, which is usually a good thing, but in this case, may be overly specific |4= <!-- Key points--> <!-- Overall --> # Promising development: Many parental motivations are suggested, with citations, and organised into categories/themes # It is unclear, however, what the main motivations are, or what the main theories are; strive to critically synthesise the theoretical and empriical literature # Provide more detailed edit summaries <!-- Scope --> # The scope is about right, but it may be that all planned aspects cannot be reasonably covered within the book chapter word count; in that case, be selective and concentrate on key aspects that address the question in the sub-title <!-- GenAI ---> # Do these key points include [[Motivation and emotion/Assessment/Using generative AI|genAI content]]? If so, this needs to be acknowledged in the edit summaries, otherwise it violates academic integrity. <!-- Conclusion --> # Conclusion is well underway # What are the practical, take-home messages? (address the focus questions) |5= <!-- Figure --> # Excellent - Relevant figure(s) presented, captioned, and cited <!-- Caption --> # Figure caption(s) provide(s) a clear, appropriately detailed description that is meaningfully connected with the main text <!-- Cite --> # Figure(s) are cited at least once in the main text # Note that there are two Figure 1s |6= <!-- Learning feature --> <!-- Interwiki links ---> # Add in-text [[m:Help:Interwiki linking|interwiki links]] for first mention of key terms to [[w:|Wikipedia]] and/or [[Motivation and emotion/Book|book chapters]] (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) <!-- Scenarios/examples/case studies --> # Consider incorporating additional scenarios, examples, or case studies to illustrate key concepts. These could build on the Overview scenario or introduce new real-world situations in the main body of the chapter to demonstrate how the concepts apply in practice. <!-- Quiz --> # Consider including quiz question(s) about the take-home messages <!-- Tables --> # Also consider using [[Motivation and emotion/Wikiversity/Tables|table(s)]] to summarise key information |7= <!-- References --> <!-- Overall --> # Excellent # Very good # Good # Basic # Insufficient # To be developed <!-- Systematic reviews --> # At least one relevant systematic review and/or meta-analysis has been identified <!-- Move --> # Move non-academic / non-peer reviewed sources to the "External links" section <!-- Citations --> # Only include references which have been accessed and read <!-- APA style --> # Check and correct [https://apastyle.apa.org/instructional-aids/reference-guide.pdf APA referencing style]: ## remove bullet points ## capitalisation ## [[Help:Wikitext quick reference|italicisation]] ## include hyperlinked dois ## many details are missing ## do not use "Retrieved from" |8= <!-- Resources --> <!-- See also --> # See also ## To be developed (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) ## Link to the most relevant Wikiversity book chapters and Wikipedia resources about this topic <!-- External links --> # External links ## Excellent ## To be developed (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) ## Link to the most relevant external resources about this topic |9= <!-- User page --> # Basic # Not created – see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]] <!-- Description about self --> # Brief description about self – consider expanding <!-- Links to profile(s) --> # Consider linking to your [https://portfolio.canberra.edu.au/ eportfolio] page and/or any other professional online profile or resume such as [https://www.linkedin.com/ LinkedIn]. This is not required, but it can be useful to interlink your professional networks. <!-- Link to book chapter --> # Add link to book chapter |10= <!-- Social contribution --> # None summarised on user page with direct link(s) to evidence (see [[Motivation and emotion/Tutorials/Wiki editing#Social contributions|Tutorial 2]]). Looking ahead to the book chapter, see [[Motivation and emotion/Assessment/Chapter#Socialcontribution|social contributions]]. }} == Resource recommendations == Hey there, I enjoyed reading through your chapter so far! I noticed that you hadn't yet included any internal or external links to related resources, so I gathered a few that I think are interesting and could be a valuable addition to your chapter. ''See also'' * [[Motivation and emotion/Book/2015/Family influences on academic motivation|Family influences on academic motivation]] (Book chapter, 2015) * [[wikipedia:Homeschooling|Homeschooling]] (Wikipedia) ''External links'' * [http://learnmate.com.au/homeschool-vs-school/ Homeschooling vs school: what’s better?] (Learnmate) * [https://theconversation.com/the-lasting-appeal-of-homeschooling-what-motivated-families-to-continue-after-schools-reopened-post-pandemic-280118 The lasting appeal of homeschooling: what motivated families to continue after schools reopened post‑pandemic] (The Conversation) * [https://theconversation.com/why-parents-of-twice-exceptional-children-choose-homeschooling-over-public-school-244385 Why parents of ‘twice‑exceptional’ children choose homeschooling over public school] (The Conversation) Best regards. [[User:U3285438|U3285438]] ([[User talk:U3285438|discuss]] • [[Special:Contributions/U3285438|contribs]]) 04:51, 1 October 2026 (UTC) tkaywjt6auzhkhhxurd83av2ypmnszy 2 331500 2835167 2826140 2026-09-30T12:41:56Z SJPiper 3107750 /* Social contributions */ 2835167 wikitext text/x-wiki == About me == Hi, I'm '''Stephanie Piper''' I am studying [[motivation and emotion]] at the [https://www.canberra.edu.au/current-students University of Canberra]. I am a 3rd year psychology student. == Hobbies == [[File:Listas! (180948337).jpg|thumb|'''Figure 1'''. Swimming is good for both your physical and emotional health. |300x300px]] * Playing sport ** Walking ** [[w:League_tag|League tag]] ** Oztag ** [[Swimming]] * Cooking * Crafts * Reading == Book chapter I'm working on == The book chapter I am working on is [[Motivation and emotion/Book/2026/Youth environmental activism motivation|Youth environmental activism motivation-What motivates young people to engage in environmental activism?]] == Social contributions == # [https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FAkrasia&diff=2826105&oldid=2826068 Capitalized Letter I] #[[Talk:Motivation and emotion/Book/2026/Sex work motivation|Made a suggestion]] #[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/456345 Shared what motivates me] #Removed double spacing in text nmab0gmsi6y4toz6s9bo74selmzk6f0 2835168 2835167 2026-09-30T12:43:00Z SJPiper 3107750 /* Social contributions */ 2835168 wikitext text/x-wiki == About me == Hi, I'm '''Stephanie Piper''' I am studying [[motivation and emotion]] at the [https://www.canberra.edu.au/current-students University of Canberra]. I am a 3rd year psychology student. == Hobbies == [[File:Listas! (180948337).jpg|thumb|'''Figure 1'''. Swimming is good for both your physical and emotional health. |300x300px]] * Playing sport ** Walking ** [[w:League_tag|League tag]] ** Oztag ** [[Swimming]] * Cooking * Crafts * Reading == Book chapter I'm working on == The book chapter I am working on is [[Motivation and emotion/Book/2026/Youth environmental activism motivation|Youth environmental activism motivation-What motivates young people to engage in environmental activism?]] == Social contributions == # [https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FAkrasia&diff=2826105&oldid=2826068 Capitalized Letter I] #[[Talk:Motivation and emotion/Book/2026/Sex work motivation|Made a suggestion]] #[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/456345 Shared what motivates me] #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FAkrasia&diff=2826105&oldid=2826068 Removed double spacing in text] qm1ponh9haogjzszsoe6bkv9ntmm07y 2835173 2835168 2026-09-30T12:50:48Z SJPiper 3107750 /* Social contributions */ 2835173 wikitext text/x-wiki == About me == Hi, I'm '''Stephanie Piper''' I am studying [[motivation and emotion]] at the [https://www.canberra.edu.au/current-students University of Canberra]. I am a 3rd year psychology student. == Hobbies == [[File:Listas! (180948337).jpg|thumb|'''Figure 1'''. Swimming is good for both your physical and emotional health. |300x300px]] * Playing sport ** Walking ** [[w:League_tag|League tag]] ** Oztag ** [[Swimming]] * Cooking * Crafts * Reading == Book chapter I'm working on == The book chapter I am working on is [[Motivation and emotion/Book/2026/Youth environmental activism motivation|Youth environmental activism motivation-What motivates young people to engage in environmental activism?]] == Social contributions == # [https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FAkrasia&diff=2826105&oldid=2826068 Capitalized Letter I] #[[Talk:Motivation and emotion/Book/2026/Sex work motivation|Made a suggestion]] #[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/456345 Shared what motivates me] #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FAkrasia&diff=2835157&oldid=2834189 Removed double spacing in text] #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FArtificial_intelligence_and_academic_motivation&diff=2835171&oldid=2833227 Corrected spelling of several] rk5peaponczn0lvrs9bqpnnwnlxjl1v 0 331771 2835222 2831260 2026-09-30T19:18:41Z Dick Bos 24466 object ref Nap 2835222 wikitext text/x-wiki {{10% done}} Welcome to the pages about '''David Ricardo'''. David Ricardo (1772–1823) was an English stockbroker, economist and politician. He made particularly significant contributions to the development of economic science and is often mentioned in the same breath as the "founder of economics", [[Adam Smith]]. He maintained close contact with contemporaries such as Malthus and the Mills, father and son. He was born in London. His father, a Sephardic Jew of Portuguese origin, was a successful stockbroker. David Ricardo received little formal education. He started working with his father at the age of 14. Ricardo defined '''political economy''' as the science, concerned with the distribution of the social product among the different classes of society: wages, profit and rent.{{sfn|Napoleoni|1975|p=[https://archive.org/details/lish0000unse_k7m1/page/61/mode/1up 61]}} (...) == Works == After his (early) retirement he developed an interest in economic theory. He read Adam Smith's ''Wealth of Nations'' and subsequently published some articles in newspapers and pamphlets: * ''The High Price of Bullion, a Proof of the Depreciation of Bank Notes'' (1810)<ref name=bul>{{cite book | last = Ricardo | first = David | authorlink = David Ricardo | date = 1810 | title = The High Price of Bullion, a Proof of the Depreciation of Bank Notes | location = London | publisher = John Murray }} [[:s:en:The High Price of Bullion | Third edition ("with additions", 1810)]] on [[Image:wikisource-logo.svg|16x16px]] WikiSource. </ref> * ''[[David Ricardo/An Essay on Profits|An Essay on the Influence of a Low Price of Corn on the Profits of Stock]]'' (1815, often shortly named ''(An) Essay on Profits''). A few years later his Magnum Opus was first published: * ''On the Principles of Political Economy and Taxation'' (1817) == Method == == Addition resources == * [[:w:en:David Ricardo|David Ricardo]]—at English Wikipedia == Sources and further reading == * {{cite book | last = Napoleoni | first = Claudio | author-link = :w:en:Claudio Napoleoni | date = 1975 | title = Smith, Ricardo, Marx | location = | publisher = Basil Blackwell | url = https://archive.org/details/lish0000unse_k7m1 | url-access = restricted | ref = harv }} == References == {{references}} fjlnedtsjauzkqgxx3u03m43zg8tdrq 2 331786 2835213 2831044 2026-09-30T17:29:55Z Dc.samizdat 2856930 2835213 wikitext text/x-wiki {{align|center|David Brooks Christie}} {{align|center|dc@samizdat.org}} {{align|center|Draft in progress}} {{align|center|June 2023 - September 2026}} <blockquote>'''Abstract:''' The physical universe is properly visualized as real Euclidean space of four orthogonal spatial dimensions <math>\mathbb{R}^4</math>. The surface of a spherical region of 4-dimensional Euclidean space is a curved, finite 3-dimensional space <math>\mathbb{S}^3</math>, dimensionally analogous to the 2-dimensional surface <math>\mathbb{S}^2</math> of an ordinary sphere. Gravitational orbits in 4-space are geodesic circles on an <math>\mathbb{S}^3</math> surface. Unlike geodesic great circles on an <math>\mathbb{S}^2</math> surface which lie in a central plane of the ordinary sphere, orbital circles in 4-space are isoclinic geodesics which curve equally in all four dimensions and lie on the surface of a Clifford torus. They are helical great circles which occur in left and right chiral forms. In isoclinic rotations of rigid 4-polytopes, the vertices orbit on such helical great circles on <math>\mathbb{S}^3</math>. Gravitational orbits are isoclinic circles of rotation on <math>\mathbb{S}^3</math>, and the discrete isoclinic rotations of the regular 4-polytopes are distinguishing properties of fundamental objects in geometry, relativity and quantum mechanics.</blockquote> == Summary == We observe that: * Gravitational orbits in <math>\mathbb{R}^4</math> are chiral isoclinic circles on <math>\mathbb{S}^3</math> in the Kepler system's proper inertial reference frame. * General relativity describes the motion of objects in four-dimensional Euclidean space. == The Kepler problem is framed in Euclidean 4-space == The [[W:Kepler problem|Kepler problem]] is named for [[W:Johannes Kepler|Johannes Kepler]], arguably the greatest geometer since the ancients up to [[w:Ludwig Schläfli|Ludwig Schläfli]], who proposed [[W:Kepler's laws of planetary motion|Kepler's laws of planetary motion]] which solved the problem of the orbits of the planets, and investigated the types of forces that would result in orbits obeying those laws. Those forces were later identified by [[W:Isaac Newton|Isaac Newton]] in his[[W:Philosophiæ Naturalis Principia Mathematica| Principia]], where he proves what today might be called the "inverse Kepler problem": the orbit characteristics require the force to depend on the inverse square of the distance.<ref>{{Cite book|last=Feynman|first=Richard|title=Feynman's Lost Lecture: The Motion of Planets Around the Sun|date=1996|publisher=W. W. Norton & Company|isbn=978-0393039184}}</ref> The inverse square law behind the Kepler problem is the [[W:Central force|central force]] law which governs not only [[W:Newtonian gravity|Newtonian gravity]] and celestial orbits, but also the motion of two charged particles in [[W:Coulomb’s law|Coulomb’s law]] of [[W:Electrostatics|electrostatics]]; it applies to attractive or repulsive forces. Problems in which two bodies interact by a central force that varies as the [[W:Inverse square law|inverse square]] of the distance between them are called Kepler problems. Thus the [[W:Hydrogen atom|hydrogen atom]] is a Kepler problem, since it comprises two charged particles interacting by Coulomb's law, another inverse-square central force. Using classical mechanics, the solution to a Kepler problem can be expressed as a [[W:Kepler orbit|Kepler orbit]] using six kinematical variables or [[W:Orbital elements|orbital elements]]. The solution conserves an orbital element called the [[W:Laplace–Runge–Lenz vector|Laplace–Runge–Lenz (LRL) vector]], a [[W:Constant of motion|constant of motion]], meaning that it is the same no matter where it is calculated on the orbit. The LRL vector was essential in the first quantum mechanical derivation of the [[W:Atomic emission spectrum|spectrum]] of the hydrogen atom, but this approach has rarely been used since the development of the [[W:Schrödinger equation|Schrödinger equation]]. The conservation of the LRL vector corresponds to the <math>SO(4)</math> symmetry, by Nother's theorem. The LRL vector lies orthogonal to both the orbital plane and the angular momentum vector of the Kepler orbit; we observe that it lies in a fourth orthogonal dimension. Fock in 1935<ref>V. Fock, Zur Theorie des Wasserstoffatoms, Zeitschrift für Physik. 98 (3-4) (1935), 145–154.</ref> and Moser in 1970<ref>J. Moser, Regularization of Kepler’s problem and the averaging method on a manifold, Commun. Pure Appl. 23 (1970), 609–636</ref> observed that the Kepler problem is mathematically equivalent to non-affine geodesic motion (a particle moving freely) on the surface of a 3-sphere, so that the whole problem is symmetric under certain rotations of the four-dimensional space. This higher-dimensional symmetry results in two well-known properties of the Kepler problem: the momentum vector always moves in a perfect circle and, for a given total energy, all such velocity circles intersect each other in the same two points. ... Relativity establishes that an orbit in space is viewed in a different way in each distinct inertial reference frame. Depending on the choice of reference frame, the same Kepler system may be seen to be performing any one of a sequence of relativistically equivalent rotations in 4-space, on a continuum from an isoclinic rotation (Q²) in the orbit's proper reference frame, to a screw transfer (QT) with a simple rotation component (Q) and a translation component (T) at velocity <math>c</math>, in the universal reference frame of 4-coordinate space wherein every object is seen to be translating at velocity <math>c</math>. In reference frames between these two limit cases, the orbit is seen to be performing a double rotation (Q²) at two unequal, completely orthogonal angular rates of rotation: an elliptical double rotation. These include the reference frames of most typical observers, who are moving slowly relative to the observed orbital system's reference frame (the relative motion is a small fraction of the speed of light). These typical observations agree closely with the predictions of special relativity, because the non-isoclinic elliptical (Q²) resembles a (QT). Since one of its two completely orthogonal rotations (Q) has such a long period, it is almost indistinguishable from a straight translation (T).{{Efn| ...this paragraph is probably misplaced here and should not interrupt the discussion at this point}} All orbits in 4-space are isoclinic in their own reference frame. Orbiting objects in their own proper Kepler systems follow circular geodesic isoclines through 4-space. Orbits in 4-space are perfectly circular in their own reference frame, as Copernicus assumed the orbits of planets to be. It is the orbit's path through the 3-space of its elliptic hyperplane that is an ellipse, as Kepler found it to be.{{Efn| ...cite Jesper Goransson's very concise paper}} The geodesic circle that an orbiting object follows through 4-space in the proper reference frame of its own Kepler system is not a simple great circle which turns in two orthogonal dimensions. It is a helical great circle that turns in four orthogonal dimensions at once.{{Efn|Geodesic orbits in 4-space are not simple 2-dimensional great circles; they are helical 4-dimensional great circles that curve in all four dimensions at once. Their circular trajectories are helixes which we call ''isoclines'', since they are the paths taken by points on a rigid object undergoing isoclinic rotation.}} Such circles lie outside our physical experience, since our local space has only three orthogonal dimensions to turn in. Nonetheless we can visualize them in imagination, because their helical, circular shape is perfectly well defined by the kinematical variables of the Kepler orbit. The real physical correlates of abstract orthogonal planes and rotation angles are already familiar to us viscerally in our body-language of physical experience, since we are endowed biologically with highly evolved visual signal processing engines. These enable us to see and understand spatial relations and motions, including rotations, without even thinking about angles and orthogonal planes. This physical endowment is an inborn capacity for dimensional analogy which our biologic evolution has provided. All our instinctive spatial reasoning is by dimensional analogy from flat 2-dimensional retinal images to 3-dimensional scenes, using our powerful inborn visualization capacities of reverse stereographic projection and pattern recognition. We humans are thus very well equipped with everything we need to see in four-dimensional space, except experience. ... Recently Anco and Moghadam found that through Noether’s theorem in reverse, the LRL vector gives rise to a corresponding infinitesimal dynamical symmetry on the kinematical variables, which they show to be the semi-direct product of <math>SO(3)</math> and <math>\mathbb{R}^3</math>, in contrast to the <math>SO(4)</math> symmetry group generated by the LRL symmetries and the rotations.{{Sfn|Anco|Moghadam|2026|ps=; The physically relevant part of the LRL vector is its direction ... since its magnitude is just a function of energy and angular momentum.}} This remarkable symmetry breaking is expressive of the ''dimensional relativity'' between ordinary 3-space <math>\mathbb{R}^3</math>, spherical space <math>\mathbb{S}^3</math> and Euclidean space <math>\mathbb{R}^4</math>. ... Consider a hydrogen atom in a Kepler orbit: for example, a hydrogen atom moving freely in space in an orbit around the sun. It is a ''double'' Kepler problem: an electrostatic Kepler problem within itself, and a gravitational Kepler problem in its environment. The ''single'' electrostatic Kepler problem of a hydrogen atom moving freely in space beyond any gravitational influence is a problem in special relativity. In our Euclidean 4-space model, this atom viewed as stationary in its own proper reference frame exhibits an <math>SO(4)</math> rotation symmetry corresponding to an isoclinic double rotation (<math>\mathrm{Q^2}</math>). The fourth dimension in this reference frame is the atom's proper time vector; it has constant velocity <math>c</math> and constant direction. From the point of view of our universal 4-coordinate space (which cannot be the proper inertial reference frame of any physical observer, all of whom are moving relative to it at velocity <math>c</math>), the entire Kepler system (the atom) is translating through 4-space via a screw translation (<math>\mathrm{QT}</math>) at constant velocity <math>c</math>. From this viewpoint the atom has only a simple <math>SO(3)</math> rotation component (<math>\mathrm{Q}</math>), breaking its stationary <math>SO(4)</math> isoclinic rotation symmetry (<math>\mathrm{Q^2}</math>). Because each discrete part of the rotating atom moves along a helical trajectory through 4-space, the atom is in orbit around a barycentric axis (like a star in a galaxy), but only in a tiny orbit within its own radius, which is its inertial domain of rotation. The straight 4-dimensional cylinder it progresses along at velocity <math>c</math> is very narrow: only the diameter of the rotating atom itself. The gravitational Kepler problem of a hydrogen atom in a Kepler orbit around the sun is a problem in general relativity. In our 4-space model, this atom viewed in its own proper reference frame exhibits the same <math>SO(4)</math> rotation symmetry as it did in the electrostatic Kepler problem where the atom was translating linearly through space. But the Kepler system in this case is not just the atom; it is the entire solar system. The LRL vector of this Kepler system is the proper time vector of the atom's inertial reference frame; once again it has constant velocity ''and constant direction''. Although the momentum vector moves in a perfect circle as the atom orbits the sun, the 4-space LRL vector does not move at all: it is a constant of motion, of linear motion (<math>\mathrm{T}</math>) of the Kepler system (the entire solar system in this case) in a constant 4-space direction, the proper time direction of the system. The direction of the system's proper time vector would vary under some kinds of acceleration of the atom, but it is constant under this kind of orbital acceleration. It continues to point in the same direction, like a 4-space compass needle, as the atom winds its way along its spiral path around the axis of the sun's straight-line translation through 4-space at velocity <math>c</math>. This compass needle always points in the direction the sun is moving, not the direction the atom is moving at any instant. ...Its Kepler orbit around the sun is its <math>SO(3)</math> rotation component (<math>\mathrm{Q}</math>). Although the atom is moving on a geodesic circle in the second problem, by the [[equivalence principle]] the difference in the state of the atomic systems in these two problems cannot be observed by examining the atoms alone. Even from another inertial reference frame, where the atom in the second problem is seen to be translating through 4-space via a screw translation (<math>\mathrm{QT}</math>) around the sun's axis of motion, there is still no difference between the two problems which can be detected by examining only the atoms within their own proper reference frames (even over time), because the LRL vector (<math>\mathrm{T}</math>) is a constant of motion of the entire system in both cases. ...Anco and Maghadam found that <math>SO(4)</math>) breaks to ... <math>\mathbb{S}^3</math>)... if the energy in the Kepler orbit is negative (an elliptical orbit), and to ... <math>\mathbb{H}^3</math>) ... Minkowski spacetime if the energy is positive (a hyperbolic orbit). ... Finally we consider a third problem in which a hydrogen atom enters the solar system as a comet, loops around the sun and exits the solar system again. This atom... ... As Hamilton found when he discovered the quaternions, we see that it is necessary to admit a fourth dimension to the system in order to properly model the problem: in Hamilton's case the general problem of ..., and in our case the Kepler problem. These are instances of the same problem in 4-dimensional Euclidean geometry, and indeed a solution to the Kepler problem in quaternions (the four Cartesian coordinates of Euclidean 4-space) is a solution to it in our model of the 4-coordinate Euclidean cosmos. == Rotations == The [[wikipedia:Rotations in 4-dimensional Euclidean space#Isoclinic_rotations|isoclinic rotations]] of the convex [[wikipedia:regular 4-polytope|regular 4-polytopes]] are usually described as discrete rotations of a rigid object. For example, the rigid [[24-cell]] can rotate in a [[24-cell#Great hexagons|hexagonal]] (6-vertex) central [[24-cell#Planes of rotation|plane of rotation]]. A 4-dimensional [[24-cell#Isoclinic rotations|''isoclinic'' rotation]] (as distinct from a [[24-cell#Simple rotations|''simple'' rotation]] like the ones that occur in 3-dimensional space) is a ''diagonal'' rotation in multiple [[wikipedia:Clifford parallel|Clifford parallel]] [[24-cell#Geodesics|central planes]] of rotation at once. It is diagonal because it is a [[wikipedia:SO(4)#Double_rotations|double rotation]]: in addition to rotating in parallel (like wheels), the multiple planes of rotation also tilt sideways in the completely orthogonal plane of rotation (like coins flipping) into each other's planes. Consequently, the path taken by each vertex is a [[24-cell#Helical hexagrams and their isoclines|twisted helical circle]], rather than the ordinary flat great circle a vertex follows in a simple rotation. In a rigid 4-polytope rotating isoclinically, ''all'' the vertices lie in one of the parallel planes of rotation, so all the vertices move in parallel along Clifford parallel twisting circular paths. [[24-cell#Clifford parallel polytopes|Clifford parallel planes]] are not parallel in the normal sense of parallel planes in three dimensions; the vertices are all moving in different directions around the [[wikipedia:3-sphere|3-sphere]]. In one complete 360° isoclinic revolution, a rigid 4-polytope turns itself inside out. This is sufficiently different from the simple rotations of rigid bodies in our 3-dimensional experience that a [[24-cell#Rotations|detailed description]] enabling the reader to properly visualize its counter-intuitive consequences runs to many pages and illustrations, with many accompanying pages of explanatory notes on surprising phenomena that arise in 4-dimensional space: [[24-cell#Great squares|completely orthogonal planes]], [[24-cell#Clifford parallel polytopes|Clifford parallelism]]{{Efn|name=Clifford parallels}} and [[wikipedia:Hopf fibration|Hopf fiber bundles]], [[24-cell#Isoclinic rotations|isoclinic geodesic paths]], and [[24-cell#Double rotations|chiral (mirror image) pairs of rotations]], among other complexities. Moreover, the characteristic rotations of the various regular 4-polytopes are all different; each is a unique surprise. [[User:Dc.samizdat/Rotations#Sequence of regular 4-polytopes|The 6 regular convex 4-polytopes]] have different numbers of vertices (5, 8, 16, 24, 120 and 600 respectively) and those with fewer vertices occur inscribed in those with more vertices (with one exception), with the result that the more complex 4-polytopes subsume the kinds of rotations characteristic of their less complex predecessors, as well as each having a characteristic kind of rotation not found in their predecessors. None of these symmetries is to be found in 3-dimensional space, although their simpler 3-dimensional analogues are all present there. [[wikipedia:Euclidean geometry#Higher_dimensions|Four dimensional Euclidean space]] is more complicated (and more interesting) than three dimensional space because there is more room in it, in which unprecedented things can happen. It subsumes 3-dimensional space, with all of the symmetries we are accustomed to, and adds astonishing new surprises. These are hard for us to visualize, because the only way we can experience them is in our imagination; we have no body of sensory experience in 4-dimensional space to draw upon, other than our evolution in time. For that reason (our difficulty in visualizing them), descriptions of isoclinic rotations usually begin and end with rigid rotations: [[24-cell#Isoclinic rotations|for example]], all 24 vertices of a single rigid 24-cell rotating in unison, with 6 vertices evenly spaced around each of 4 Clifford parallel twisted circles.{{Efn|name=360 degree geodesic path visiting 3 hexagonal planes}} But that is only the simplest case, which is easiest for us to understand. Compound and [[wikipedia:Kinematics|kinematic]] 24-cells (with moving parts) are even more interesting (and more complicated) than the rotation of a single rigid 24-cell. To begin with, when we examine the individual parts of a single rigid 24-cell that are moving in an isoclinic rotation, such as the orbits of individual vertices, we can imagine a case where fewer than 24 point-objects are orbiting on those twisted circular paths at once. [[24-cell#Reflections|For example]], if we imagine just 8 point-objects, evenly spaced around the 24-cell at [[24-cell#Reciprocal constructions from 8-cell and 16-cell|the 8 vertices that lie on the 4 coordinate axes]], and rotate them isoclinically along exactly the same orbits they would take in the above-mentioned rotation of a rigid 24-cell, then in the course of a single 360° rotation the 8 point-objects will trace out the whole 24-cell, with just one point-object reaching each of the 24 vertex positions just once, and no point-object colliding with (or even crossing the path of) any other at any time. This is an example of a discrete Hopf fibration. But it is still an example of a rigid object in a discrete isoclinic rotation: a rigid 8-vertex object (called the 4-[[wikipedia:orthoplex|orthoplex]] or [[16-cell]]) performing one half of the characteristic rotation of the 24-cell. We can also imagine ''combining'' distinct isoclinic rotations. What happens when multiple point-objects are orbiting at once, but do ''not'' all follow the Clifford parallel paths characteristic of the ''same'' distinct rigid rotation? What happens when we combine orbits from distinct rotations characteristic of different 4-polytopes, for example when different rigid 4-polytopes are concentric and rotating simultaneously in their characteristic ways? What kinds of such hybrid rotations are possible in the same 3-sphere shell without collisions? In adjacent concentric shells without asymmetric imbalance? What sort of [[Kinematics of the cuboctahedron|kinematic polytopes]] do they trace out, and how do their [[24-cell#Clifford parallel polytopes|component parts]] relate to each other as they move? Is there (sometimes) some kind of mutual stability amid their lack of combined rigidity? Visualizing isoclinic rotations (rigid and otherwise) allows us to explore such questions of [[wikipedia:kinematics|kinematics]], and where dynamic stabilities arise, of [[wikipedia:kinetics (physics)|kinetics]]. In four dimensions, we discover that space has more room in it than we have experienced, which permits previously unimagined motions. Even 3-space is more commodious than we thought; when it is curved and lies embedded in a higher-dimensional space, it permits previously impossible symmetric packings. Sadoc studied double-twisted 3-dimensional molecules, and imagined them embedded in 4-dimensional space as the Hopf fibrations of regular 4-polytopes. He found that these molecules would close-pack on the 3-sphere perfectly without exhibiting any torsion, although their packing in ordinary flat 3-space is imperfect, "frustrated" by their twisted geometry.<blockquote>The frustration, which arises when the molecular orientation is transported along the two [spiral] AB paths of figure 1 [double twist helix], is imposed by the very topological nature of the Euclidean space R³. It would not occur if the molecules were embedded in the non-Euclidean space of the [[wikipedia:3-sphere|3-sphere]] S³, or hypersphere. This space with a homogeneous positive curvature can indeed be described by equidistant and uniformly twisted fibers, along which the molecules can be aligned without any conflict between compactness and [[wikipedia:torsion of a curve|torsion]].... The fibres of this [[wikipedia:Hopf fibration|Hopf fibration]] are great circles of S³, the whole family of which is also called the [[wikipedia:Clifford parallel|Clifford parallels]].{{Efn|name=Clifford parallels}} Two of these fibers are C_∞ symmetry axes for the whole fibration; each fibre makes one turn around each axis and regularly rotates when moving from one axis to another.{{Efn|name=helical geodesic}} These fibers build a double twist configuration while staying parallel, i.e. without any frustration, in the whole volume of S³.{{Efn|name=Petrie polygon of a honeycomb}} They can therefore be used as models to study the condensation of long molecules in the presence of a double twist constraint.{{Sfn|Sadoc & Charvolin|2009|loc=§1.2 The curved space approach|ps=; studies the helical orientation of molecules in crystal structures and their imperfect packings ("frustrations") in 3-dimensional space.}}</blockquote>Of course we do not find molecules condensing to close-pack the 3-sphere in our experience, and Sadoc does not say that we do. We find 3-spheres in the atomic realm (if atoms are 4-polytopes), and in the cosmic realm (as the surface boundaries of stars, and the concentric surfaces of galaxies). But in between, in the realm of ordinary experience which includes the molecular realm, ourselves and all the objects we can materially handle or observe up close including the planets, we are confined together by gravity as inertia within a curved 3-dimensional space that is no more than one atom thick in the fourth spatial dimension. That is why in the molecular realm we find only objects that occupy 3-spaces which, though infinitesimally curved in the fourth dimension, are tiny patches on whole 3-spheres of galactic size. So Sadoc's exercise is a thought experiment, like Einstein's gedankenexperiments about railroad embankments and trains moving at nearly the speed of light. It is no less illuminating, despite the symmetry it reveals not having a realization as an actual 3-sphere of actual molecules. And might not something very like it have an actual realization in the atomic realm? We know that atoms have their own complex internal structure, which we are unable to model geometrically in ordinary 3-dimensional space. Suppose such a model is impossible because an atom is actually a 4-polytope occupying a tiny spherical region of 4-dimensional space, and so we only find its constituent particles in close-packed helical orbits on the 3-sphere, in the manner of Sadoc's imaginary twisted molecules, but as real 4-dimensional helices of atomic scale. We would expect to find the atomic orbit of a fundamental particle in some discrete Hopf fibration characteristic of a symmetry group, that is, on the maximally symmetric isoclines of a discrete isoclinic rotation characteristic of some regular 4-polytope and the particle. == Relativity in real space of four or more orthogonal dimensions == Special relativity is Galilean relativity in a Euclidean space of four orthogonal dimensions. General relativity is Galilean relativity in a general space of four or more orthogonal dimensions, e.g. in Euclidean 4-space <math>\mathbb{R}^4</math>, spherical 4-space <math>\mathbb{S}^4</math>, or any orthogonal 4-manifold. Light is a consequence of symmetry group reflections at quantum scale. Gravity and the other fundamental forces are consequences of rotations, which are consequences of quantum reflections. Light is discrete reflections. Gravity and all forces are discrete rotations. Both are group actions, expressions of intrinsic symmetries. That is all of physics. Every observer may properly see themself as stationary and the universe as an ''n''-sphere with themself at the center. The curvature of these spheres is a function of the rate at which causality evolves, and can be measured by the observer as the speed of light. 0ntkwu1fzimz4cw6hftjvgiflfri2b6 0 331914 2835244 2832878 2026-09-30T23:58:49Z The Citer 3110681 Added phylogeny! 2835244 wikitext text/x-wiki [[Image:Tionesta-ac-moss2.jpg|thumb|300px|right|This is a [[Plant Divisions (Phyla)/Bryophyta|Bryophyte]].]] Mosses are small, non-vascular seedless plants in the taxonomic division Bryophyta (/braɪˈɒfətə/, /ˌbraɪ.əˈfaɪtə/) sensu stricto. Bryophyta sensu lato may also refer to the parent group, bryophytes, which comprises liverworts, mosses, and hornworts. [[Image:Mose09.jpg|thumb|300px|right]] ==Information== Name Meaning: Bryum-like plant, moss plant English Common Name: Moss Major distinguishing characteristics: Persistent branched sporophytes, no vascular system Approximate number of species described: 12,000 ===Other Facts=== ====DNA Repair==== The moss ''Physcomitrium patens'' has been used as a demonstrative organism to study how plants repair damage to their DNA, especially the repair mechanism known as homologous recombination. [[Image:RedMoss.jpg|thumb|300px|right]] ==Evolutionary History== The fossil record of moss is sparse, due to their soft-walled and fragile nature. However, unambiguous moss fossils have been recovered from as early as the Permian of Antarctica and Russia, and a case has been made for Carboniferous mosses. It has further been claimed that tube-like fossils from the Silurian are the macerated remains of moss operculum. Mosses also seem to evolve 2–3 times slower than ferns, gymnosperms and angiosperms. ==Classes== Andreaeobryopsida – Andreaeopsida – Bryopsida – Oedipodiopsida – Sphagnopsida – Takakiopsida – Tetraphidopsida ==Phylogeny== {{clade |1={{clade |1=Tracheophyta [[File:Cycas rumphii-IMG 9702.JPG|60px]] |label2=Pan-Bryophyta |2={{clade |1=[[Plant Divisions (Phyla)/Anthocerotophyta|Anthocerotophyta]] [[File:Hornwort (3144429129).jpg|60px]] |2={{clade |1=[[Plant Divisions (Phyla)/Marchantiophyta|Marchantiophyta]] [[File:Lunularia cruciata.jpg|60px]] |label2='''Bryophyta''' |2={{clade |1=Takakiopsida [[File:Takakia lepidozioides.jpg|60px]] |2=Sphagnopsida [[File:Nationaal Park Drents-Friese Wold. Locatie Fochteloërveen 01-09-2020. (actm.) 15.jpg|60px]] |3={{clade |1=Andreaeopsida [[File:Andreaea rupestris (b, 150028-481738) 3756.JPG|60px]] |2=Andreaeobryopsida [[File:Haeckel Muscinae.jpg|60px]] |label3=Neomusci |3={{clade |1=Oedipodiopsida [[File:Oedipodium griffithianum 1.jpg|60px]] |label2=Cenomusci |2={{clade |1=Polytrichopsida [[File:Polytrichum piliferum female colony.jpg|60px]] |label2=Altamusci |2={{clade |1=Tetraphidopsida [[File:Tetrodontium brownianum 2022.jpg|60px]] |2=Bryopsida [[File:Bryopsida.jpg|60px]] }} }} }} }} }} }} }} }} }} ==References== [[Wikipedia:Moss]] [[Category:Plants]] [[Category:Taxonomy]] [[Category:Botany]] [[Category:Biology]] t64qwcxysnwwys5khw2cb4716iwkdkj 0 331991 2835245 2834020 2026-10-01T00:23:00Z The Citer 3110681 Added phylogeny! 2835245 wikitext text/x-wiki [[Image:Tree of Angiosperm Phylogeny 2024.jpg|thumb|300px|right|Many species of Angiospermae phylogenetic picture.]] Flowering plants are plants that bear flowers and fruits, and form the clade Angiospermae (/ˌændʒiəˈspɜːrmiː/). The term ''angiosperm'' is derived from the Greek words ἀγγεῖον (angeion; 'container, vessel') and σπέρμα (sperma; 'seed'), meaning that the seeds are enclosed within a fruit. The group was formerly called Magnoliophyta. Angiosperms are by far the most diverse group of land plants with 64 orders, 416 families, approximately 13,000 known genera and 300,000 known species! The diversity of flowering plants is not evenly distributed. Nearly all species belong to the eudicot (75%), monocot (23%), and magnoliid (2%) clades. The remaining five clades contain a little over 250 species in total; i.e. less than 0.1% of flowering plant diversity, divided among nine families. The 25 most speciated families are: {| class="wikitable sortable" |+ The 25 largest angiosperm families |- ! <!--Rank, by size--> !! Group !! Family !! English name !! No. of spp. |- | 1 || Eudicot || Asteraceae or Compositae || daisy || 22,750 |- | 2 || Monocot || Orchidaceae || orchid || 21,950 |- | 3 || Eudicot || Fabaceae or Leguminosae || pea, legume || 19,400 |- | 4 || Eudicot || Rubiaceae || Rubia|madder || 13,150<ref>{{cite web|title=Kew Scientist 30|date=October 2006|url=https://www.kew.org/kewscientist/ks_30.pdf|archive-url=https://web.archive.org/web/20070927005410/https://www.kew.org/kewscientist/ks_30.pdf|archive-date=27 September 2007}}</ref> |- | 5 || Monocot || Poaceae or Gramineae || grass || ~12,000 |- | 6 || Eudicot || Lamiaceae or Labiatae || mint || 7,175 |- | 7 || Eudicot || Euphorbiaceae || spurge || 5,735 |- | 8 || Eudicot || Melastomataceae || melastome || 5,005 |- | 9 || Eudicot || Myrtaceae || myrtle || 4,625 |- | 10 || Eudicot || Apocynaceae || dogbane || 4,555 |- | 11 || Monocot || Cyperaceae || sedge || 4,350 |- | 12 || Eudicot || Malvaceae || mallow || 4,225 |- | 13 || Monocot || Araceae || arum || 4,025 |- | 14 || Eudicot || Ericaceae || heath || 3,995 |- | 15 || Eudicot || Gesneriaceae || gesneriad || 3,870 |- | 16 || Eudicot || Apiaceae or Umbelliferae || parsley || 3,780 |- | 17 || Eudicot || Brassicaceae or Cruciferae || cabbage || 3,710 |- | 18 || Magnoliid dicot || Piperaceae || pepper || 3,600 |- | 19 || Monocot || Bromeliaceae || bromeliad || 3,540 |- | 20 || Eudicot || Acanthaceae || acanthus || 3,500 |- | 21 || Eudicot || Rosaceae || rose || 2,830 |- | 22 || Eudicot || Boraginaceae || borage || 2,740 |- | 23 || Eudicot || Urticaceae || nettle || 2,625 |- | 24 || Eudicot || Ranunculaceae || buttercup || 2,525 |- | 25 || Magnoliid dicot || Lauraceae || laurel || 2,500 |} ==More facts== ===Name Meaning=== Magnolia-like plant ===Major distinguishing characteristics=== Flowers and fruit, vascular system with vessels ==Evolutionary history== Fossilised spores suggest that embryophytes have existed for at least 475 million years<ref>{{cite journal |last=Edwards |first=D. |title=The role of mid-palaeozoic mesofossils in the detection of early bryophytes |journal=Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences |volume=355 |issue=1398 |pages=733–54; discussion 754–5 |date=June 2000 |pmid=10905607 |pmc=1692787 |doi=10.1098/rstb.2000.0613 }}</ref> However, angiosperms appeared suddenly and rapidly diversified during the Valanginian (beginning ~130 mya), much later than other major plant groups.<ref>{{Cite journal |last1=Herendeen |first1=Patrick S. |last2=Friis |first2=Else Marie |last3=Pedersen |first3=Kaj Raunsgaard |last4=Crane |first4=Peter R. |date=2017-03-03 |title=Palaeobotanical redux: revisiting the age of the angiosperms |url=https://rdcu.be/c0Zhm |journal=Nature Plants |volume=3 |issue=3 |page=17015 |doi=10.1038/nplants.2017.15 |pmid=28260783 |bibcode=2017NatPl...317015H |s2cid=205458714 |issn=2055-0278}}</ref><ref>{{Cite journal |last=Friedman |first=William E. |date=January 2009 |title=The meaning of Darwin's "abominable mystery" |url=https://onlinelibrary.wiley.com/doi/10.3732/ajb.0800150 |journal=American Journal of Botany |volume=96 |issue=1 |pages=5–21 |doi=10.3732/ajb.0800150 |pmid=21628174|bibcode=2009AmJB...96....5F |url-access=subscription }}</ref> The evolutionary success and rapid diversification of angiosperms are largely attributed to their coevolutionary relationships with animal pollinators, particularly insects, birds, and bats. Unlike [https://en.wikipedia.org/wiki/Gymnosperm gymnosperms], which today rely on wind for pollen dispersal, angiosperms developed specialized traits—such as nectar production, vivid pigmentations, and complex volatile scents—to attract specific floral visitors. ==Classes== No one really knows how to divide Angiospermae into classes, unless you only count one class (Magnoliopsida). (See [[Talk:Plant Divisions (Phyla)/Magnoliophyta|talk]]) However, we can still list the defined orders. ===Orders=== Acorales – Alismatales – Amborellales – Apiales – Aquifoliales – Arecales – Asparagales – Asterales – Austrobaileyales – Berberidopsidales – Boraginales – Brassicales – Bruniales – Buxales – Canellales – Caryophyllales – Celastrales – Ceratophyllales – Chloranthales – Commelinales – Cornales – Crossosomatales – Cucurbitales – Dilleniales – Dioscoreales – Dipsacales – Ericales – Escalloniales – Fabales – Fagales – Garryales – Gentianales – Geraniales – Gunnerales – Huerteales – Icacinales – Lamiales – Laurales – Liliales – Magnoliales – Malpighiales – Malvales – Metteniusales – Myrtales – Nymphaeales – Oxalidales – Pandanales – Paracryphiales – Petrosaviales – Picramniales – Piperales – Poales – Proteales – Ranunculales – Rosales – Santalales – Sapindales – Saxifragales – Solanales – Trochodendrales – Vahliales – Vitales – Zingiberales – Zygophyllales{{sfnp|ps=none|APG IV|2016|p=5}} ==Phylogeny== {{clade |label1=Magnoliophyta |1={{clade |1=Amborellaopsida [[File:Amborella trichopoda (3173820625)-2.jpg|60px]] |2={{clade |1=Nymphaeaopsida [[File:Aampal poov.JPG|60px]] |2={{clade |1=Austrobaileyaopsida [[File:Austrobaileya-scandens-SF24315-01.jpg|60px]] |2={{clade |label1='''Mesomagnoliopsida''' |1={{clade |1=Magnoliidae [[File:Asimina triloba - pawpaw - desc-flower.jpg|60px]] |2=Chloranthales [[File:Sarcandra glabra2.jpg|60px]] |label3=''Pancota'' |3={{clade |1=Monocota [[File:Banana-Single.jpg|60px]][[File:Dew on grass Luc Viatour.jpg|60px]] |label2=Dicota |2={{clade |label1=''Paradicota'' |1=Ceratophyllales [[File:Ceratophyllum demersum s. str. sl2.jpg|60px]] |2=Eudicota [[File:Acer pseudoplatanus Chaltenbrunnen.jpg|60px]] [[File:Sunflowers in Canada1.JPG|60px]] }} }} }} }} }} }} }} }} ==Quiz== [[Plant Divisions (Phyla)/Magnoliophyta/Quiz]] ==References== [[Wikipedia:Flowering plant]]<br> [[Wikispecies:Magnoliopsida]] [[Category:Plants]] [[Category:Taxonomy]] [[Category:Botany]] [[Category:Biology]] [[Category:Flowers]] m2si2kwkbsj8jwi3kvj7cmitwp0kjlq 2 332116 2835206 2834015 2026-09-30T15:40:36Z JonAwbrey 29537 cleanup Minimal Negation Operators 0, 1, 2, 3 Arguments + latex table for Logical Boundaries and Their Complements 2835206 wikitext text/x-wiki ==Minimal Negation Operators 0, 1, 2, 3 Arguments== ===PNG=== {| align="center" style="text-align:center" | [[File:Minimal Negation Operators 0, 1, 2, 3 Arguments 2.0.png|500px]] |} ===LaTeX=== {| align="center" cellpadding="4" style="text-align:center" | <math>\begin{matrix} \texttt{()} & = & \nu_0 & = & 0 & = & \mathrm{false} \\[6pt] \texttt{(} x \texttt{)} & = & \nu_1 (x) & = & \tilde{x} & = & x\prime \\[6pt] \texttt{(} x \texttt{,} y \texttt{)} & = & \nu_2 (x, y) & = & \tilde{x}y \lor x\tilde{y} & = & x\prime y \lor x y\prime \\[6pt] \texttt{(} x \texttt{,} y \texttt{,} z \texttt{)} & = & \nu_3 (x, y, z) & = & \tilde{x}yz \lor x\tilde{y}z \lor xy\tilde{z} & = & x\prime y z \lor x y\prime z \lor x y z\prime \end{matrix}</math> |} ==Logical Boundaries and Their Complements== ===PNG=== {| align="center" style="text-align:center; font-size:large" | <math>\text{Table 3. Logical Boundaries and Their Complements}</math> |- | [[File:Logical Boundaries and Their Complements.png|600px]] |} ===LaTeX=== <br> {| align="center" border="1" cellpadding="8" cellspacing="0" style="text-align:center; width:60%" |+ <math>\text{Table 3. Logical Boundaries and Their Complements}</math> |- style="background:ghostwhite" | <math>\mathcal{L}_1</math> | <math>\mathcal{L}_2</math> | <math>\mathcal{L}_3</math> | <math>\mathcal{L}_4</math> |- style="background:ghostwhite" | &nbsp; | align="right" | <math>p\colon</math> | <math>1~1~1~1~0~0~0~0</math> | &nbsp; |- style="background:ghostwhite" | &nbsp; | align="right" | <math>q\colon</math> | <math>1~1~0~0~1~1~0~0</math> | &nbsp; |- style="background:ghostwhite" | &nbsp; | align="right" | <math>r\colon</math> | <math>1~0~1~0~1~0~1~0</math> | &nbsp; |- | <math>\begin{matrix} f_{104} \\[4pt] f_{148} \\[4pt] f_{146} \\[4pt] f_{97} \\[4pt] f_{134} \\[4pt] f_{73} \\[4pt] f_{41} \\[4pt] f_{22} \end{matrix}</math> | <math>\begin{matrix} f_{01101000} \\[4pt] f_{10010100} \\[4pt] f_{10010010} \\[4pt] f_{01100001} \\[4pt] f_{10000110} \\[4pt] f_{01001001} \\[4pt] f_{00101001} \\[4pt] f_{00010110} \end{matrix}</math> | <math>\begin{matrix} 0~1~1~0~1~0~0~0 \\[4pt] 1~0~0~1~0~1~0~0 \\[4pt] 1~0~0~1~0~0~1~0 \\[4pt] 0~1~1~0~0~0~0~1 \\[4pt] 1~0~0~0~0~1~1~0 \\[4pt] 0~1~0~0~1~0~0~1 \\[4pt] 0~0~1~0~1~0~0~1 \\[4pt] 0~0~0~1~0~1~1~0 \end{matrix}</math> | <math>\begin{matrix} \texttt{(}~p~\texttt{,}~q~\texttt{,}~r~\texttt{)} \\[4pt] \texttt{(}~p~\texttt{,}~q~\texttt{,}(r\texttt{))} \\[4pt] \texttt{(}~p~\texttt{,(}q\texttt{),}~r~\texttt{)} \\[4pt] \texttt{(}~p~\texttt{,(}q\texttt{),(}r\texttt{))} \\[4pt] \texttt{((}p\texttt{),}~q~\texttt{,}~r~\texttt{)} \\[4pt] \texttt{((}p\texttt{),}~q~\texttt{,(}r\texttt{))} \\[4pt] \texttt{((}p\texttt{),(}q\texttt{),}~r~\texttt{)} \\[4pt] \texttt{((}p\texttt{),(}q\texttt{),(}r\texttt{))} \end{matrix}</math> |- | <math>\begin{matrix} f_{233} \\[4pt] f_{214} \\[4pt] f_{182} \\[4pt] f_{121} \\[4pt] f_{158} \\[4pt] f_{109} \\[4pt] f_{107} \\[4pt] f_{151} \end{matrix}</math> | <math>\begin{matrix} f_{11101001} \\[4pt] f_{11010110} \\[4pt] f_{10110110} \\[4pt] f_{01111001} \\[4pt] f_{10011110} \\[4pt] f_{01101101} \\[4pt] f_{01101011} \\[4pt] f_{10010111} \end{matrix}</math> | <math>\begin{matrix} 1~1~1~0~1~0~0~1 \\[4pt] 1~1~0~1~0~1~1~0 \\[4pt] 1~0~1~1~0~1~1~0 \\[4pt] 0~1~1~1~1~0~0~1 \\[4pt] 1~0~0~1~1~1~1~0 \\[4pt] 0~1~1~0~1~1~0~1 \\[4pt] 0~1~1~0~1~0~1~1 \\[4pt] 1~0~0~1~0~1~1~1 \end{matrix}</math> | <math>\begin{matrix} \texttt{(((}p\texttt{),(}q\texttt{),(}r\texttt{)))} \\[4pt] \texttt{(((}p\texttt{),(}q\texttt{),}~r~\texttt{))} \\[4pt] \texttt{(((}p\texttt{),}~q~\texttt{,(}r\texttt{)))} \\[4pt] \texttt{(((}p\texttt{),}~q~\texttt{,}~r~\texttt{))} \\[4pt] \texttt{((}~p~\texttt{,(}q\texttt{),(}r\texttt{)))} \\[4pt] \texttt{((}~p~\texttt{,(}q\texttt{),}~r~\texttt{))} \\[4pt] \texttt{((}~p~\texttt{,}~q~\texttt{,(}r\texttt{)))} \\[4pt] \texttt{((}~p~\texttt{,}~q~\texttt{,}~r~\texttt{))} \end{matrix}</math> |} twid5eguu9t0uf7m4tywd1485fitts3 2 332158 2835246 2834880 2026-10-01T00:57:20Z The Citer 3110681 2835246 wikitext text/x-wiki My template, text, and phrase storage! ==Templates== [[File:|thumb|300x300px|[Insert_text_here]]], [[File:|60px]] ==Text== – ==Phrases== <nowiki>''Incertae sedis''</nowiki> ==Purpose== It's a storage space so I don't have to copy text in source editor; I just can copy it in reading mode. =[Unused NAME]= [[Wikipedia:Superrosids|Superrosidia]], [[Wikipedia:Rosids|Rosida]], [[Wikipedia:Rosids|Eurosida]], Fabidae, Malvidae<br> [[Wikipedia:Superasterids|Superasteridia]], [[Wikipedia:Asterids|Asterida]], [[Wikipedia:Asterids|Euasterida]], campanulidae, lamiidae ir0ecbu4u7f6z1m69xkm1b7p3wdzyqy 0 332203 2835273 2834379 2026-10-01T05:01:42Z U3285438 3103750 shifted figure to the right and updated its caption (renamed figure 2, to avoid duplication) 2835273 wikitext text/x-wiki {{title|Parental motivations for homeschooling:<br>What motivates parents to homeschool their children?}} == '''Overview:''' == <div style="border:1px solid #668cff; border-radius:6px; padding:10px; margin:8px 4px 25px 4px;"> '''“Choosing homeschooling or Traditional Schooling?”''' Think of it this way: You're one of the parents of 2 Children who attend a local school. Over time, you become worried/concerned that your children's education doesn't reflect the type of learning environment you want for them. After the school days your children express that they are being bullied and are feeling quite a bit of academic pressure. Your partner expresses that your children would learn better with greater flexibility and more individual attention. You sit down together to assess what you both think would be best for your children, and after considering their options, you decide to begin homeschooling. But what is actually motivating their decision? </div> {{expand}} <div style="border:1px solid #a2a9b1; padding:12px 16px; margin:8px 0 20px 0;"> ;Focus questions {{ic|Use bullet points as shown in [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]}} # What are the primary push (avoidance) and pull (approach) factors that prompt parents to choose homeschooling over conventional education? # How do internal value alignments and pedagogical beliefs shape parents' long-term educational goals for their children? # In what ways do negative school environment experiences (e.g., bullying, unaddressed learning needs) act as acute psychological drivers for school withdrawal? # How do parental self-efficacy and perceived capability influence whether motivational intentions successfully translate into home education? # How do initial reactive motivations evolve over time into proactive, sustaining educational practices as families adapt? </div> == '''Understanding homeschooling and parental motivation''' == * Parental motivation to homeschool represents a dynamic, goal-directed psychological process that governs how families initiate and sustain home-based education (Green & Hoover-Dempsey, 2007). === '''Multiple motivations and values''' === * Parents rarely choose homeschooling for a single reason; decisions typically reflect a complex combination of academic, social, and emotional factors (Collom, 2005). * Home education allows parents to integrate their personal, moral, and cultural values directly into their children's daily learning environment (Morton, 2010). * Increased parent-child interaction acts as a primary motivator, fostering stronger attachment and active participation in developmental milestones (Guterman & Neuman, 2017). <div style="float:right; width:210px; margin:5px 0 12px 20px; border:1px solid #c8ccd1; padding:4px; background:#fff;">[[File:RAF Mildenhall Airman maintains resilience amid COVID 19 (6194977).jpg|center|200x200px|A young girl focuses on her laptop from a table, during remote lockdown learning.]]<div style="font-size:90%; line-height:1.3;"> '''Figure 1.''' A young girl focuses on her laptop from a table, during remote lockdown learning. </div></div> === '''External push factors and tailored education''' === * Acute negative experiences in conventional settings, such as peer victimization and persistent bullying, push parents to seek protective alternatives (Green & Hoover-Dempsey, 2007). * Parents are driven by the desire to provide specific pedagogical approaches that conventional schools may fail to deliver (Thomas, 2016). * Economic factors, such as balancing private school tuition costs against the financial trade-offs of single-income home education, influence decision feasibility (Collom, 2005). * Disruptions during pandemic lockdowns exposed widespread gaps in institutional remote instruction, driving many families to transition from temporary crisis schooling to permanent, intentional home education (Ray, 2021; see Figure 1). === '''Parental role construction and self-efficacy''' === * Decision-making begins when parents reconstruct their parental identity to include primary responsibility for formal academic instruction (Ice & Hoover-Dempsey, 2011). * Grounded in Bandura's (1997) self-efficacy theory, a parent's belief in their ability to teach strongly dictates whether motivational intentions turn into actual behavior. * As parents gain instructional experience, perceived self-efficacy increases, bolstering long-term commitment to home education (Green & Hoover-Dempsey, 2007). == '''Parents' values and educational goals''' == * Value-driven motivations represent approach-oriented goals where parents proactively seek to align education with their core philosophical ideals (Morton, 2010). === '''Educational beliefs and goals''' === * '''Pedagogical philosophy:''' Parents hold distinct beliefs about how children learn best, often favoring constructivist or child-led learning over rigid institutional curricula (Thomas, 2016). * Motivation is driven by fostering deep curiosity and lifelong learning rather than preparing for standardized testing (Ames, 1992). * Educational goals prioritize emotional resilience, character building, and social-emotional maturity alongside academic achievement (Guterman & Neuman, 2017). === '''Individualized education''' === * Homeschooling allows parents to adapt instructional speed to match their child's unique cognitive strengths and weaknesses (Thomas, 2016). * Parents retain freedom to select specialized learning materials that cater to specific talents, neurodivergent needs, or personal interests (Jackson, 2017). * Eliminating classroom distractions enables more efficient, targeted daily study sessions (Neuman & Aviram, 2003). <div style="float:right; width:150px; margin:20px auto; border:1px solid #c8ccd1; padding:4px; background:#fff;">[[File:Homework 03.jpg|center|Parent guiding children through individualized home learning activities]]<div style="font-size:90%; line-height:1.3;"> Parent guiding children through individualized home learning activities '''''Figure 2.'' Parental involvement in home education reflects both approach motives (desire for custom pedagogy) and high instructional self-efficacy.''' </div></div> === '''Perceived benefits''' === * Spending extended time together strengthens sibling relationships and parent-child relational bonds (Morton, 2010). * Families gain time sovereignty, allowing them to structure schedule routines around family needs rather than rigid school calendars. * Parents perceive home environments as safer spaces for children to build self-esteem free from peer pressure and social comparison (Guterman & Neuman, 2017). == '''Concerns about conventional schooling''' == * Avoidance-oriented motivations stem from perceived mismatches between institutional school environments and a child's developmental well-being (Green & Hoover-Dempsey, 2007). === '''School-related structural concerns''' === * '''Classroom overcrowding''' - High student-to-teacher ratios reduce individualized attention and slow down academic progression for both gifted and struggling students (Thomas, 2016). * '''Academic pressure''' - Oversaturation of high-stakes assessments is perceived by parents as damaging to intrinsic motivation and creative inquiry (Ames, 1992). * Inflexible school schedules and rigid administrative policies can create systemic friction for families seeking adaptability. === '''Child well-being and experiences''' === * Chronic bullying and playground exclusion serve as major emotional catalysts for removing children from school (Green & Hoover-Dempsey, 2007). * Parents report withdrawing children due to school-induced stress, school refusal behaviors, and burnout (Jackson, 2017). * Conventional settings often lack resources to support children with ADHD, Autism, or learning differences, leading parents to intervene (Jackson, 2017). === '''Perception versus objective circumstances''' === * Parental choices are guided by their subjective perception of school climate quality, regardless of objective national standards (Collom, 2005). * Declining trust in school administration leads parents to rely on their own evaluation of what is best for their child (Ice & Hoover-Dempsey, 2011). * Specific negative incidents often act as the tipping point that transforms ongoing background dissatisfaction into definitive action (Neuman & Aviram, 2003). == '''Autonomy, control, and family circumstances''' == * Translating motivational desires into sustainable home education requires a combination of personal agency, perceived capability, and structural feasibility (Bandura, 1997). === '''Parental autonomy and responsibility''' === * Parents seek full sovereignty over curriculum content, moral exposure, and daily instructional methods (Bartholet, 2020). * Motivation involves stepping into full accountability for the academic and developmental outcomes of the child (Ice & Hoover-Dempsey, 2011). * Self-Determination Theory suggests that exercising educational autonomy fulfills a core psychological need for parents (Deci & Ryan, 2000). === '''Self-efficacy and competence''' === * Parents must feel cognitively and pedagogically capable of facilitating grade-appropriate learning (Bandura, 1997). * Early worries about teaching ability are offset by accessing educational resources and supportive peer networks (Green & Hoover-Dempsey, 2007). * High self-efficacy enables parents to view teaching challenges as opportunities to learn alongside their children (Ice & Hoover-Dempsey, 2011). === '''Family circumstances and practicalities''' === * Household budgeting and single-income dynamics significantly shape whether motivational intentions can be realistically sustained (Collom, 2005). * Remote work options and adaptable work schedules enhance a family's logistical capacity to homeschool. * Access to local homeschooling co-ops and online communities provides essential emotional and practical scaffolding for parents (Medlin, 2013). == '''How parental motivations shape homeschooling decisions''' == * Parental motivation is an evolving psychological process that adapts as family circumstances, child development, and instructional experience mature (Guterman & Neuman, 2017). === '''Approach and avoidance motivational interactions''' === * Initial decisions are frequently triggered by avoidance (push) factors (See Table 1), while long-term maintenance relies on approach (pull) factors (Collom, 2005). * Parents who harbor both strong protective drives and positive educational goals demonstrate the highest commitment levels (Neuman & Aviram, 2003). * Positive pull factors help buffer against the daily logistical stressors associated with reactive push motivations. === '''Motivation, perceived ability, and change over time''' === * Over time, initial crisis-driven motivations (e.g., escaping bullying) transition into value-driven practices (e.g., customized interest-based learning) (Neuman & Aviram, 2003). * As children reach adolescence, parental motives shift toward university preparation, vocational skills, and encouraging autonomous study (Jackson, 2017). * Increased instructional competence reinforces ongoing motivation, creating a positive self-sustaining cycle (Bandura, 1997). === '''Overall psychological explanation''' === * Homeschooling decision-making is ultimately explained by the ongoing pursuit of basic psychological need fulfillment—autonomy, competence, and relatedness—for both parent and child (Deci & Ryan, 2000). * '''Protection vs. flourishing''' - Parental motivation balances protective instincts (avoiding psychological harm) with developmental flourishing (maximizing growth potential) (Guterman & Neuman, 2017). * Understanding homeschooling requires viewing parents not just as managers of schooling, but as active drivers of a integrated psychological ecosystem (Green & Hoover-Dempsey, 2007). == '''Summary of parental motivations for homeschooling''' == '''Table 1''' '''''Psychological Frameworks, Key Drivers, and Behavioral Manifestations of Parental Motivations for Homeschooling''''' {| class="wikitable" style="width:100%; border-collapse:collapse;" ! style="width:20%;" |Motivation Category ! style="width:20%;" |Psychological Framework ! style="width:20%;" |Primary Drivers / Triggers ! style="width:20%;" |Key Citations ! style="width:20%;" |Educational & Behavioral Impact |- |'''Avoidance / Push Motivations''' |Threat protection & stress reduction models |Bullying, school anxiety, unaddressed neurodivergent needs, standardized testing pressure |Collom (2005); Green & Hoover-Dempsey (2007); Jackson (2017) |Serves as the acute catalyst for removing a child from traditional schooling to restore emotional safety and well-being. |- |'''Approach / Pull Motivations''' |Self-Determination Theory (Intrinsic Motivation) |Custom pedagogical pacing, child-centered inquiry, religious/moral alignment, family bonding |Deci & Ryan (2000); Morton (2010); Thomas (2016) |Fosters high autonomous motivation, deep mastery goal orientation, and sustained long-term commitment to home education. |- |'''Self-Efficacy & Role Beliefs''' |Social Cognitive Theory (Bandura) |Active parental role construction, instructional confidence, adaptability, resource availability |Bandura (1997); Ice & Hoover-Dempsey (2011) |Dictates whether motivational desires successfully translate into real-world teaching behaviors and persistent instructional effort. |- |'''Sustaining / Evolving Motivations''' |Longitudinal motivational recalibration |Shift from crisis management to interest-based learning, tertiary prep, child autonomy |Guterman & Neuman (2017); Neuman & Aviram (2003) |Prevents parental burnout by transitioning reactive push factors into proactive pull factors as the family adapts over time. |} ''Note. Synthesized from empirical literature on parental educational choice and psychological need fulfillment.'' == '''Conclusion''' == * Parental motivation to homeschool is not a static decision, but a dynamic psychological process governed by the continuous interplay of push (avoidance) and pull (approach) factors (Collom, 2005; Green & Hoover-Dempsey, 2007). * Framed through Self-Determination Theory (Deci & Ryan, 2000), home education serves as a vehicle for parents to fulfill fundamental needs for autonomy, instructional competence, and familial relatedness. * Grounded in Bandura's (1997) social cognitive framework, high parental self-efficacy and active role construction are essential for translating motivational desires into effective, sustained educational practices (Ice & Hoover-Dempsey, 2011). * While acute environmental stressors (such as bullying, academic anxiety, or neurodivergent mismatches) often act as initial reactive catalysts, long-term commitment relies on proactive, value-driven motivators like tailored pedagogy and family cohesion (Guterman & Neuman, 2017; Neuman & Aviram, 2003). * Understanding the multifaceted drivers of parental choice provides crucial insights for developmental psychologists, educators, and policymakers seeking to better support family well-being and diverse learning pathways across childhood development (Jackson, 2017; Ray, 2017). == See also == {{expand}} == '''References''' == {{Hanging indent|1= * Abuzandah, S. (2017). Guterman, O., & Neuman, A. (2017b). schools and emotional and behavioral problems a comparison of school-going and homeschooled children. ''The Journal of Educational Research, 110'', 425-432. - references - scientific research publishing. Retrieved August 28, 2026, from Scirp.org website. * Ames, C. (1992). APA PsycNet. Retrieved August 27, 2026, from psycnet.apa.org website. * Bandura, A. (1997). ''Self-efficacy: The exercise of control.'' Retrieved August 28, 2026, from APA PsycNET website. * Bartholet, E. (2019, June 17). ''Homeschooling: Parent rights absolutism vs. child rights to Education & Protection.'' * Deci, E., & Ryan, R. (2000). APA PsycNet. Retrieved August 28, 2026, from psycnet.apa.org website. * Dobosz, D., Gierczyk, M., & Hornby, G. (2022). Parental perspectives of home-schooling of children with special educational needs and disabilities during the COVID-19 pandemic: A review. ''Journal of Research in Special Educational Needs.'' * Green, C. L., & Hoover-Dempsey, K. V. (2007). Why do parents homeschool? A systematic examination of parental involvement. ''Education and Urban Society, 39''(2), 264–285. * Grolnick, W. S., & Slowiaczek, M. L. (1994). Parents' involvement in children's schooling: A multidimensional conceptualization and motivational model. ''Child Development, 65''(1), 237–252. * Ice, C. L., & Hoover-Dempsey, K. V. (2010). Linking parental motivations for involvement and student proximal achievement outcomes in homeschooling and public schooling settings. ''Education and Urban Society, 43''(3), 339–369. * Isaac, E. P. (2005). The future of adult education in the urban African American church. ''Education and Urban Society, 37''(3), 276–291. * Morton, R. (2010). ''Home education: Constructions of choice.'' * Neuman, A., & Guterman, O. (2017). Homeschooling is not just about education: Focuses of meaning. ''Journal of School Choice, 11''(1), 148–167. * Ray, B. (2021). Should educators promote homeschooling? Worldwide growth and learner outcomes. ''Journal of Pedagogy, 12''(1), 55–76. * Ray, B. D. (2017). A systematic review of the empirical research on selected aspects of homeschooling as a school choice. ''Journal of School Choice, 11''(4), 604–621. * Thomas, A., & Pattison, H. (2012). Informal home education: Philosophical aspirations put into practice. ''Studies in Philosophy and Education, 32''(2), 141–154. }} ==External links== {{expand}} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Education]] [[Category:Motivation and emotion/Book/Parenting]] np5i5ilu0x1tyrkl15dot5fon1a61la 0 332225 2835217 2835077 2026-09-30T18:10:06Z 202 Xup iartkab lakarg 3111500 /* 1. Zodiac Signs */ 2835217 wikitext text/x-wiki {{Infobox | title = The Lost Zodiac | image = | caption = | label1 = Author | data1 = Tahmid Arian Borno | label2 = Year | data2 = 2026 | label3 = Status | data3 = Proposed hypothesis; under development | label4 = Subject | data4 = Astrology / stellar symbolism }} == The Lost Zodiac == '''The Lost Zodiac''' is a proposed hypothesis developed by [[Tahmid Arian Borno]] in 2026. It is an experimental astrological framework based on selected stars and constellational figures, their associated date ranges, and a proposed method for converting conventional natal-chart positions into Lost Zodiac positions. <div style="clear: both; width: auto; margin: 1em 0;"> <!-- Research Project Box --> <div style="border-left: 10px solid #0066cc; background-color: #f0f8ff; padding: 0.5em 1em; margin-bottom: 0.5em; box-sizing: border-box; width: 100%;"> '''This is a research project at Wikiversity.''' </div> <!-- Hypothesis Warning Box --> <div style="border-left: 10px solid #f28500; background-color: #fef6e7; padding: 0.5em 1em; box-sizing: border-box; width: 100%;"> '''This article describes a personal hypothesis that is currently under development. It is not presented as an established astronomical or astrological system. The astronomical information underlying individual stars and constellations is supported by external sources; the organization of the periods and the natal-chart conversion methodology are proposed by the author.''' </div> </div> == Background == The Lost Zodiac is based on a set of zodiacal periods associated with prominent stars and constellational figures. The source system on which the reconstruction is based contains 31 periods representing 22 distinct constellational figures. Several figures recur in non-adjacent periods because different stars associated with the same figure are assigned to different parts of the year. The Lost Zodiac system used as the basis for this project was created by astrologer Catherine Tennant and features 22 "lost" star signs based on major constellations located north and south of the main zodiac belt.<ref name="Interactive Stars">{{cite web |url=https://www.interactivestars.com/beyond_zodiac/lost_zodiac_sign.php |title=The Lost Zodiac |publisher=InteractiveStars.com |access-date=2026-09-23 }}</ref> The period boundaries, associated figures, and principal stars used in this project are derived directly from that source; the organization of the periods within this article and the natal-chart conversion methodology described below remain original to the author. The present project does not claim that the organization of these periods or their relationship to the modern natal zodiac has been historically established. Instead, the source material is used as the astronomical and symbolic foundation for a proposed reconstruction. == The Lost Zodiac Signs == {| class="wikitable sortable" ! Sign ! Period ! Associated star(s) ! Sources |- | The Lyre of Orpheus | December 29 – January 13 | Vega | <ref name="The Lyre of Orpheus">{{cite web |url=https://www.interactivestars.com/beyond_zodiac/lost_zodiac.php?sign=orpheus&date=Dec-29th@Jan-13th |title=The Lyre of Orpheus |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Eagle | January 14 – January 28 | Altair | <ref name="The Eagle">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Eagle.pdf |title=The Eagle |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Dolphin | January 29 – February 8 | Rotanev and Sualocin | <ref name="The Dolphin">{{cite web |url=https://www.interactivestars.com/beyond_zodiac/lost_zodiac.php?sign=dolphin&date=Jan-29th@Feb-8th |title=The Dolphin |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Swan | February 9 – February 28/29 | Sadir | <ref name="The Swan">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Swan.pdf |title=The Swan |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The River of Night | March 1 – March 12 | Achernar | <ref name="The River of Night">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_River_of_Night.pdf |title=The River of Night |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | Pegasus | March 13 – April 1 | Markab, Scheat and Algenib | <ref name="Pegasus">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/Pegasus.pdf |title=Pegasus |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | Andromeda | April 2 – April 9 | Alpheratz | <ref name="Andromeda">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/Andromeda.pdf |title=Andromeda |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The River of Night | April 10 – April 18 | Acamar | <ref name="The River of Night"/> |- | Andromeda | April 19 – May 8 | Mirach and Alamach | <ref name="Andromeda"/> |- | The River of Night | May 9 – May 15 | Rana and Zanrak | <ref name="The River of Night"/> |- | Perseus | May 16 – May 31 | Algol and Mirfak | <ref name="Perseus">{{cite web |url=https://www.interactivestars.com/beyond_zodiac/lost_zodiac.php?sign=perseus&date=May16th@31st |title=Perseus |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | Orion | June 1 – June 7 | Rigel | <ref name="Orion">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/Orion.pdf |title=Orion |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Charioteer | June 8 – June 16 | Capella | <ref name="The Charioteer">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Charioteer.pdf |title=The Charioteer |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | Orion | June 17 – June 27 | Betelgeuse | <ref name="Orion"/> |- | The Dogs | June 28 – July 7 | Sirius | <ref name="The Dogs">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Dogs.pdf |title=The Dogs |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Ship of the Argonauts | July 8 – July 17 | Canopus | <ref name="Ship of the Argonauts">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Ship_of_the_Argonauts.pdf |title=The Ship of the Argonauts |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Dogs | July 18 – July 25 | Procyon | <ref name="The Dogs"/> |- | The Dragon | July 26 – August 7 | Gianfar | <ref name="The Dragon">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Dragon.pdf |title=The Dragon |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Great Bear | August 8 – August 15 | Dubhe and Merak | <ref name="The Great Bear">{{cite web |url=https://www.interactivestars.com/beyond_zodiac/lost_zodiac.php?sign=great_bear&date=Aug-8th@15th |title=The Great Bear |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Sea Serpent | August 16 – August 23 | Alphard | <ref name="The Sea Serpent">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Sea_Serpent.pdf |title=The Sea Serpent |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Great Bear | August 24 – September 10 | Phekda, Megrez, Alioth and Mizar | <ref name="The Great Bear"/> |- | The Cup | September 11 – September 21 | Alkes | <ref name="The Cup">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Cup.pdf |title=The Cup |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Ship of the Argonauts | September 22 – September 28 | Markeb | <ref name="Ship of the Argonauts"/> |- | The Raven | September 29 – October 11 | Minkar and Algorab | <ref name="The Raven">{{cite web |url=https://jumpshare.com/share/plV6yw6ulAAMDx81uL72 |title=The Raven |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Bear Keeper | October 12 – October 26 | Arcturus and Izar | <ref name="The Bear Keeper">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/Bear_Keeper.pdf |title=The Bear Keeper |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Crown of the North Wind | October 27 – November 10 | Alphecca | <ref>{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Crown_of_the_North_Wind.pdf |title=The Lost Zodiac |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Serpent | November 11 – November 19 | Unuk Elhaia | <ref>{{cite web |url=https://jumpshare.com/share/ht2Iim8ke1VrgYzEPIFQ |title=The Serpent |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Wise Centaur | November 20 – December 5 | Toliman (Alpha Centauri) | <ref>{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Wise_Centaur.pdf |title=The Wise Centaur |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | Ophiuchus | December 6 – December 16 | Han, Sabik and Ras Alhague | <ref>{{cite web |url=https://www.interactivestars.com/zodiac_pdf/Ophiuchus.pdf |title=Ophiuchus |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Dragon | December 17 – December 23 | Grumium and Etanin | <ref>{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Dragon.pdf |title=The Dragon |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Serpent | December 24 – December 28 | Alya | <ref>{{cite web |url=https://jumpshare.com/share/ht2Iim8ke1VrgYzEPIFQ |title=The Serpent |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |} == Natal chart conversion methodology == The Lost Zodiac proposes a proportional conversion between a conventional zodiacal position and the corresponding Lost Zodiac period. A placement is first treated as a position within its conventional zodiac sign. That position is converted into a corresponding calendar date and time. The resulting date and time are then located within the relevant Lost Zodiac period. Each listed period includes the full span of every calendar date in its range. The starting date begins at 12:00 a.m., and the ending date concludes at 11:59 p.m. For example, a period ending on February 28 includes the entire day of February 28. In leap years, the Swan period ends at 11:59 p.m. on February 29. For a Lost Zodiac period, the beginning of the period is treated as 0°00′ and the end of the period as 29°59′. The beginning boundary is midnight at the start of the first listed date, while the ending boundary is 11:59 p.m. on the last listed date. The proposed formula is: <math> L = \frac{t-t_0}{t_1-t_0}\times29^\circ 59' </math> where: * <math>L</math> = resulting Lost Zodiac degree * <math>t</math> = the corresponding date and time of the natal placement * <math>t_0</math> = beginning of the Lost Zodiac period * <math>t_1</math> = end boundary of the Lost Zodiac period === Example === A tropical Sun position of Pisces 1°29′ corresponds to February 20, 2009 at approximately 6:25 AM in the example used by the author. The Swan period runs from February 9 through the last day of February, ending on February 28 in a common year or February 29 in a leap year. The position of February 20 at 6:25 AM is approximately 56.34% through the Swan period. Therefore: <math> 29^\circ 59'\times0.5634\approx16^\circ 53' </math> The resulting proposed Lost Zodiac position is therefore: '''Swan 16°53′''' == Reference natal chart == The following conventional natal-chart placements are used as the reference positions for the Lost Zodiac conversion. {| class="wikitable" ! Natal point ! Conventional natal position ! House |- | Sun | Pisces 1°29′ | 1st House |- | Ascendant | Aquarius 29°24′ | — |- | Moon | Capricorn 5°24′ | 11th House |- | Mercury | Aquarius 6°07′ | 12th House |- | Venus | Aries 11°30′ | 2nd House |- | Mars | Aquarius 11°55′ | 12th House |- | Jupiter | Aquarius 10°38′ | 12th House |- | Saturn | Virgo 19°41′ Rx | 7th House |- | Uranus | Pisces 21°25′ | 1st House |- | Neptune | Aquarius 24°13′ | 12th House |- | Pluto | Capricorn 2°47′ | 10th House |- | North Node | Aquarius 8°18′ Rx | 12th House |- | Lilith | Capricorn 5°16′ | 11th House |- | Chiron | Aquarius 21°52′ | 12th House |- | Fortune | Aries 25°29′ | 2nd House |- | Vertex | Virgo 17°15′ | 7th House |- | MC | Sagittarius 8°28′ | — |} == Example: Author's Lost Zodiac natal chart == Using the conversion methodology described above, the author's proposed Lost Zodiac natal placements are: {| class="wikitable" ! Natal point ! Lost Zodiac placement |- | Sun | Swan 16°53′ |- | Ascendant | Swan 14°06′ |- | Moon | Serpent 20°23′ |- | Mercury | Eagle 24°13′ |- | Venus | Pegasus 29°14′ |- | Mars | Dolphin 7°57′ |- | Jupiter | Dolphin 4°27′ |- | Saturn | Cup 1°52′ |- | Uranus | River of Night 28°32′ |- | Neptune | Swan 6°19′ |- | Pluto | Serpent 4°42′ |- | North Node | Eagle 28°35′ |- | Lilith | Serpent 19°35′ |- | Chiron | Swan 2°48′ |- | Fortune | River of Night 18°16′ |- | Vertex | Great Bear 27°04′ |- | MC | Wise Centaur 19°37′ |} == In case you don't know basic astrology == To interpret any astrological framework, including the Lost Zodiac, it is necessary to understand the four foundational components of a natal chart. These components work together to describe ''what'' is happening (Planets), ''how'' it is happening (Signs), ''where'' it is happening (Houses), and the ''dynamic relationships'' between these factors (Aspects). === 1. Zodiac Signs === Signs represent the ''style'' or ''manner'' in which planetary energy is expressed. They describe the overarching psychological themes, energetic qualities, and core motivations associated with different segments of the ecliptic. {| class="wikitable sortable" ! Sign ! Overall Concept ! Main Energy ! Need / Goal |- | Aries | Independence, Autonomy | Follows Own Impulses | Self-Expression |- | Taurus | Self-Value, Secure Self-Concept | Steady, Harmonious Doing | Peaceful Environment |- | Gemini | Perception, Thinking, Communicating | Electrical, Speedy | To Connect |- | Cancer | Sensitivity to Other People's Energies | Subtle awareness of Surroundings | Protection, Nurturing Environment |- | Leo | Self-Identity, Ego, Self-Development | Engaging | Recognition, Affirmation, Applause |- | Virgo | To be of Great Service | Analytical | To Deeply Understand |- | Libra | Knowing Self through Relating with Others | Back and Forth Energy Exchanges | Harmonious Interactions |- | Scorpio | Self-Mastery through Self-Knowledge | Investigative | Privacy to Do Inner Work |- | Sagittarius | Self-Expansion | Growing, Changing, Assimilating | New Experiences |- | Capricorn | Knowing Self from the Inside Out | Listens to Inner Guidance & Wisdom | Work Hard, Be Captain, Boss |- | Aquarius | Individuation, "I've Got To Be Me" | Separates Self Out From Others | Freedom of Thought |- | Pisces | Not of This World, Mystic, Empath | Creative, Spiritual | New Vision of Self |} === 2. Houses === Houses represent the ''areas of life'' or specific environments where planetary energies manifest. The chart is divided into 12 houses, each governing a distinct domain of human experience, from personal identity to public status. {| class="wikitable sortable" ! House ! Overall Concept ! Main Energy ! Need |- | 1st House | How One Presents and is Seen by Others, Body, Early Childhood Experiences | Energetic, Enthusiasm, Action-oriented | To Assert Oneself, To be Seen, To be Heard |- | 2nd House | Self-Concept, Self-Value, Material Security | Building, works steadily with a sense of rhythm and harmony | Sense of Self-Value, Comfort, Stability, Needs met |- | 3rd House | Perception, Thinking, Communicating, Connecting | Electrical, Mentally-Oriented | To connect |- | 4th House | Family Conditioning, Modeling Parents' Reactions, Emotional Needs | Sensitive Awareness of How Others Relate to Us | Love, Nurturing |- | 5th House | Ego-Development, Self-identity, Play, Fun, Art, Children | Joyful Creativity, Role-Playing | To Play, Have Fun, Try New Things |- | 6th House | Service, Science, Medicine, Pets, Mentors | Desire to Help, Be of Service | To Perfect a Skill, Serve Others |- | 7th House | All one-on-one close relationships | Energy Exchanges with Others | A Harmonious Environment |- | 8th House | Self-Transformation, Self-Mastery through Self-Knowledge, Renewal | Inner Work - digging up the unconscious emotions | Courage to do it, Desire to Change |- | 9th House | Self-Expansion, Seeks Meaning in Life | Assimilation of New Experiences | Meaningful New Experiences |- | 10th House | Outer-Most Social Self, Position, Status | Being of Service through Having Mastered Skill | Confidence in Inner Wisdom, Sense of Integrity |- | 11th House | One's Tribe, Audience, Allies, People w/ Commonality | Wants to Improve Society, Impact It | To be inventive, Have new ideas |- | 12th House | To let go of what is no longer needed; grieve losses, embrace gifts | Release negatives of sign; embrace positives of sign | To connect with Soul-Spirit, one's creativity, Reinvent Self |} === 3. Planets === Planets represent the ''driving forces'' or archetypal functions within the psyche. Each planet governs a specific type of energy or psychological need that seeks expression through the sign and house it occupies. {| class="wikitable sortable" ! Planet ! Overall Concept ! Main Energy ! Need / Goal |- | Sun | Self-Identity, Ego Development | Creative Play, Fun, Expressing | Recognition, Applause |- | Moon | Consciousness, Awareness, Emotional Body | Sensitivity, Awareness of Other People's Energies | Emotional Wellbeing, What makes us Happy |- | Mercury | Perception, Thinking, Communicating | Electrical, Speedy | Connection |- | Venus | Balance, Beauty, Values, Emotional Processes/Attitudes | Attractive, Magnetic | Love, Harmony, Meaning |- | Mars | Actions, Doing, Going for it | Expressive, Assertive, Defending | Good Use of Outgoing Energy, Good Boundaries |- | Jupiter | Expansiveness, Growth | Reaching out, Learning, Growing, Expanding, Assimilating | Assimilation of New Ideas, Qualities, Beliefs |- | Saturn | Steady Focus, Work, Career, Social Position / Authority | Holding, Maintaining | Maintaining Structures, to remain focused |- | Uranus | Individuation, Change, Growth, Authenticity | Dividing, Separating, Distinguishing Self from Other, Breaks Up Old Patterns | Strong Inner Focus on Authentic Self, Independent Thinking |- | Neptune | Spiritual Connection, Creativity, Dissolution | Attention to Higher Self or Soul, Erodes, Dissolves the Negative | To help you let go of what inhibits Soul life |- | Pluto | The Soul's Intention, Profound Evolution | Powerful Demand for Change, Doesn't take NO for an answer | Needs you to listen, take yourself seriously |- | Chiron | Core Wounds, Healing | Nagging, Persistence | Demands Attention for Healing |} === 4. Aspects === Aspects are the specific angular distances (measured in degrees) between planets in a chart. They describe the ''dynamic relationship'' between planetary energies, indicating whether they work together harmoniously, create tension that demands action, or require conscious integration. {| class="wikitable sortable" ! Degree ! Aspect ! Key Words |- | 0° | Conjunction | Blending Energies; Power in Union; New Beginning; Creative Impulse; Innate Potential |- | 30° | Semi-Sextile | Nagging Itch; Awakening Urge or Desire; Stimulated Imagination; Initiating Action |- | 45° | Semi-Square | Something's Not Right Feeling; Resistance; Misalignment; Friction; Reality Check |- | 60° | Sextile | Stimulation / Support to Grow, Learn, Plan, Organize, Explore, Progress & Reach Out |- | 90° | Square | Something's Got to Give; Crisis; Stress; Tension; Time for Courage, Honesty, & Decisiveness |- | 120° | Trine | Support; Easy Flow of Energy; Need Conscious Attention and Intention to Make Use of It |- | 135° | Sesqui-Square | Adjusting Personal Goals/Desires to Outer Conditions, Obstacles, or Other People's Needs |- | 150° | Quincunx | Nagging Voice of Dissatisfaction; Desire for Improvement; Attention to Details; Discernment |- | 180° | Opposition | Two Sides of One Coin; Stimulates Awareness to Balance, Integrate, & Become Whole |} '''Note on Application:''' When analyzing a Lost Zodiac chart, these four components are synthesized. The converted Lost Zodiac sign provides the thematic style, the house indicates the life area of expression, the planet identifies the driving psychological force, and the aspects reveal how these forces interact with the rest of the chart. 8pc16odgzs89wx44if1wi8muf9p4fid 2835218 2835217 2026-09-30T18:12:28Z 202 Xup iartkab lakarg 3111500 /* 2. Houses */ 2835218 wikitext text/x-wiki {{Infobox | title = The Lost Zodiac | image = | caption = | label1 = Author | data1 = Tahmid Arian Borno | label2 = Year | data2 = 2026 | label3 = Status | data3 = Proposed hypothesis; under development | label4 = Subject | data4 = Astrology / stellar symbolism }} == The Lost Zodiac == '''The Lost Zodiac''' is a proposed hypothesis developed by [[Tahmid Arian Borno]] in 2026. It is an experimental astrological framework based on selected stars and constellational figures, their associated date ranges, and a proposed method for converting conventional natal-chart positions into Lost Zodiac positions. <div style="clear: both; width: auto; margin: 1em 0;"> <!-- Research Project Box --> <div style="border-left: 10px solid #0066cc; background-color: #f0f8ff; padding: 0.5em 1em; margin-bottom: 0.5em; box-sizing: border-box; width: 100%;"> '''This is a research project at Wikiversity.''' </div> <!-- Hypothesis Warning Box --> <div style="border-left: 10px solid #f28500; background-color: #fef6e7; padding: 0.5em 1em; box-sizing: border-box; width: 100%;"> '''This article describes a personal hypothesis that is currently under development. It is not presented as an established astronomical or astrological system. The astronomical information underlying individual stars and constellations is supported by external sources; the organization of the periods and the natal-chart conversion methodology are proposed by the author.''' </div> </div> == Background == The Lost Zodiac is based on a set of zodiacal periods associated with prominent stars and constellational figures. The source system on which the reconstruction is based contains 31 periods representing 22 distinct constellational figures. Several figures recur in non-adjacent periods because different stars associated with the same figure are assigned to different parts of the year. The Lost Zodiac system used as the basis for this project was created by astrologer Catherine Tennant and features 22 "lost" star signs based on major constellations located north and south of the main zodiac belt.<ref name="Interactive Stars">{{cite web |url=https://www.interactivestars.com/beyond_zodiac/lost_zodiac_sign.php |title=The Lost Zodiac |publisher=InteractiveStars.com |access-date=2026-09-23 }}</ref> The period boundaries, associated figures, and principal stars used in this project are derived directly from that source; the organization of the periods within this article and the natal-chart conversion methodology described below remain original to the author. The present project does not claim that the organization of these periods or their relationship to the modern natal zodiac has been historically established. Instead, the source material is used as the astronomical and symbolic foundation for a proposed reconstruction. == The Lost Zodiac Signs == {| class="wikitable sortable" ! Sign ! Period ! Associated star(s) ! Sources |- | The Lyre of Orpheus | December 29 – January 13 | Vega | <ref name="The Lyre of Orpheus">{{cite web |url=https://www.interactivestars.com/beyond_zodiac/lost_zodiac.php?sign=orpheus&date=Dec-29th@Jan-13th |title=The Lyre of Orpheus |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Eagle | January 14 – January 28 | Altair | <ref name="The Eagle">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Eagle.pdf |title=The Eagle |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Dolphin | January 29 – February 8 | Rotanev and Sualocin | <ref name="The Dolphin">{{cite web |url=https://www.interactivestars.com/beyond_zodiac/lost_zodiac.php?sign=dolphin&date=Jan-29th@Feb-8th |title=The Dolphin |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Swan | February 9 – February 28/29 | Sadir | <ref name="The Swan">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Swan.pdf |title=The Swan |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The River of Night | March 1 – March 12 | Achernar | <ref name="The River of Night">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_River_of_Night.pdf |title=The River of Night |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | Pegasus | March 13 – April 1 | Markab, Scheat and Algenib | <ref name="Pegasus">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/Pegasus.pdf |title=Pegasus |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | Andromeda | April 2 – April 9 | Alpheratz | <ref name="Andromeda">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/Andromeda.pdf |title=Andromeda |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The River of Night | April 10 – April 18 | Acamar | <ref name="The River of Night"/> |- | Andromeda | April 19 – May 8 | Mirach and Alamach | <ref name="Andromeda"/> |- | The River of Night | May 9 – May 15 | Rana and Zanrak | <ref name="The River of Night"/> |- | Perseus | May 16 – May 31 | Algol and Mirfak | <ref name="Perseus">{{cite web |url=https://www.interactivestars.com/beyond_zodiac/lost_zodiac.php?sign=perseus&date=May16th@31st |title=Perseus |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | Orion | June 1 – June 7 | Rigel | <ref name="Orion">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/Orion.pdf |title=Orion |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Charioteer | June 8 – June 16 | Capella | <ref name="The Charioteer">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Charioteer.pdf |title=The Charioteer |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | Orion | June 17 – June 27 | Betelgeuse | <ref name="Orion"/> |- | The Dogs | June 28 – July 7 | Sirius | <ref name="The Dogs">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Dogs.pdf |title=The Dogs |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Ship of the Argonauts | July 8 – July 17 | Canopus | <ref name="Ship of the Argonauts">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Ship_of_the_Argonauts.pdf |title=The Ship of the Argonauts |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Dogs | July 18 – July 25 | Procyon | <ref name="The Dogs"/> |- | The Dragon | July 26 – August 7 | Gianfar | <ref name="The Dragon">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Dragon.pdf |title=The Dragon |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Great Bear | August 8 – August 15 | Dubhe and Merak | <ref name="The Great Bear">{{cite web |url=https://www.interactivestars.com/beyond_zodiac/lost_zodiac.php?sign=great_bear&date=Aug-8th@15th |title=The Great Bear |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Sea Serpent | August 16 – August 23 | Alphard | <ref name="The Sea Serpent">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Sea_Serpent.pdf |title=The Sea Serpent |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Great Bear | August 24 – September 10 | Phekda, Megrez, Alioth and Mizar | <ref name="The Great Bear"/> |- | The Cup | September 11 – September 21 | Alkes | <ref name="The Cup">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Cup.pdf |title=The Cup |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Ship of the Argonauts | September 22 – September 28 | Markeb | <ref name="Ship of the Argonauts"/> |- | The Raven | September 29 – October 11 | Minkar and Algorab | <ref name="The Raven">{{cite web |url=https://jumpshare.com/share/plV6yw6ulAAMDx81uL72 |title=The Raven |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Bear Keeper | October 12 – October 26 | Arcturus and Izar | <ref name="The Bear Keeper">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/Bear_Keeper.pdf |title=The Bear Keeper |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Crown of the North Wind | October 27 – November 10 | Alphecca | <ref>{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Crown_of_the_North_Wind.pdf |title=The Lost Zodiac |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Serpent | November 11 – November 19 | Unuk Elhaia | <ref>{{cite web |url=https://jumpshare.com/share/ht2Iim8ke1VrgYzEPIFQ |title=The Serpent |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Wise Centaur | November 20 – December 5 | Toliman (Alpha Centauri) | <ref>{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Wise_Centaur.pdf |title=The Wise Centaur |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | Ophiuchus | December 6 – December 16 | Han, Sabik and Ras Alhague | <ref>{{cite web |url=https://www.interactivestars.com/zodiac_pdf/Ophiuchus.pdf |title=Ophiuchus |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Dragon | December 17 – December 23 | Grumium and Etanin | <ref>{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Dragon.pdf |title=The Dragon |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Serpent | December 24 – December 28 | Alya | <ref>{{cite web |url=https://jumpshare.com/share/ht2Iim8ke1VrgYzEPIFQ |title=The Serpent |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |} == Natal chart conversion methodology == The Lost Zodiac proposes a proportional conversion between a conventional zodiacal position and the corresponding Lost Zodiac period. A placement is first treated as a position within its conventional zodiac sign. That position is converted into a corresponding calendar date and time. The resulting date and time are then located within the relevant Lost Zodiac period. Each listed period includes the full span of every calendar date in its range. The starting date begins at 12:00 a.m., and the ending date concludes at 11:59 p.m. For example, a period ending on February 28 includes the entire day of February 28. In leap years, the Swan period ends at 11:59 p.m. on February 29. For a Lost Zodiac period, the beginning of the period is treated as 0°00′ and the end of the period as 29°59′. The beginning boundary is midnight at the start of the first listed date, while the ending boundary is 11:59 p.m. on the last listed date. The proposed formula is: <math> L = \frac{t-t_0}{t_1-t_0}\times29^\circ 59' </math> where: * <math>L</math> = resulting Lost Zodiac degree * <math>t</math> = the corresponding date and time of the natal placement * <math>t_0</math> = beginning of the Lost Zodiac period * <math>t_1</math> = end boundary of the Lost Zodiac period === Example === A tropical Sun position of Pisces 1°29′ corresponds to February 20, 2009 at approximately 6:25 AM in the example used by the author. The Swan period runs from February 9 through the last day of February, ending on February 28 in a common year or February 29 in a leap year. The position of February 20 at 6:25 AM is approximately 56.34% through the Swan period. Therefore: <math> 29^\circ 59'\times0.5634\approx16^\circ 53' </math> The resulting proposed Lost Zodiac position is therefore: '''Swan 16°53′''' == Reference natal chart == The following conventional natal-chart placements are used as the reference positions for the Lost Zodiac conversion. {| class="wikitable" ! Natal point ! Conventional natal position ! House |- | Sun | Pisces 1°29′ | 1st House |- | Ascendant | Aquarius 29°24′ | — |- | Moon | Capricorn 5°24′ | 11th House |- | Mercury | Aquarius 6°07′ | 12th House |- | Venus | Aries 11°30′ | 2nd House |- | Mars | Aquarius 11°55′ | 12th House |- | Jupiter | Aquarius 10°38′ | 12th House |- | Saturn | Virgo 19°41′ Rx | 7th House |- | Uranus | Pisces 21°25′ | 1st House |- | Neptune | Aquarius 24°13′ | 12th House |- | Pluto | Capricorn 2°47′ | 10th House |- | North Node | Aquarius 8°18′ Rx | 12th House |- | Lilith | Capricorn 5°16′ | 11th House |- | Chiron | Aquarius 21°52′ | 12th House |- | Fortune | Aries 25°29′ | 2nd House |- | Vertex | Virgo 17°15′ | 7th House |- | MC | Sagittarius 8°28′ | — |} == Example: Author's Lost Zodiac natal chart == Using the conversion methodology described above, the author's proposed Lost Zodiac natal placements are: {| class="wikitable" ! Natal point ! Lost Zodiac placement |- | Sun | Swan 16°53′ |- | Ascendant | Swan 14°06′ |- | Moon | Serpent 20°23′ |- | Mercury | Eagle 24°13′ |- | Venus | Pegasus 29°14′ |- | Mars | Dolphin 7°57′ |- | Jupiter | Dolphin 4°27′ |- | Saturn | Cup 1°52′ |- | Uranus | River of Night 28°32′ |- | Neptune | Swan 6°19′ |- | Pluto | Serpent 4°42′ |- | North Node | Eagle 28°35′ |- | Lilith | Serpent 19°35′ |- | Chiron | Swan 2°48′ |- | Fortune | River of Night 18°16′ |- | Vertex | Great Bear 27°04′ |- | MC | Wise Centaur 19°37′ |} == In case you don't know basic astrology == To interpret any astrological framework, including the Lost Zodiac, it is necessary to understand the four foundational components of a natal chart. These components work together to describe ''what'' is happening (Planets), ''how'' it is happening (Signs), ''where'' it is happening (Houses), and the ''dynamic relationships'' between these factors (Aspects). === 1. Zodiac Signs === Signs represent the ''style'' or ''manner'' in which planetary energy is expressed. They describe the overarching psychological themes, energetic qualities, and core motivations associated with different segments of the ecliptic. {| class="wikitable sortable" ! Sign ! Overall Concept ! Main Energy ! Need / Goal |- | Aries | Independence, Autonomy | Follows Own Impulses | Self-Expression |- | Taurus | Self-Value, Secure Self-Concept | Steady, Harmonious Doing | Peaceful Environment |- | Gemini | Perception, Thinking, Communicating | Electrical, Speedy | To Connect |- | Cancer | Sensitivity to Other People's Energies | Subtle awareness of Surroundings | Protection, Nurturing Environment |- | Leo | Self-Identity, Ego, Self-Development | Engaging | Recognition, Affirmation, Applause |- | Virgo | To be of Great Service | Analytical | To Deeply Understand |- | Libra | Knowing Self through Relating with Others | Back and Forth Energy Exchanges | Harmonious Interactions |- | Scorpio | Self-Mastery through Self-Knowledge | Investigative | Privacy to Do Inner Work |- | Sagittarius | Self-Expansion | Growing, Changing, Assimilating | New Experiences |- | Capricorn | Knowing Self from the Inside Out | Listens to Inner Guidance & Wisdom | Work Hard, Be Captain, Boss |- | Aquarius | Individuation, "I've Got To Be Me" | Separates Self Out From Others | Freedom of Thought |- | Pisces | Not of This World, Mystic, Empath | Creative, Spiritual | New Vision of Self |} === 2. Houses === Houses represent the ''areas of life'' or specific environments where planetary energies manifest. The chart is divided into 12 houses, each governing a distinct domain of human experience, from personal identity to public status. {| class="wikitable sortable" ! House ! Overall Concept ! Main Energy ! Need |- | 1st House | How One Presents and is Seen by Others, Body, Early Childhood Experiences | Energetic, Enthusiasm, Action-oriented | To Assert Oneself, To be Seen, To be Heard |- | 2nd House | Self-Concept, Self-Value, Material Security | Building, works steadily with a sense of rhythm and harmony | Sense of Self-Value, Comfort, Stability, Needs met |- | 3rd House | Perception, Thinking, Communicating, Connecting | Electrical, Mentally-Oriented | To connect |- | 4th House | Family Conditioning, Modeling Parents' Reactions, Emotional Needs | Sensitive Awareness of How Others Relate to Us | Love, Nurturing |- | 5th House | Ego-Development, Self-identity, Play, Fun, Art, Children | Joyful Creativity, Role-Playing | To Play, Have Fun, Try New Things |- | 6th House | Service, Science, Medicine, Pets, Mentors | Desire to Help, Be of Service | To Perfect a Skill, Serve Others |- | 7th House | All one-on-one close relationships | Energy Exchanges with Others | A Harmonious Environment |- | 8th House | Self-Transformation, Self-Mastery through Self-Knowledge, Renewal | Inner Work - digging up the unconscious emotions | Courage to do it, Desire to Change |- | 9th House | Self-Expansion, Seeks Meaning in Life | Assimilation of New Experiences | Meaningful New Experiences |- | 10th House | Outer-Most Social Self, Position, Status | Being of Service through Having Mastered Skill | Confidence in Inner Wisdom, Sense of Integrity |- | 11th House | One's Tribe, Audience, Allies, People with Commonality | Wants to Improve Society, Impact It | To be inventive, Have new ideas |- | 12th House | To let go of what is no longer needed; grieve losses, embrace gifts | Release negatives of sign; embrace positives of sign | To connect with Soul-Spirit, one's creativity, Reinvent Self |} === 3. Planets === Planets represent the ''driving forces'' or archetypal functions within the psyche. Each planet governs a specific type of energy or psychological need that seeks expression through the sign and house it occupies. {| class="wikitable sortable" ! Planet ! Overall Concept ! Main Energy ! Need / Goal |- | Sun | Self-Identity, Ego Development | Creative Play, Fun, Expressing | Recognition, Applause |- | Moon | Consciousness, Awareness, Emotional Body | Sensitivity, Awareness of Other People's Energies | Emotional Wellbeing, What makes us Happy |- | Mercury | Perception, Thinking, Communicating | Electrical, Speedy | Connection |- | Venus | Balance, Beauty, Values, Emotional Processes/Attitudes | Attractive, Magnetic | Love, Harmony, Meaning |- | Mars | Actions, Doing, Going for it | Expressive, Assertive, Defending | Good Use of Outgoing Energy, Good Boundaries |- | Jupiter | Expansiveness, Growth | Reaching out, Learning, Growing, Expanding, Assimilating | Assimilation of New Ideas, Qualities, Beliefs |- | Saturn | Steady Focus, Work, Career, Social Position / Authority | Holding, Maintaining | Maintaining Structures, to remain focused |- | Uranus | Individuation, Change, Growth, Authenticity | Dividing, Separating, Distinguishing Self from Other, Breaks Up Old Patterns | Strong Inner Focus on Authentic Self, Independent Thinking |- | Neptune | Spiritual Connection, Creativity, Dissolution | Attention to Higher Self or Soul, Erodes, Dissolves the Negative | To help you let go of what inhibits Soul life |- | Pluto | The Soul's Intention, Profound Evolution | Powerful Demand for Change, Doesn't take NO for an answer | Needs you to listen, take yourself seriously |- | Chiron | Core Wounds, Healing | Nagging, Persistence | Demands Attention for Healing |} === 4. Aspects === Aspects are the specific angular distances (measured in degrees) between planets in a chart. They describe the ''dynamic relationship'' between planetary energies, indicating whether they work together harmoniously, create tension that demands action, or require conscious integration. {| class="wikitable sortable" ! Degree ! Aspect ! Key Words |- | 0° | Conjunction | Blending Energies; Power in Union; New Beginning; Creative Impulse; Innate Potential |- | 30° | Semi-Sextile | Nagging Itch; Awakening Urge or Desire; Stimulated Imagination; Initiating Action |- | 45° | Semi-Square | Something's Not Right Feeling; Resistance; Misalignment; Friction; Reality Check |- | 60° | Sextile | Stimulation / Support to Grow, Learn, Plan, Organize, Explore, Progress & Reach Out |- | 90° | Square | Something's Got to Give; Crisis; Stress; Tension; Time for Courage, Honesty, & Decisiveness |- | 120° | Trine | Support; Easy Flow of Energy; Need Conscious Attention and Intention to Make Use of It |- | 135° | Sesqui-Square | Adjusting Personal Goals/Desires to Outer Conditions, Obstacles, or Other People's Needs |- | 150° | Quincunx | Nagging Voice of Dissatisfaction; Desire for Improvement; Attention to Details; Discernment |- | 180° | Opposition | Two Sides of One Coin; Stimulates Awareness to Balance, Integrate, & Become Whole |} '''Note on Application:''' When analyzing a Lost Zodiac chart, these four components are synthesized. The converted Lost Zodiac sign provides the thematic style, the house indicates the life area of expression, the planet identifies the driving psychological force, and the aspects reveal how these forces interact with the rest of the chart. hy258042bts3mv54tgmu4ylirs7q5t5 6 332280 2835161 2026-09-30T12:39:32Z Young1lim 21186 {{Information |Description=C04.SA0: Address and Dereference Operators (20260928 - 20260921) |Source={{own|Young1lim}} |Date=2026-09-30 |Author=Young W. Lim |Permission={{self|GFDL|cc-by-sa-4.0,3.0,2.5,2.0,1.0}} }} 2835161 wikitext text/x-wiki == Summary == {{Information |Description=C04.SA0: Address and Dereference Operators (20260928 - 20260921) |Source={{own|Young1lim}} |Date=2026-09-30 |Author=Young W. 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Lim |Permission={{self|GFDL|cc-by-sa-4.0,3.0,2.5,2.0,1.0}} }} 2835182 wikitext text/x-wiki == Summary == {{Information |Description=Laurent.5: Permutation 6C (20260929 - 20260928) |Source={{own|Young1lim}} |Date=2026-09-30 |Author=Young W. Lim |Permission={{self|GFDL|cc-by-sa-4.0,3.0,2.5,2.0,1.0}} }} == Licensing == {{self|GFDL|cc-by-sa-4.0,3.0,2.5,2.0,1.0}} e5ok6788qvcmee6313k0vq5xyho4m2t 0 332286 2835215 2026-09-30T17:39:20Z DavidMCEddy 218607 create 2835215 wikitext text/x-wiki :''This discusses a 2026-09-18 interview with Rainey Reitman<ref name=Reitman><!--Rainey Reitman-->{{cite Q|Q28778243}}</ref> about (a) how finance companies punish speech, (b) [[w:Freedom of the Press Foundation|Freedom of the Press Foundation]], and (c) their new Penlight prize,<ref name=Penlight><!--The Penlight Prize-->{{cite Q|Q141526943}}</ref> including a video and 29:00 mm:ss podcast excerpted from the interview. The podcast is released 2026-10-17 to the [[w:Fortnight|fortnightly]] "Media & Democracy" show<ref name=M&D><!--Media & Democracy-->{{cite Q|Q127839818}}</ref> syndicated for the [[w:Pacifica Foundation|Pacifica Radio]] Network<ref><!--Pacifica Radio Network-->{{cite Q|Q2045587}}</ref> of [[w:List of Pacifica Radio stations and affiliates|over 200 community radio stations]].''<ref><!--list of Pacifica Radio stations and affiliates-->{{cite Q|Q6593294}}</ref> :''It is posted here to invite others to contribute other perspectives, subject to the Wikimedia rules of [[w:Wikipedia:Neutral point of view|writing from a neutral point of view]] while [[w:Wikipedia:Citing sources|citing credible sources]]<ref name=NPOV>The rules of writing from a neutral point of view citing credible sources may not be enforced on other parts of Wikiversity. However, they can facilitate dialog between people with dramatically different beliefs.</ref> and treating others with respect.''<ref name=AGF>[[Wikiversity:Assume good faith|Wikiversity asks contributors to assume good faith]], similar to Wikipedia. The rule in [[w:Wikinews|Wikinews]] was different: Contributors there were asked to [[Wikinews:Never assume|"Don't assume things; be skeptical about everything."]] That's wise. However, we should still treat others with respect while being skeptical.</ref> <!--[[File:Rainey Reitman on how finance companies punish speech.webm|thumb|2026-09-18 interview with Rainey Reitman<ref nam=Reitman.> about how finance companies punish speech, [[w:Freedom of the Press Foundation|Freedom of the Press Foundation]], and their new Penlight prize.<ref name=Penlight/>]]--> <!--[[File:Rainey Reitman on how finance companies punish speech.ogg|thumb|29:00 mm:ss excerpts from a 2026-09-18 interview with Rainey Reitman<ref nam=Reitman.> about how finance companies punish speech, [[w:Freedom of the Press Foundation|Freedom of the Press Foundation]], and their new Penlight prize.<ref name=Penlight/>]]--> Rainey Reitman<ref name=Reitman/> describes (a) how finance companies punish speech, (b) [[w:Freedom of the Press Foundation|Freedom of the Press Foundation]], and (c) their new Penlight prize.<ref name=Penlight/> Reitman is a writer, civil liberties advocate, online organizer, and facilitator. She is currently president of the board of [[w:Freedom of the Press Foundation|Freedom of the Press Foundation]], which she co-founded in 2012. At that time she was activism director for the [[w:Electronic Frontier Foundation|Electronic Frontier Foundation]].<ref>"About" in "rainey reitman's blog".<!--rainey reitman's blog-->{{cite Q|Q141599314}}</ref> Her new book, ''Transaction Denied: Big Finance's Power to Punish Speech'',<ref>Reitman (2026).</ref> is a primary topic of this interview. She is interviewed by Spencer Graves.<ref name=Graves><!--Spencer Graves-->{{cite Q|Q56452480}}</ref> ==Highlights== :''These excerpts from the interview are rushed, lightly edited for readability, and may not be in final form. The ultimate authority on what was said is the accompanying video.'' Reitman said that ''Transactions Denied'' was the result of {{quote| probably 10 or 12 years that I was becoming increasingly aware of the ways that financial systems were being used as a backdoor way of punishing legal speakers. ... What I found through my research and through my own experience was that financial systems could be weaponized to shudder speakers who had not otherwise violated the law, but who were nonetheless heterodox or promoting viewpoints that perhaps ran contrary to the status quo. I became aware of it when one of my nonprofit projects, the [[w:Chelsea Manning|Chelsea Manning]] Support Network, had our [[w:PayPal|PayPal]] account frozen. Back in 2010-2011, when I first co-founded the Chelsea Manning Support Network, we were working to raise awareness of her campaign but also funds for her legal defense. We even had some ideas that we could help give her scholarship money to go to college after she got out of prison, assuming we were successful in our campaign. Lots of people were donating, including people outside of the United States. Many of the international donors used PayPal to send us money. And soon after [[w:WikiLeaks|WikiLeaks]] started publishing [[w:United States diplomatic cables leak|CableGate]], which was all of these documents of State Department cables that were so embarrassing to the United States government, all of a sudden, our campaign for Chelsea had our PayPal account frozen.}} === Chelsea v. Bradley === Graves interrupted, "Actually, it was not Chelsea at that time. It was Bradley still?" Reitman replied, "That's an interesting point. It's best practice when someone changes their name to always refer to them as their chosen name later. When you refer to them by their prior name, it's called '[[w:Deadnaming|deadnaming]]'. That's why I always call it the 'Chelsea Manning Support Network'. I always talk about 'Chelsea Manning' in a way to honor her identity and indicate that that is where she is now." === PayPal account frozen === Reitman continued, {{quote| So our PayPal account was frozen. Because I was involved in the campaign, I knew we hadn't done anything wrong. I knew that we were a legitimate nonprofit project, and that we had not violated any laws. I also had, through my work at the Electronic Frontier Foundation and previously with the Privacy Rights Clearinghouse,<ref><!--Privacy Rights Clearinghouse-->{{cite Q|Q7246018}}</ref> a lot of consumer advocacy contacts. So I have had plenty of contacts at companies that I use to advocate on behalf of consumers. So I felt certain I could get this resolved. And I went up the chain at PayPal, and I could not get them to reverse the decision. They kept saying it's an internal policy.<ref>Under certain circumstances, they are forbidden by law from giving you the real reason for the freeze, as discussed below in the section under [[Rainey Reitman on how finance companies punish speech#Discussion|Discussion]] on "[[Rainey Reitman on how finance companies punish speech#Frozen accounts restrict withdrawals but allow deposits|Frozen accounts restrict withdrawals but allow deposits]]".</ref> In the end, we launched a publicity campaign and got them to change their mind, reinstate our account, so that people could continue to donate to Chelsea's campaign. But for me, it was such a wake-up call of how small nonprofits who have a shoestring budget, that are trying to go up against the status quo, are so vulnerable to having their financial system shut down. I tried to collect a lot of stories over 10 years. I found that there were a few names that came up quite frequently. In my book, you'll see [[w:Chase Bank|Chase]] is particularly frequently mentioned. [[w:Bank of America|Bank of America]] comes up a fair amount. [[w:Mastercard|Mastercard]], [[w:Visa Inc.|Visa]], and PayPal were especially frequently named, but I would not say they're the only ones. For example, recently, a number of [[w:Donor-advised fund|donor-advised fund]]s, like [[w:Fidelity Investments|Fidelity]] and some of the other large ones, froze donor-advised donations to the [[w:Southern Poverty Law Center|Southern Poverty Law Center]]. And so we got to see, just this year, a pretty dramatic example of a legitimate nonprofit that still had its nonprofit status having countless donations to them frozen over a [[w:United States v. Southern Poverty Law Center Inc.|bogus investigation by the Trump administration]]. ... There's a lot of power from any financial institution to freeze the accounts of organizations that they disagree with, but it is the largest banks that we hear about most frequently. Those are the big players. They really set the terms for the rest of the financial industry.}} === Confiscate social security or retirement? === Graves asked, "Can they confiscate my Social Security or retirement annuities?" Reitman replied, "As far as I know, they cannot."<ref>In fact, financial institutions can accept deposits to frozen accounts and confiscate those funds under certain circumstances. Social security and some other funds are protected, but the protections are limited as discussed in the section under [[Rainey Reitman on how finance companies punish speech#Discussion|Discussion]] on "[[Rainey Reitman on how finance companies punish speech#Frozen accounts restrict withdrawals but allow deposits|Frozen accounts restrict withdrawals but allow deposits]]".</ref> === Motivation for financial institutions to freeze accounts === Graves then asked, "Talk about the motivation for the financial institutions to do this." Reitman replied, "One civil liberties advocate that I quote in my book that I think said it so well. He said that bankers are not known for their great moral fortitude. They are like long-tailed cats in a rocking chair store. These banks and their compliance officers will often go above and beyond what is required by law to stay in the good graces of what they believe could be the government's policies or other financial company policies, even when they don't need to, and even when it comes at the cost of real significant harms to their customers or to free speech online. I would characterize their motivation as over-compliance and fear." === Freezing sexual fantasies === Reitman continued, "It's worth noting that there are real morality aspects in some of the decisions that they're making. I have an entire chapter in my book on different forms of sexual speech. I talk a lot about legal sexual speech, like erotica, fictional erotica books that lost access to financial services." Graves interrupted, "Women writing for women, right?" Reitman agreed: "Often that is correct. A lot of the people I spoke to were writing about taboo subjects, but they're often women writing for other women readers. In those cases, we see financial institutions policing sexual thoughts and fantasies. It's hard to imagine that that's merely government compliance at that point. It seems like it's stepping into the realm of moralizing." === Marijuana === Graves noted, "You talk about [[w:Cannabis (drug)|marijuana]]." Reitman replied, {{quote| One of the people I talk a lot about in my book, was a journalist named Jackie Bryant.<ref><!--Jackie Bryant0-->{{cite Q|Q141600100}}</ref> Jackie is a journalist who writes in [[w:San Diego|San Diego]]. She writes about [[w:Cannabis (drug)|cannabis]]. She's a very well-known journalist, who has been writing about cannabis for years.She has a popular [[w:substack|substack]]. She used to publish with a San Diego newspaper. When that newspaper folded, she moved online to Substack. And then she had her [[w:Stripe, Inc.|Stripe]] account frozen. Substack uses Stripe to process payments, so as soon as her Stripe account was frozen, she wasn't able to get any paid subscribers to her newsletter, which was pretty popular. It was so popular, in fact, that when she wasn't able to get answers, Substack, the newsletter company, reached out to try to figure out what was going on. The found out from Stripe that the fact that Jackie was writing about marijuana, and that she was linking to companies that are marijuana companies, cannabis companies, that they were not going to allow her to have a Stripe account and have paid subscribers to her newsletter, unless she went through and removed all the hyperlinks from her newsletter. Anybody in the journalism space could understand that hyperlinks are very much citations online. We need to be able to include hyperlinks, because that's how you go back and find out what was this author referring to? Do I agree with it when I look at the original source? Jackie spoke out and was able to get coverage from other cannabis journalists, who spoke out about it. In the end, Stripe recanted, and she was able to get her account reinstated. But this really opened up for me a whole world, both of cannabis journalists and those journalists losing their bank accounts and financial services. ... Whether it's about medical issues, corporate issues, labor issues, policy issues. A lot of hot topics are happening in the cannabis space right now that are worthy of public scrutiny. After publishing this book and telling Jackie's story, I've heard from a whole raft of different cannabis journalists who say, "This happened to me too." So there's a whole group of journalists out there right now who are losing financial services just because of the topic they're writing about.}} === Two laws === Graves noted, "You mentioned two foundational laws: The [[w:Trading with the Enemy Act|Trading with the Enemy Act]] of 1917 and the [[w:International Emergency Economic Powers Act|International Emergency Economic Powers Act]] of 1977. And you said. they can fine a financial institution over $360,000 per violation."<ref>Reitman (2026, p. 60). A web search for documentation of fines of "over $360,000 per violation" identified Moss (2026), "TD Bank to Pay Record $3 Billion for BSA/AML Violations". $3 billion may sound like a lot of money but may be a minor cost of doing business, as outlined below in the section under [[Rainey Reitman on how finance companies punish speech#Discussion|Discussion]] on "''[[Rainey Reitman on how finance companies punish speech#The Chickenshit Club|''The Chickenshit Club]]''".</ref> Reitman replied, "These are what we often think of as [[w:Economic sanctions|economic sanctions]]. I don't take a position on sanctions in my book. A lot of people have written very thoughtfully about whether or not economic sanctions are helpful to the United States, whether or not they're appropriate -- sanctions against Iran, sanctions against Cuba." === Banking While Muslim === Reitman continued, {{quote| My book looked at people, who are not supposed to be subject to sanctions, just regular, everyday people who have names like Muhammad, who find themselves getting inadvertently flagged by the automated systems that financial institutions have in place to search for sanctions-violating transactions. Tons of people are inadvertently having their transactions flagged or blocked. ... I spoke to some lawyers, who are in this space. Most of them are Muslim Americans, who are not the subject of sanctions but have names that trigger sanctions review. It is easier, faster, and simpler for these banking services to simply shut off the accounts or freeze the transactions of these folks rather than go through the due diligence to ensure that those transactions, which are not violating any laws, can go through. One of the people I profiled in my book is a young poetry teacher ... . He teaches online. After he graduated from college with a degree in economics, he was having trouble finding a job. He became a popular online [[w:Persian language|Farsi]] teacher. He teaches Farsi to people all over the world. A lot of folks are of [[w:Iran|Iranian]] descent, and they want to learn Farsi, so they can get back to their roots. He teaches poetry classes on [[w:Rumi|Rumi]] and other poetry. And he teaches a ton of historical classes as well. You can go online at Persian Poetics<ref><!--Persian Poetics-->{{cite Q|Q141600385}}</ref> and buy a class pass. Then you can take classes with him. He was incredibly dependent on financial services like [[w:Chase Bank|Chase]] and [[w:Venmo|Venmo]], because he had to process so many different small transactions from different people all over the world. Many of them would write "Persian classes", and it would get his account flagged again and again and again. He just had problem after problem with his PayPal and Venmo account and later with his Chase Bank account, which ended up getting shut down entirely. I remember talking to him. He said, "I feel like I can't do anything, because there's nobody I can speak to about this. PayPal doesn't care. There's nobody I can appeal this to. I'm not gonna put together a lawsuit and try to sue them. I'm just a regular guy. The sense of being stuck and frozen, and at the same time, your livelihood, your ability to pay bills and cover your rent is dependent on these financial companies. And for what? For teaching poetry online." Those are the stories I wanted to hone in on, because I wanted to step away from sanctions. I get it. They [sanctions] are a complicated issue. People have feelings about them. But I want people to understand that it is not just the targets of sanctions that suffer from those programs. It is all sorts of people who did nothing wrong, who are simply speaking out online, publishing articles, teaching poetry classes, whose names happen to trigger something, who are losing access to financial services.}} === In any country in the world, you are free to say anything you want ...=== Graves then commented, "As you were speaking, I was reminded that the [[w:American Civil Liberties Union|American Civil Liberties Union]] decades ago famously said that in any country in the world, you're free to say anything you want ... as long as it's popular with those in power. It is only the freedom to say unpopular things that needs to be protected. And I would add that the primary reason for freedom of speech is not for the speaker, it's for the audience. Your comment?" Reitman responded, {{quote| Spencer, I think you're really nailing it,. I tried to make this such an important topic in my book, which included people from across the political spectrum. I have somebody who was a left-wing protester who lost her bank account after a going to the [[w:Stop Cop City|Stop Cop City]] rally in [[w:Atlanta|Atlanta]], [[w:Georgia (U.S. state)|Georgia]]. And then I had, on the right, someone who was advocating for religious freedom here in the United States, and had put together a non-profit advocating for religious freedom. He's very much on the right. He's [[w:Anti-abortion movements|anti-abortion]], pro-family values. I included them in the same chapter, because I wanted the reader to confront the idea that this matters even for people you disagree with. These basic rights to access financial services can be a devastating weapon against a plural democracy where all views are allowed to exist. We can't really defend freedom of speech, if we aren't looking at the backdoor ways that we are having it attacked.}} ===Southern Poverty Law Center=== Graves noted, "You mentioned the [[w:Southern Poverty Law Center|Southern Poverty Law Center]] was attacked. My understanding of their purpose and their activities is to try to shut down the [[w:Ku Klux Klan|Ku Klux Klan]] and [[w:Neo-Nazism|neo-Nazi]] groups, and they've been moderately successful." Reitman agreed. {{quote| Yes. ... The basis of the indictment had to do with this idea that for a period of time, the Southern Poverty Law Center allegedly had a system where they were paying informants to find out more information about what was happening within the white supremacy movement. They might pay an informant to find out about upcoming events and then be able to prepare for them and do something about it. That program doesn't exist anymore, but it did for a while. The Trump administration is alleging that by having this paid informants program, they were somehow supporting white supremacy, which is a ridiculous idea. The indictment is ridiculous. Everything about that case is a little ridiculous, including because the Southern Poverty Law Center worked very closely with the police in developing that program, is my understanding. ... But the financial systems, these donor-advised funds that nonprofit organizations very much rely on to do their work, didn't wait for a judge to weigh in on it, and instead said "Just because there's an indictment, just because this is in the news, we are going to stop donations to the Southern Poverty Law Center." And I want to flag that they didn't have to do that. And in fact, there were other donor-advised funds, like the [[w:San Francisco Foundation|San Francisco Foundation]], that said, we absolutely are going to continue to allow donations to flow to the Southern Poverty Law Center ... .}} === Trend === Graves asked, "Has this become more common in recent years, since the year 2000, or since Trump's second inauguration?" Reitman replied, {{quote| I don't think we have enough data to answer that question. ... We would have to require companies to be more transparent about when they're shutting off accounts and why they're shutting off accounts. Right now, they don't have to put out any kind of reports about that, not to the public and not to Congress. I think we need more transparency.<ref>In some cases banks are prohibited by law from giving the real reason for freezing an account, as discussed in the section on "[[Rainey Reitman on how finance companies punish speech#Frozen accounts restrict withdrawals but allow deposits|Frozen accounts restrict withdrawals but allow deposits]]" under [[Rainey Reitman on how finance companies punish speech#Discussion|Discussion]] below.</ref>}} === How to respond? === Graves then noted, "I'm Secretary of PeaceWorks Kansas City,<ref><!--PeaceWorks Kansas City-->{{cite Q|Q64287449}}</ref> and I'm writing research reports to raise questions about the US military budget and priorities. I can imagine that I would be targeted and that Peaceworks would be targeted. What should we do if we are?" Reitman replied, {{quote| I don't have a lot of examples. I don't have a lot of specific advice for individual consumers. I did look at a couple of alternatives to using the financial system. I looked at cash. Some people are like, "Should I just be dealing with cash?" Cash is quite censorship-resistant, and it's much more difficult to surveil, so there's a lot of benefits there. But cash is very difficult if you're trying to process online transactions, which a lot of organizations need to do. And cash is quite bulky if you're trying to move it around in large quantities. If you're, say, a dental office, that's physically quite a lot of cash to manage. It's just not gonna be a great solution. I mention in my book, cash is also under attack. A lot of people are promoting the elimination or the reduction of cash in our society, that we would move to almost all digital transactions. That would have so much more surveillance, so much more control, and all these problems of censorship. So, rather than seeing cash as a savior, I really said cash is under attack right now. If we want to have it for future generations, we need to protect it. I also looked at cryptocurrency. Cryptocurrency is a very hot button issue. People have strong feelings about it. I didn't want to wade into all that. I just wanted this one question answered, which is, "Is it censorship resistant?" Could you use cryptocurrency if PayPal or Visa or whoever had shut you down? And what I said is, technically, yes, the protocol is pretty censorship resistant. But most people who are using cryptocurrency today are using it through a cryptocurrency company. They're using a [[w:Coinbase|Coinbase]] or [[w:Kraken (cryptocurrency exchange)|Kraken]] or one of these big cryptocurrency companies. And as soon as they do that, they've basically recreated the same systems of control that we have in the traditional financial world.}} ===Freedom of the Press Foundation=== Graves asked, "Talk about Freedom of the Press Foundation." Reitman replied, {{quote| Freedom of the Press Foundation is a non-profit that I co-founded with my friend Trevor Tim<ref><!--Trevor Tim-->{{cite Q|Q141606284}}</ref> back in 2012. Freedom of the Press Foundation works to promote freedom of speech and defend the rights of journalists in the United States and a little bit outside of the United States, increasingly. We do advocacy around the law, but we also do technical projects to provide tools for journalists. For example, we have a project called [[w:SecureDrop|SecureDrop]], which we have set up in all these newsrooms around the world that lets any news organization securely receive anonymous documents from whistleblowers. And then, let's say the government comes to those news organizations in the future and says, "You have to tell us where you got this." The news organization can say, "We don't know. We never got their information. It's a super secure system, so there's no way for us to find out." We maintain that system and a number of other projects that help support journalists. Maybe more broadly, I think we're a voice for unyielding support for the First Amendment here in the United States, which I think is incredibly important at this moment.}} === Penlight prize === Reitman continued, {{quote| We have a new prize: The Pennlight Prize is a project that we launched with the support of a donor this year. The idea is to provide a $25,000 prize to a journalist who publishes an article based on [[w:Freedom of Information Act|Freedom of Information Act]] documents that they published outside of a paywall. Here's why we're doing that. One of the things that has happened, and I completely understand why it's happening, is that so much important and necessary information that the public needs to know is increasingly behind paywalls. There are so many different news organizations that people don't end up getting a subscription to 55 different news organizations. So they hit a paywall and they leave. And where do they go? They go to less reliable news organizations. They go to misinformation websites. They get bogus data because it's not behind paywalls. And they're filled up with a whole bunch of wrong data. So we wanted to find a way to encourage at least a tiny amount of information, super high-quality journalism, to be outside of paywalls and to help inform the public. And Freedom of Information Act requests are documents based on information that we have a right to know. It was made publicly available, so we want the underlying documents to be made public, and we want the articles about those documents to also be outside of a paywall. So we made this a very big journalism prize. Journalists traditionally don't make a lot of money. Our hope was that by making it a significant prize, $25,000, that it would incentivize journalists to really advocate for these policies internally within their news organizations. This is the first year we're doing it. We had over 100 submissions. We're working through them right now. My hope is that next year, maybe we get 300 submissions, and we get more news organizations saying, "We're taking these important articles. We're putting them outside of the paywall, so that more people can get access to them."}} === Changes since publication? === Graves asked, "What has changed in this regard since your book went to press?" Reitman replied, "I submitted this book before I knew if Kamala or Trump was going to win, and I really had no idea what kind of a political reality this book was going to be born into. ..." Graves asked, "What reactions have you gotten from the book?" Reitman replied, {{quote| Very positive for the most part from the civil liberties community and from lots of different folks in the tech sphere. The financial companies have been less positive about it. Some of the feedback I got from people in the financial space was this idea that they're the victims, right? "We are just doing what we have to, and you're painting us as the villains", which I feel is overly simplistic and frankly not accurate. I think there's a lot of power within these financial companies to develop positions that could harm or hurt consumers, and they're not doing their due diligence to stand up for free speech ... .}} Graves asked, "What about elected officials like Senator Elizabeth Warren?" Reitman replied, "I haven't talked to Senator Elizabeth Warren about it." === Final words === When asked for final words for the audience, Reitman replied, "If folks are interested, one of the best ways to support a new author is to buy a book from a local bookseller or whoever. It's called ''Transaction Denied.'' And half of the author proceeds go to support the Freedom of the Press Foundation ... ." Graves added that he had previously interviewed [[Freedom of the Press Foundation says...|a couple of the leaders from Freedom of Press Foundation]] earlier in this Media Democracy series, "and I've been a long-time supporter." ==Discussion == :''[Interested readers are invited to comment here, subject to the Wikimedia rules of [[w:Wikipedia:Neutral point of view|writing from a neutral point of view]] [[w:Wikipedia:Citing sources|citing credible sources]]<ref name=NPOV/> and treating others with respect.<ref name=AGF/>]'' ===Frozen accounts restrict withdrawals but allow deposits=== In this interview Graves asked, "Can they confiscate my Social Security or retirement annuities?" Reitman replied, "As far as I know, they cannot." Further research suggests the reality is complicated in part, because accounts can be frozen in some cases by creditors as well as under anti–money laundering laws. Eneriz (2026) says, "A frozen bank account restricts you from withdrawing or transferring funds but allows deposits." fedlaws.org (2026) provides more detail with legal citations. They say, {{quote| A freeze blocks withdrawals, transfers, and scheduled payments while keeping the account technically open. ... When a bank’s monitoring flags a suspicious pattern, it files a Suspicious Activity Report with the Financial Crimes Enforcement Network. ... :''These freezes are the most disorienting because the bank is legally prohibited from telling you the real reason.'' (emphasis added) ... Even when a garnishment order is perfectly valid, certain money in your account is off-limits. Federal law protects direct-deposited benefits from Social Security [and some other funds]. ... When a bank receives a garnishment order, it must look back over the prior two months of deposits and calculate a “protected amount” equal to the total federal benefit payments deposited during that window. The bank must give you full access to that protected amount without requiring paperwork or an exemption claim. ... If your account contains additional exempt funds above the protected amount, you can assert a further exemption by contacting the creditor, completing an exemption form with the court, or working with a legal aid attorney. One detail most people miss: direct deposit matters. If you receive benefits by paper check and deposit them yourself, the automatic two-month lookback may not identify the funds as protected. Direct deposit creates the electronic trail the bank’s system uses. Joint Accounts Put Your Money at Risk ... The law generally presumes each co-owner has equal rights to every dollar in the account, so a creditor pursuing one account holder can freeze the entire balance. .. A non-debtor co-owner can fight this, but must act fast. The garnishment notice includes a hearing date, and requesting that hearing in writing before the deadline is critical. ... Miss the hearing and the court can release the entire balance to the creditor.}} === ''The Chickenshit Club'' === The interview mentioned potential fines of over $360,000 per violation, mentioned by Reitman (2026, p. 60). A web search for documentation of such fines identified Moss (2026), "TD Bank to Pay Record $3 Billion for [[w:Bank Secrecy Act|BSA]]/AML Violations". However, no mention was found of fines "over $360,000 per violation." $3 billion may sound like a lot of money but may be a minor cost of doing business for a large organization like [[w:TD Bank (United States)|TD Bank]]. The article by Moss (2026) reported that, {{quote| senior management at TD Bank knew that its failure to adequately support [[w:Anti–money laundering|AML]] compliance created backlogs that allowed illicit transactions to continue to flow through the bank. ... Notably, the bank: ... Allowed trillions of dollars of domestic [[w:ACH Network|ACH]], remote deposit capture, and peer-to-peer (P2P) transactions to go unmonitored for over a decade." It's not immediately obvious how much money TD Bank made from having "allowed trillions of dollars of ... transactions to go unmonitored". Might $3 billion have been a small percentage of what they made violating the law? The fact that the settlement did not include prison time for any "senior management" is consistent with the discussion in "[[Dean Starkman and the watchdog that didn't bark]]" of "Whitewashing corporate crime ... described by Eisinger (2017) :[''The chickenshit club : why the Justice Department fails to prosecute executives'']. :''When these deals are announced with the Justice Department, invariably the shares of the company go up, not down.'' (emphasis added)}} == Notes == {{reflist}} == Bibliography == * <!--Jesse Eisinger (2017) The chickenshit club : why the Justice Department fails to prosecute executives-->{{cite Q|Q134599351}} * <!--Ashley Eneriz (2026-09-25) "Frozen Bank Account: Common Causes and Steps to Unfreeze"-->{{cite Q|Q141599984}} * <!--fedlaws.org (2026-09-23) "Why Do Banks Freeze Accounts? Triggers, Exemptions, and Fixes-->{{cite Q|Q141599719}} * <!--Valerie Moss (2024-10-17) "TD Bank to Pay Record $3 Billion for BSA/AML Violations"-->{{cite Q|Q141600174}} * <!--Rainey Reitman (2026-04-07) Transaction Denied: Big Finance's Power to Punish Speech-->{{cite Q|Q141526890}} [[Category:Media]] [[Category:News]] [[Category:Democracy]] [[Category:Politics]] [[Category:Political economy]] [[Category:Freedom of speech]] [[Category:Finance]] [[Category:Economics and Personal Finance]] [[Category:Media reform to improve democracy]] <!--list of categories https://en.wikiversity.org/wiki/Wikiversity:Category_Review [[Wikiversity:Category Review]]--> q8ik7szlt23fm1ps7r4k1voqwukir3z 2835225 2835215 2026-09-30T20:28:48Z DavidMCEddy 218607 typo 2835225 wikitext text/x-wiki :''This discusses a 2026-09-18 interview with Rainey Reitman<ref name=Reitman><!--Rainey Reitman-->{{cite Q|Q28778243}}</ref> about (a) how finance companies punish speech, (b) [[w:Freedom of the Press Foundation|Freedom of the Press Foundation]], and (c) their new Penlight prize,<ref name=Penlight><!--The Penlight Prize-->{{cite Q|Q141526943}}</ref> including a video and 29:00 mm:ss podcast excerpted from the interview. The podcast is released 2026-10-17 to the [[w:Fortnight|fortnightly]] "Media & Democracy" show<ref name=M&D><!--Media & Democracy-->{{cite Q|Q127839818}}</ref> syndicated for the [[w:Pacifica Foundation|Pacifica Radio]] Network<ref><!--Pacifica Radio Network-->{{cite Q|Q2045587}}</ref> of [[w:List of Pacifica Radio stations and affiliates|over 200 community radio stations]].''<ref><!--list of Pacifica Radio stations and affiliates-->{{cite Q|Q6593294}}</ref> :''It is posted here to invite others to contribute other perspectives, subject to the Wikimedia rules of [[w:Wikipedia:Neutral point of view|writing from a neutral point of view]] while [[w:Wikipedia:Citing sources|citing credible sources]]<ref name=NPOV>The rules of writing from a neutral point of view citing credible sources may not be enforced on other parts of Wikiversity. However, they can facilitate dialog between people with dramatically different beliefs.</ref> and treating others with respect.''<ref name=AGF>[[Wikiversity:Assume good faith|Wikiversity asks contributors to assume good faith]], similar to Wikipedia. The rule in [[w:Wikinews|Wikinews]] was different: Contributors there were asked to [[Wikinews:Never assume|"Don't assume things; be skeptical about everything."]] That's wise. However, we should still treat others with respect while being skeptical.</ref> <!--[[File:Rainey Reitman on how finance companies punish speech.webm|thumb|2026-09-18 interview with Rainey Reitman<ref nam=Reitman.> about how finance companies punish speech, [[w:Freedom of the Press Foundation|Freedom of the Press Foundation]], and their new Penlight prize.<ref name=Penlight/>]]--> <!--[[File:Rainey Reitman on how finance companies punish speech.ogg|thumb|29:00 mm:ss excerpts from a 2026-09-18 interview with Rainey Reitman<ref nam=Reitman.> about how finance companies punish speech, [[w:Freedom of the Press Foundation|Freedom of the Press Foundation]], and their new Penlight prize.<ref name=Penlight/>]]--> Rainey Reitman<ref name=Reitman/> describes (a) how finance companies punish speech, (b) [[w:Freedom of the Press Foundation|Freedom of the Press Foundation]], and (c) their new Penlight prize.<ref name=Penlight/> Reitman is a writer, civil liberties advocate, online organizer, and facilitator. She is currently president of the board of [[w:Freedom of the Press Foundation|Freedom of the Press Foundation]], which she co-founded in 2012. At that time she was activism director for the [[w:Electronic Frontier Foundation|Electronic Frontier Foundation]].<ref>"About" in "rainey reitman's blog".<!--rainey reitman's blog-->{{cite Q|Q141599314}}</ref> Her new book, ''Transaction Denied: Big Finance's Power to Punish Speech'',<ref>Reitman (2026).</ref> is a primary topic of this interview. She is interviewed by Spencer Graves.<ref name=Graves><!--Spencer Graves-->{{cite Q|Q56452480}}</ref> ==Highlights== :''These excerpts from the interview are rushed, lightly edited for readability, and may not be in final form. The ultimate authority on what was said is the accompanying video.'' Reitman said that ''Transactions Denied'' was the result of {{quote| probably 10 or 12 years that I was becoming increasingly aware of the ways that financial systems were being used as a backdoor way of punishing legal speakers. ... What I found through my research and through my own experience was that financial systems could be weaponized to shudder speakers who had not otherwise violated the law, but who were nonetheless heterodox or promoting viewpoints that perhaps ran contrary to the status quo. I became aware of it when one of my nonprofit projects, the [[w:Chelsea Manning|Chelsea Manning]] Support Network, had our [[w:PayPal|PayPal]] account frozen. Back in 2010-2011, when I first co-founded the Chelsea Manning Support Network, we were working to raise awareness of her campaign but also funds for her legal defense. We even had some ideas that we could help give her scholarship money to go to college after she got out of prison, assuming we were successful in our campaign. Lots of people were donating, including people outside of the United States. Many of the international donors used PayPal to send us money. And soon after [[w:WikiLeaks|WikiLeaks]] started publishing [[w:United States diplomatic cables leak|CableGate]], which was all of these documents of State Department cables that were so embarrassing to the United States government, all of a sudden, our campaign for Chelsea had our PayPal account frozen.}} === Chelsea v. Bradley === Graves interrupted, "Actually, it was not Chelsea at that time. It was Bradley still?" Reitman replied, "That's an interesting point. It's best practice when someone changes their name to always refer to them as their chosen name later. When you refer to them by their prior name, it's called '[[w:Deadnaming|deadnaming]]'. That's why I always call it the 'Chelsea Manning Support Network'. I always talk about 'Chelsea Manning' in a way to honor her identity and indicate that that is where she is now." === PayPal account frozen === Reitman continued, {{quote| So our PayPal account was frozen. Because I was involved in the campaign, I knew we hadn't done anything wrong. I knew that we were a legitimate nonprofit project, and that we had not violated any laws. I also had, through my work at the Electronic Frontier Foundation and previously with the Privacy Rights Clearinghouse,<ref><!--Privacy Rights Clearinghouse-->{{cite Q|Q7246018}}</ref> a lot of consumer advocacy contacts. So I have had plenty of contacts at companies that I use to advocate on behalf of consumers. So I felt certain I could get this resolved. And I went up the chain at PayPal, and I could not get them to reverse the decision. They kept saying it's an internal policy.<ref>Under certain circumstances, they are forbidden by law from giving you the real reason for the freeze, as discussed below in the section under [[Rainey Reitman on how finance companies punish speech#Discussion|Discussion]] on "[[Rainey Reitman on how finance companies punish speech#Frozen accounts restrict withdrawals but allow deposits|Frozen accounts restrict withdrawals but allow deposits]]".</ref> In the end, we launched a publicity campaign and got them to change their mind, reinstate our account, so that people could continue to donate to Chelsea's campaign. But for me, it was such a wake-up call of how small nonprofits who have a shoestring budget, that are trying to go up against the status quo, are so vulnerable to having their financial system shut down. I tried to collect a lot of stories over 10 years. I found that there were a few names that came up quite frequently. In my book, you'll see [[w:Chase Bank|Chase]] is particularly frequently mentioned. [[w:Bank of America|Bank of America]] comes up a fair amount. [[w:Mastercard|Mastercard]], [[w:Visa Inc.|Visa]], and PayPal were especially frequently named, but I would not say they're the only ones. For example, recently, a number of [[w:Donor-advised fund|donor-advised fund]]s, like [[w:Fidelity Investments|Fidelity]] and some of the other large ones, froze donor-advised donations to the [[w:Southern Poverty Law Center|Southern Poverty Law Center]]. And so we got to see, just this year, a pretty dramatic example of a legitimate nonprofit that still had its nonprofit status having countless donations to them frozen over a [[w:United States v. Southern Poverty Law Center Inc.|bogus investigation by the Trump administration]]. ... There's a lot of power from any financial institution to freeze the accounts of organizations that they disagree with, but it is the largest banks that we hear about most frequently. Those are the big players. They really set the terms for the rest of the financial industry.}} === Confiscate social security or retirement? === Graves asked, "Can they confiscate my Social Security or retirement annuities?" Reitman replied, "As far as I know, they cannot."<ref>In fact, financial institutions can accept deposits to frozen accounts and confiscate those funds under certain circumstances. Social security and some other funds are protected, but the protections are limited as discussed in the section under [[Rainey Reitman on how finance companies punish speech#Discussion|Discussion]] on "[[Rainey Reitman on how finance companies punish speech#Frozen accounts restrict withdrawals but allow deposits|Frozen accounts restrict withdrawals but allow deposits]]".</ref> === Motivation for financial institutions to freeze accounts === Graves then asked, "Talk about the motivation for the financial institutions to do this." Reitman replied, "One civil liberties advocate that I quote in my book that I think said it so well. He said that bankers are not known for their great moral fortitude. They are like long-tailed cats in a rocking chair store. These banks and their compliance officers will often go above and beyond what is required by law to stay in the good graces of what they believe could be the government's policies or other financial company policies, even when they don't need to, and even when it comes at the cost of real significant harms to their customers or to free speech online. I would characterize their motivation as over-compliance and fear." === Freezing sexual fantasies === Reitman continued, "It's worth noting that there are real morality aspects in some of the decisions that they're making. I have an entire chapter in my book on different forms of sexual speech. I talk a lot about legal sexual speech, like erotica, fictional erotica books that lost access to financial services." Graves interrupted, "Women writing for women, right?" Reitman agreed: "Often that is correct. A lot of the people I spoke to were writing about taboo subjects, but they're often women writing for other women readers. In those cases, we see financial institutions policing sexual thoughts and fantasies. It's hard to imagine that that's merely government compliance at that point. It seems like it's stepping into the realm of moralizing." === Marijuana === Graves noted, "You talk about [[w:Cannabis (drug)|marijuana]]." Reitman replied, {{quote| One of the people I talk a lot about in my book, was a journalist named Jackie Bryant.<ref><!--Jackie Bryant0-->{{cite Q|Q141600100}}</ref> Jackie is a journalist who writes in [[w:San Diego|San Diego]]. She writes about [[w:Cannabis (drug)|cannabis]]. She's a very well-known journalist, who has been writing about cannabis for years.She has a popular [[w:substack|substack]]. She used to publish with a San Diego newspaper. When that newspaper folded, she moved online to Substack. And then she had her [[w:Stripe, Inc.|Stripe]] account frozen. Substack uses Stripe to process payments, so as soon as her Stripe account was frozen, she wasn't able to get any paid subscribers to her newsletter, which was pretty popular. It was so popular, in fact, that when she wasn't able to get answers, Substack, the newsletter company, reached out to try to figure out what was going on. The found out from Stripe that the fact that Jackie was writing about marijuana, and that she was linking to companies that are marijuana companies, cannabis companies, that they were not going to allow her to have a Stripe account and have paid subscribers to her newsletter, unless she went through and removed all the hyperlinks from her newsletter. Anybody in the journalism space could understand that hyperlinks are very much citations online. We need to be able to include hyperlinks, because that's how you go back and find out what was this author referring to? Do I agree with it when I look at the original source? Jackie spoke out and was able to get coverage from other cannabis journalists, who spoke out about it. In the end, Stripe recanted, and she was able to get her account reinstated. But this really opened up for me a whole world, both of cannabis journalists and those journalists losing their bank accounts and financial services. ... Whether it's about medical issues, corporate issues, labor issues, policy issues. A lot of hot topics are happening in the cannabis space right now that are worthy of public scrutiny. After publishing this book and telling Jackie's story, I've heard from a whole raft of different cannabis journalists who say, "This happened to me too." So there's a whole group of journalists out there right now who are losing financial services just because of the topic they're writing about.}} === Two laws === Graves noted, "You mentioned two foundational laws: The [[w:Trading with the Enemy Act|Trading with the Enemy Act]] of 1917 and the [[w:International Emergency Economic Powers Act|International Emergency Economic Powers Act]] of 1977. And you said. they can fine a financial institution over $360,000 per violation."<ref>Reitman (2026, p. 60). A web search for documentation of fines of "over $360,000 per violation" identified Moss (2026), "TD Bank to Pay Record $3 Billion for BSA/AML Violations". $3 billion may sound like a lot of money but may be a minor cost of doing business, as outlined below in the section under [[Rainey Reitman on how finance companies punish speech#Discussion|Discussion]] on "''[[Rainey Reitman on how finance companies punish speech#The Chickenshit Club|''The Chickenshit Club]]''".</ref> Reitman replied, "These are what we often think of as [[w:Economic sanctions|economic sanctions]]. I don't take a position on sanctions in my book. A lot of people have written very thoughtfully about whether or not economic sanctions are helpful to the United States, whether or not they're appropriate -- sanctions against Iran, sanctions against Cuba." === Banking While Muslim === Reitman continued, {{quote| My book looked at people, who are not supposed to be subject to sanctions, just regular, everyday people who have names like Muhammad, who find themselves getting inadvertently flagged by the automated systems that financial institutions have in place to search for sanctions-violating transactions. Tons of people are inadvertently having their transactions flagged or blocked. ... I spoke to some lawyers, who are in this space. Most of them are Muslim Americans, who are not the subject of sanctions but have names that trigger sanctions review. It is easier, faster, and simpler for these banking services to simply shut off the accounts or freeze the transactions of these folks rather than go through the due diligence to ensure that those transactions, which are not violating any laws, can go through. One of the people I profiled in my book is a young poetry teacher ... . He teaches online. After he graduated from college with a degree in economics, he was having trouble finding a job. He became a popular online [[w:Persian language|Farsi]] teacher. He teaches Farsi to people all over the world. A lot of folks are of [[w:Iran|Iranian]] descent, and they want to learn Farsi, so they can get back to their roots. He teaches poetry classes on [[w:Rumi|Rumi]] and other poetry. And he teaches a ton of historical classes as well. You can go online at Persian Poetics<ref><!--Persian Poetics-->{{cite Q|Q141600385}}</ref> and buy a class pass. Then you can take classes with him. He was incredibly dependent on financial services like [[w:Chase Bank|Chase]] and [[w:Venmo|Venmo]], because he had to process so many different small transactions from different people all over the world. Many of them would write "Persian classes", and it would get his account flagged again and again and again. He just had problem after problem with his PayPal and Venmo account and later with his Chase Bank account, which ended up getting shut down entirely. I remember talking to him. He said, "I feel like I can't do anything, because there's nobody I can speak to about this. PayPal doesn't care. There's nobody I can appeal this to. I'm not gonna put together a lawsuit and try to sue them. I'm just a regular guy. The sense of being stuck and frozen, and at the same time, your livelihood, your ability to pay bills and cover your rent is dependent on these financial companies. And for what? For teaching poetry online." Those are the stories I wanted to hone in on, because I wanted to step away from sanctions. I get it. They [sanctions] are a complicated issue. People have feelings about them. But I want people to understand that it is not just the targets of sanctions that suffer from those programs. It is all sorts of people who did nothing wrong, who are simply speaking out online, publishing articles, teaching poetry classes, whose names happen to trigger something, who are losing access to financial services.}} === In any country in the world, you are free to say anything you want ...=== Graves then commented, "As you were speaking, I was reminded that the [[w:American Civil Liberties Union|American Civil Liberties Union]] decades ago famously said that in any country in the world, you're free to say anything you want ... as long as it's popular with those in power. It is only the freedom to say unpopular things that needs to be protected. And I would add that the primary reason for freedom of speech is not for the speaker, it's for the audience. Your comment?" Reitman responded, {{quote| Spencer, I think you're really nailing it,. I tried to make this such an important topic in my book, which included people from across the political spectrum. I have somebody who was a left-wing protester who lost her bank account after a going to the [[w:Stop Cop City|Stop Cop City]] rally in [[w:Atlanta|Atlanta]], [[w:Georgia (U.S. state)|Georgia]]. And then I had, on the right, someone who was advocating for religious freedom here in the United States, and had put together a non-profit advocating for religious freedom. He's very much on the right. He's [[w:Anti-abortion movements|anti-abortion]], pro-family values. I included them in the same chapter, because I wanted the reader to confront the idea that this matters even for people you disagree with. These basic rights to access financial services can be a devastating weapon against a plural democracy where all views are allowed to exist. We can't really defend freedom of speech, if we aren't looking at the backdoor ways that we are having it attacked.}} ===Southern Poverty Law Center=== Graves noted, "You mentioned the [[w:Southern Poverty Law Center|Southern Poverty Law Center]] was attacked. My understanding of their purpose and their activities is to try to shut down the [[w:Ku Klux Klan|Ku Klux Klan]] and [[w:Neo-Nazism|neo-Nazi]] groups, and they've been moderately successful." Reitman agreed. {{quote| Yes. ... The basis of the indictment had to do with this idea that for a period of time, the Southern Poverty Law Center allegedly had a system where they were paying informants to find out more information about what was happening within the white supremacy movement. They might pay an informant to find out about upcoming events and then be able to prepare for them and do something about it. That program doesn't exist anymore, but it did for a while. The Trump administration is alleging that by having this paid informants program, they were somehow supporting white supremacy, which is a ridiculous idea. The indictment is ridiculous. Everything about that case is a little ridiculous, including because the Southern Poverty Law Center worked very closely with the police in developing that program, is my understanding. ... But the financial systems, these donor-advised funds that nonprofit organizations very much rely on to do their work, didn't wait for a judge to weigh in on it, and instead said "Just because there's an indictment, just because this is in the news, we are going to stop donations to the Southern Poverty Law Center." And I want to flag that they didn't have to do that. And in fact, there were other donor-advised funds, like the [[w:San Francisco Foundation|San Francisco Foundation]], that said, we absolutely are going to continue to allow donations to flow to the Southern Poverty Law Center ... .}} === Trend === Graves asked, "Has this become more common in recent years, since the year 2000, or since Trump's second inauguration?" Reitman replied, {{quote| I don't think we have enough data to answer that question. ... We would have to require companies to be more transparent about when they're shutting off accounts and why they're shutting off accounts. Right now, they don't have to put out any kind of reports about that, not to the public and not to Congress. I think we need more transparency.<ref>In some cases banks are prohibited by law from giving the real reason for freezing an account, as discussed in the section on "[[Rainey Reitman on how finance companies punish speech#Frozen accounts restrict withdrawals but allow deposits|Frozen accounts restrict withdrawals but allow deposits]]" under [[Rainey Reitman on how finance companies punish speech#Discussion|Discussion]] below.</ref>}} === How to respond? === Graves then noted, "I'm Secretary of PeaceWorks Kansas City,<ref><!--PeaceWorks Kansas City-->{{cite Q|Q64287449}}</ref> and I'm writing research reports to raise questions about the US military budget and priorities. I can imagine that I would be targeted and that Peaceworks would be targeted. What should we do if we are?" Reitman replied, {{quote| I don't have a lot of examples. I don't have a lot of specific advice for individual consumers. I did look at a couple of alternatives to using the financial system. I looked at cash. Some people are like, "Should I just be dealing with cash?" Cash is quite censorship-resistant, and it's much more difficult to surveil, so there's a lot of benefits there. But cash is very difficult if you're trying to process online transactions, which a lot of organizations need to do. And cash is quite bulky if you're trying to move it around in large quantities. If you're, say, a dental office, that's physically quite a lot of cash to manage. It's just not gonna be a great solution. I mention in my book, cash is also under attack. A lot of people are promoting the elimination or the reduction of cash in our society, that we would move to almost all digital transactions. That would have so much more surveillance, so much more control, and all these problems of censorship. So, rather than seeing cash as a savior, I really said cash is under attack right now. If we want to have it for future generations, we need to protect it. I also looked at cryptocurrency. Cryptocurrency is a very hot button issue. People have strong feelings about it. I didn't want to wade into all that. I just wanted this one question answered, which is, "Is it censorship resistant?" Could you use cryptocurrency if PayPal or Visa or whoever had shut you down? And what I said is, technically, yes, the protocol is pretty censorship resistant. But most people who are using cryptocurrency today are using it through a cryptocurrency company. They're using a [[w:Coinbase|Coinbase]] or [[w:Kraken (cryptocurrency exchange)|Kraken]] or one of these big cryptocurrency companies. And as soon as they do that, they've basically recreated the same systems of control that we have in the traditional financial world.}} ===Freedom of the Press Foundation=== Graves asked, "Talk about Freedom of the Press Foundation." Reitman replied, {{quote| Freedom of the Press Foundation is a non-profit that I co-founded with my friend Trevor Timm<ref><!--Trevor Timm-->{{cite Q|Q141606284}}</ref> back in 2012. Freedom of the Press Foundation works to promote freedom of speech and defend the rights of journalists in the United States and a little bit outside of the United States, increasingly. We do advocacy around the law, but we also do technical projects to provide tools for journalists. For example, we have a project called [[w:SecureDrop|SecureDrop]], which we have set up in all these newsrooms around the world that lets any news organization securely receive anonymous documents from whistleblowers. And then, let's say the government comes to those news organizations in the future and says, "You have to tell us where you got this." The news organization can say, "We don't know. We never got their information. It's a super secure system, so there's no way for us to find out." We maintain that system and a number of other projects that help support journalists. Maybe more broadly, I think we're a voice for unyielding support for the First Amendment here in the United States, which I think is incredibly important at this moment.}} === Penlight prize === Reitman continued, {{quote| We have a new prize: The Pennlight Prize is a project that we launched with the support of a donor this year. The idea is to provide a $25,000 prize to a journalist who publishes an article based on [[w:Freedom of Information Act|Freedom of Information Act]] documents that they published outside of a paywall. Here's why we're doing that. One of the things that has happened, and I completely understand why it's happening, is that so much important and necessary information that the public needs to know is increasingly behind paywalls. There are so many different news organizations that people don't end up getting a subscription to 55 different news organizations. So they hit a paywall and they leave. And where do they go? They go to less reliable news organizations. They go to misinformation websites. They get bogus data because it's not behind paywalls. And they're filled up with a whole bunch of wrong data. So we wanted to find a way to encourage at least a tiny amount of information, super high-quality journalism, to be outside of paywalls and to help inform the public. And Freedom of Information Act requests are documents based on information that we have a right to know. It was made publicly available, so we want the underlying documents to be made public, and we want the articles about those documents to also be outside of a paywall. So we made this a very big journalism prize. Journalists traditionally don't make a lot of money. Our hope was that by making it a significant prize, $25,000, that it would incentivize journalists to really advocate for these policies internally within their news organizations. This is the first year we're doing it. We had over 100 submissions. We're working through them right now. My hope is that next year, maybe we get 300 submissions, and we get more news organizations saying, "We're taking these important articles. We're putting them outside of the paywall, so that more people can get access to them."}} === Changes since publication? === Graves asked, "What has changed in this regard since your book went to press?" Reitman replied, "I submitted this book before I knew if Kamala or Trump was going to win, and I really had no idea what kind of a political reality this book was going to be born into. ..." Graves asked, "What reactions have you gotten from the book?" Reitman replied, {{quote| Very positive for the most part from the civil liberties community and from lots of different folks in the tech sphere. The financial companies have been less positive about it. Some of the feedback I got from people in the financial space was this idea that they're the victims, right? "We are just doing what we have to, and you're painting us as the villains", which I feel is overly simplistic and frankly not accurate. I think there's a lot of power within these financial companies to develop positions that could harm or hurt consumers, and they're not doing their due diligence to stand up for free speech ... .}} Graves asked, "What about elected officials like Senator Elizabeth Warren?" Reitman replied, "I haven't talked to Senator Elizabeth Warren about it." === Final words === When asked for final words for the audience, Reitman replied, "If folks are interested, one of the best ways to support a new author is to buy a book from a local bookseller or whoever. It's called ''Transaction Denied.'' And half of the author proceeds go to support the Freedom of the Press Foundation ... ." Graves added that he had previously interviewed [[Freedom of the Press Foundation says...|a couple of the leaders from Freedom of Press Foundation]] earlier in this Media Democracy series, "and I've been a long-time supporter." ==Discussion == :''[Interested readers are invited to comment here, subject to the Wikimedia rules of [[w:Wikipedia:Neutral point of view|writing from a neutral point of view]] [[w:Wikipedia:Citing sources|citing credible sources]]<ref name=NPOV/> and treating others with respect.<ref name=AGF/>]'' ===Frozen accounts restrict withdrawals but allow deposits=== In this interview Graves asked, "Can they confiscate my Social Security or retirement annuities?" Reitman replied, "As far as I know, they cannot." Further research suggests the reality is complicated in part, because accounts can be frozen in some cases by creditors as well as under anti–money laundering laws. Eneriz (2026) says, "A frozen bank account restricts you from withdrawing or transferring funds but allows deposits." fedlaws.org (2026) provides more detail with legal citations. They say, {{quote| A freeze blocks withdrawals, transfers, and scheduled payments while keeping the account technically open. ... When a bank’s monitoring flags a suspicious pattern, it files a Suspicious Activity Report with the Financial Crimes Enforcement Network. ... :''These freezes are the most disorienting because the bank is legally prohibited from telling you the real reason.'' (emphasis added) ... Even when a garnishment order is perfectly valid, certain money in your account is off-limits. Federal law protects direct-deposited benefits from Social Security [and some other funds]. ... When a bank receives a garnishment order, it must look back over the prior two months of deposits and calculate a “protected amount” equal to the total federal benefit payments deposited during that window. The bank must give you full access to that protected amount without requiring paperwork or an exemption claim. ... If your account contains additional exempt funds above the protected amount, you can assert a further exemption by contacting the creditor, completing an exemption form with the court, or working with a legal aid attorney. One detail most people miss: direct deposit matters. If you receive benefits by paper check and deposit them yourself, the automatic two-month lookback may not identify the funds as protected. Direct deposit creates the electronic trail the bank’s system uses. Joint Accounts Put Your Money at Risk ... The law generally presumes each co-owner has equal rights to every dollar in the account, so a creditor pursuing one account holder can freeze the entire balance. .. A non-debtor co-owner can fight this, but must act fast. The garnishment notice includes a hearing date, and requesting that hearing in writing before the deadline is critical. ... Miss the hearing and the court can release the entire balance to the creditor.}} === ''The Chickenshit Club'' === The interview mentioned potential fines of over $360,000 per violation, mentioned by Reitman (2026, p. 60). A web search for documentation of such fines identified Moss (2026), "TD Bank to Pay Record $3 Billion for [[w:Bank Secrecy Act|BSA]]/AML Violations". However, no mention was found of fines "over $360,000 per violation." $3 billion may sound like a lot of money but may be a minor cost of doing business for a large organization like [[w:TD Bank (United States)|TD Bank]]. The article by Moss (2026) reported that, {{quote| senior management at TD Bank knew that its failure to adequately support [[w:Anti–money laundering|AML]] compliance created backlogs that allowed illicit transactions to continue to flow through the bank. ... Notably, the bank: ... Allowed trillions of dollars of domestic [[w:ACH Network|ACH]], remote deposit capture, and peer-to-peer (P2P) transactions to go unmonitored for over a decade." It's not immediately obvious how much money TD Bank made from having "allowed trillions of dollars of ... transactions to go unmonitored". Might $3 billion have been a small percentage of what they made violating the law? The fact that the settlement did not include prison time for any "senior management" is consistent with the discussion in "[[Dean Starkman and the watchdog that didn't bark]]" of "Whitewashing corporate crime ... described by Eisinger (2017) :[''The chickenshit club : why the Justice Department fails to prosecute executives'']. :''When these deals are announced with the Justice Department, invariably the shares of the company go up, not down.'' (emphasis added)}} == Notes == {{reflist}} == Bibliography == * <!--Jesse Eisinger (2017) The chickenshit club : why the Justice Department fails to prosecute executives-->{{cite Q|Q134599351}} * <!--Ashley Eneriz (2026-09-25) "Frozen Bank Account: Common Causes and Steps to Unfreeze"-->{{cite Q|Q141599984}} * <!--fedlaws.org (2026-09-23) "Why Do Banks Freeze Accounts? Triggers, Exemptions, and Fixes-->{{cite Q|Q141599719}} * <!--Valerie Moss (2024-10-17) "TD Bank to Pay Record $3 Billion for BSA/AML Violations"-->{{cite Q|Q141600174}} * <!--Rainey Reitman (2026-04-07) Transaction Denied: Big Finance's Power to Punish Speech-->{{cite Q|Q141526890}} [[Category:Media]] [[Category:News]] [[Category:Democracy]] [[Category:Politics]] [[Category:Political economy]] [[Category:Freedom of speech]] [[Category:Finance]] [[Category:Economics and Personal Finance]] [[Category:Media reform to improve democracy]] <!--list of categories https://en.wikiversity.org/wiki/Wikiversity:Category_Review [[Wikiversity:Category Review]]--> p1932kgrytjjg9kz39dyiva8hfttrsu 0 332288 2835228 2026-09-30T22:03:48Z Scogdill 1331941 Created page with "=Event= ==Overview== ==Logistics== * ===Staff and Vendors=== * ==Related Events== * Reception * Honeymoon ==Who Was Present== ===Bride and Bridesmaids=== ====Bride==== ====Bridesmaids==== ====Pages==== ===Groom and Best Man=== ===People Who Attended=== # ==What People Wore== # ==Gifts== ===Unusual or Interesting Gifts=== ==Anthology== == Notes and Questions == # ==References== {{reflist}}" 2835228 wikitext text/x-wiki =Event= ==Overview== ==Logistics== * ===Staff and Vendors=== * ==Related Events== * Reception * Honeymoon ==Who Was Present== ===Bride and Bridesmaids=== ====Bride==== ====Bridesmaids==== ====Pages==== ===Groom and Best Man=== ===People Who Attended=== # ==What People Wore== # ==Gifts== ===Unusual or Interesting Gifts=== ==Anthology== == Notes and Questions == # ==References== {{reflist}} pagr46ahbqks0052eepfsoe542bxmox 2835230 2835228 2026-09-30T22:19:13Z Scogdill 1331941 2835230 wikitext text/x-wiki = Wedding of Miss Clarita de Murietta and the Duc de Santona = ==Overview== This wedding is between Spanish Catholics, but it took place in England. ==Logistics== * ===Staff and Vendors=== * ==Related Events== * Reception * Honeymoon ==Who Was Present== ===Bride and Bridesmaids=== ====Bride==== ====Bridesmaids==== ====Pages==== ===Groom and Best Man=== ===People Who Attended=== # The Prince of Wales ==What People Wore== # ==Gifts== ===Unusual or Interesting Gifts=== ==Anthology== The Marques and Marquesa of Santurce hosted a house party and then the reception for the wedding of their daughter, Miss Clarita de Murietta, and the Duc de Santona. ==== The House Party ==== This ''Bedfordshire Mercury'' report includes both the house party and some information about the wedding as well. Given the focus on [[Social Victorians/People/Louisa Montagu Cavendish|Louisa, Duchess of Manchester]] and her daughter-in-law [[Social Victorians/People/Mandeville|Consuelo, Lady Mandeville]], the ''Bedfordshire Mercury'' looks like a paper local to them.<blockquote>The Duchess of Manchester, Vicountess Mandeville and Lord Kimbolton were among the guests entertained by the Marques and Marquesa de Santurce at their residence, Carlton House-terrace, London, on the occasion of the marriage of their younger daughter, Mdlle. Clarita de Murrieta, with the Due de Santona, last Wednesday. The ceremony took place at Brompton Oratory, where the floral  decorations were most elaborate, whole trees of white lilac and camelias, besides a profusion of arums and lilies of the valley, being artistically arranged about the sanctuary and in adjacent chapels. An orchestra of nearly 40 string instruments, with the organ, performed for three-quarters of hour before the time fixed, 11.30. The bridesmaids were Mdlle. de Mitjans (sister of the bridegroom), the Hon. Muriel and Hon. Marie Brassey, Miss Joan Nevill, Miss Violet  Gathorne-Hardy, and Miss Constance Barron. Mr Francis de Murrieta, cousin of the bride, was best man. The Bishop of Southwark performed the nuptial rite, and afterwards said Mass, assisted by the Rev. W. F. Gordon, and other Fathers; Gounod’s "Messe Solennelle" was sung by nearly 40 voices, and his "Ave Maria," adapted from Bach, by a Master Hawkins. The Prince of Wales, the Duchess of Leinster and Lady Helen Duncombe, Viscountess Hood, Lady Frances and Lady Clementine Pratt, the Hon. C. R. and Mrs Spencer, Mr Grenfell, Mr and Mrs Hulse, &c., were also of the bridal company. The Duchess of Manchester wore at the church a long velvet mantle trimmed with sable, which almost concealed her grey dress. The donors of wedding presents included the Empress Eugénie, the Prince and Princess of Wales, the Duke and (Princess Louise) Duchess of Fife, Mr Alfred Rothschild, &c. The Duchess of Manchester gave the bride a pair of silver-gilt-topped scent bottles, and Lady Mandeville a small green leather travelling bag. The Duc de Santona and his bride left town for Wadhurst Park.<ref>"Kimbolton." ''Bedfordshire Mercury'' 1 February 1890, Saturday: 8 [of 8], Col. 3b [of 6]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0001290%2F18900201&page=8&article=101&stringtohighlight=mandeville+viscount. Same print title and p.</ref></blockquote> ==== The Wedding ==== This report from the ''The Sussex Express, Surrey Standard, Weald of Kent Mail, Hants and County Advertiser'' took up about 2 1/3 full columns:<blockquote>The marriage was solemnised, on Wednesday, at Brompton Oratory, with imposing ceremonial, and under most auspicious circumstances, of Juan Manuel Mitjans, Duque de Santona, a grandee of Spain, to Clarita de Murrieta, younger daughter of the Marques and Marquesa de Santurce, of Wadhurst Park, Sussex, and 18, Carlton House-terrace. The [happy event?] we now record not only attracted a numerous and brilliant congregation of the fashionable world to the service at the Oratory and the subsequent festivities, but was [invested?] with considerable interest to the wide borders of Kent and Sussex, from the sea to beyond the Weald, the bride being connected by the marriage of her sister to Lord William Nevill, last year, with the noble local families of Nevill, Gathorne-Hardy, Brassey, and Egerton. Her father, too, the Marques de Santurce, is now quite a Sussex man, having for years past been seated at Wadhurst Park. The weather was all that could desired of a winter's day, presenting a bright and cheerful contrast to the storms which have lately proved so destructive and depressing. That is to say, the wind had moderated, the sun shone brightly, and the air was tinged with exhiliarating [sic] crispness. As early ten o'clock — an hour and half before the ceremony — the holders of tickets for admission to the sacred building began to arrive, and crowd to assemble round the gateways. At eleven every seat, except those reserved for the wedding party, was oocupied, and from that time till nearly one o’clock a long line of carriages occupied both sides of the broad roadway from the Oratory to beyond South Kensington Museum. The interior of the church, long before the arrival of the bride, presented a brilliant appearance. Rays of sunshine from the clerestory windows brought into relief the beautiful floral decorations within the sanctuary. Groups tall palms and camellia trees in blooms, interspersed with white lilac and arum lilies, were placed in front of the chancel, while on the fine marble balustrade were large brass bowls filled with white azaleas, lilies of the valley, and roses. Between the massive columns separating the transepts from the aisles, were also palms and ferns interspersed with rose-tinted camellias and other flowers. The altars were also richly decorated. On the high altar were eight large bouquets of choice white exotics. The altar of Our Lady in the East transept was decked in bouquets of white, orange, and a pale shade of yellow, while that of St. Philip the west transept, was arranged with palms and scarlet and white blooms. THE CEREMONY. The choral part of the service commenced at eleven o’clock, when the choir, numbering about one hundred performers, including trumpeters and stringed instrumentalists, commenced a programme of grand sacred music. The Duke de Santona, who was attended by the bride’s cousin, Mr. Francis Murrieta, as best man, arrived several minutes before the half-hour, and awaited, at a ''prie-Dieu'' placed in front of the chancel balustrades, the coming of his ''fiance'' [sic]. The bridesmaids reached the Oratory just afterwards in readiness to take their part in the bridal procession. They were Miss Marie Mitjans (sister of the bridegroom), Miss Joan Marion Nevill (daughter of Lord Henry Nevill), Miss Violet Gathorne-Hardy (daughter of the Hon. C. C. and Lady Cicely Louisa Gathorne-Hardy), Miss Barron (daughter of Capt. and Mrs. Barron), the Hon. Muriel Agnes Brassey,  and the Hon. Marie Adelaide Brassey (daughters of Lord Brassey, of Normanhurst). Then came the Prince of Wales, who had journeyed from Sandringham specially for the occasion. His Royal Highness, attended by  Colonel Teesdale, was conducted to a seat in front of the sanctuary. The Bishop of Southwark, the Rev. Canon Searle (of Tunbridge Wells), the Rev. Father Gordon, of the Oratory, who performed the ceremony, entered the church in procession, with their attendants, from the north door of the west transept, and took their position in front of the high altar. The bride was accompanied to church by her mother, and the Marques de Santurce received his daughter at the main entrance to the nave. The bridal procession was at once formed. The fair and stately bride — fairer than most of the daughters of the sunny south — was escorted by her father through the nave and transepts to the ''prie-Dieu'' in front of the entrance to the sanctuary, the bridesmaids following, and the instrumental part of the choir performing the spirited bridal match [sic] from Lohengrin. During the first few minutes of the holy ceremony, the bride and bridegroom  remained in prayer in front of the chancel. They were then conducted to the altar, before which, the marriage service was celebrated. It occupied but a few minutes[.] The clergy, the bride and bridegroom, the Prince of Wales, the parents of the happy pair, and several of their nearest relatives repaired to the vestry to sign the register. The Prince gave his arm to the Marquesa de Santurce, and signed the register as one of the witnesses. On returning to the church Nuptial Mass was celebrated, and the whole service which occupied less than an hour, was brought to a conclusion by the Bishop bestowing the blessing of the Church upon the young couple. The music was as follows:— Before service, slow movement of minuet and trio for Italian Symphony (Mendelssohn) and Allegretto from 8th Symphony (Beethoven). As the bride entered the church, "Bridal march" from Lohengrin. While the register was signed, offertoire from "Messe Solennelle." During Mass, Gounod's "Mess Solennelle," offertory, Gounod's "Ave Maria," solo by Master Hawkins. Finale, Mendelssohn’s "Wedding March." THE DRESSES OF THE LADIES. The Bride. — The bride’s dress was of rich white Venetian brocade, with a very long court train; the front was bordered round the hem with fringes and bouquets of orange blossom, a garland of the same being arranged on the left side. The bodice had a high collar of delicate lace and a softly-draped fichu of lace and fine muslin. She wore small crown of orange-flowers and a tulle veil fastened to the hair with diamond ornaments and carried a lovely bouquet of exotics. The Bridesmaids. — The bridesmaids’ pretty costumes were of soft cream crepon, with sleeves and vests of apple green velvet; the straight skirts were edged with a single row of gold braid; and they wore sashes of pale mauve moiré, the ends of which fell from the waist in front to the feet. The two elder bridesmaids wore small bonnets of green velvet and gold braid, and the other four picturesque hats match, trimmed with the braid and several green ostrich feathers. The bridegroom's gift to each bridesmaid was also worn. It was a very handsome brooch formed of a horseshoe in diamonds and sapphires pierced by a diamond arrow; in the centre of the horseshoe were the initials "J. C." in diamonds, with a ducal coronet above in rubies and diamonds. The bridesmaids carried bouquets of lilies of the valley and green orchids, tied with mauve and green ribbons. The Bride’s Mother. — The Marquesa de Santurce's costume was entirely of dark reseda velvet, with the exception of the sleeves, which were of embossed silk with a design of foliage delicately outlined in gold. The straight collar was also of embossed brocade. The Marquesa’s bonnet was composed of two wing-like arrangements of reseda-green lisse, wrought with lines of gold, placed eave-like over the wearer's dark hair. The crown, a very tiny one, almost hidden by the wings, was of velvet embroidered in gold. The bouquet carried was an exquisite combination of white orchids, Maréchal Niel roses, and mimosa. It was tied with ribbon of the same colour as the costume. The Bridegroom's Mother. — The Marquesa de Manzanedo, the bridegroom’s mother, wore train of almost courtly proportions. It, as well as the bodice, was of dark heliotrope velvet. The bodice was made with puffed sleeves, very high on the shoulders, and a Medici collar This was faced, and the bodice bordered, with Russian sable. The skirt was of pearl-coloured brocade, backed with plaler heliotrope. It was deeply flounced with dark rich sable tail, and over it at one side a scarf of priceless Spanish lace was draped. A bonnet of lisse and velvet in corresponding tones of heliotrope colour was worn. The Marquesa carried a magnificent bouquet of orchids of the same shade her costume, arranged with varied foliage and tied with dark heliotrope ribbon. The Bridegroom's Sister.—The Duquesa de Lecera, the bridegroom's sister, was attired in a striking costume of pale pink satin striped with black. It was princess in form the stripes symetrically converging towards the waist. The skirt was bordered with soft ruche of pale pink chiffon. A pretty little bonnet composed of lisse and velvet matched the dress, and the Duquesa carried a bouquet of pale pink carnations and orchids. The Bride’s Sister.—Lady William Nevill’s dress was of Sicilienne and velvet. The form was of the polonaise order and the colour serpent-green. The skirt was quite plainly arranged, and entirely of Sicilienne. Lady William’s bonnet was of velvet, a ruche of pale pink China crêpe showing above the hair. Pink and green ospreys were placed at one side. Her bouquet was mass of pink blossoms arranged with fern fronds, and tied with serpent-green ribbon. Lady Cicely Gathorne-Hardy's dress was a pretty combination of electric-blue velvet and cashmere. There was soft vest of white China crêpe. The bonnet was of velvet, similar that of the dress; a grey and white bird was coquettishly placed at one side. Lady Cicely’s bouquet was of white roses and pink carnations. Lady Henry Nevill’s dress was made of light cloth of a pale tone of fawn-colour striped with narrow lines of brown. The sleeves and top portion of the bodice were of violet velvet. pointed panel of similar velvet showed at either side of the skirt. The cloth was drawn in folds  over the shoulders, and was caught under folds of velvet at the waist, showing deep V-shaped points of the bright-hued velvet in front and at the back. A bonnet of fawn-coloured silken gauze was covered with violet velvet pansies laid flatly on the crown. Lady Henry's bouquet was of shaded violets. Lady George Nevill wore a long mantle of dark-brown cloth broché with red. The sleeves, made high at shoulders were of dark autumnal-brown velvet, and the bonnet was of velvet, of the same colour, amid loops of which dark-red plumaged birds were nestled. Lady Idina Brassey's costume of ruby velvet was very effective, being flounced and bordered with dark fur. The hat was of felt, matching the dress in colour, and its flat crown was surrounded with dark red ostrich feathers. Lady Rose Leigh was quietly dressed in a neat tailor-made tweed gown, dark blue in colour, intercepted by narrow lines of white. A hat of dark blue felt, bordered with cock’s feathers twisted into a curl over the flat crown, looked appropriate to the studied simplicity of the dress. Lady Dorothy Nevill was attired in a long mantle of wall-flower red plush trimmed with bronze passementerie. Her headgear was a neat, closely-fitting bonnet, matching her mantle in color. The Duchess of Manchester wore a dress of silver-grey silk brocaded with satin; a section of plain satin, arranged in straight pleats, formed the back. Her Grace's mantle was of velvet — of so dark a shade of [Col. 1c–2a] myrtle green as to appear black in the shadow — and it was trimmed with lines of jet embroidery. The bonnet worn by the Duchess was of sinrlar velvet, with a spray of jet across the front. The Duchess of Leinster, who was accompanied by her sister, Lady Helen Duncombe, was attired in golden brown cloth trimmed with a design of foliage in velvet, applied to the surface of the cloth, with silk embroidery. Her Grace’s coat was of embossed silk of a delicate shade of stone colour slightly wrought with gold. The pretty but very small hat worn by the duchess was of brown felt, and her Grace's boa of ostrich feathers shaded from brown to pale stone colour. Lady Helen’s dress was of dark reddish brown woollen material, simple in form but of perfect style. Her hat was also of felt, matching her costume in colour. Lady Algernon Gordon Lennox. — A strikingly-handsome costume was that worn by Lady Algernon Gordon-Lennox. It was of bright soft-red velvet trimmed with bands of red-gold embroidery. Her bonnet was a very small one of red velvet, with a spray of ferns  simulated in jet across the front. Lady Algernon wore a long boa of sable-tail. The Dowager Countess Airlie. — Was costumed in her invariable sable robes of almost cloister-like severity, which so admirably suit her distinguished figure and beautiful face. Lady Grisel [Griselda?] Ogilvy. — Wore a black skirt, with a broad sash of pale blue moire. Her cape was of fine steel beadwork, and she wore a Henry VIII. hat of black velvet, with a group of pale blue feathers at one side. Mrs. Ronalds. — Wore a dress and mantle of black velvet bordered with sable tail, and a bonnet ''en suite''. Her daughter, Mrs. Ritchie. — Was gowned in willow-green Royal silk, and wore a bonnet of green lisse and mantle made entirely of jet beadwork. THE WEDDING GUESTS. The company present the wedding ceremony, and afterwards at the breakfast at Carlton House-terrace, included, in addition to the Prince of Wales, the Marquesa de Manzanedo and Mdlle. Maria Mitjans, the Duque and Duquesa de Lecera, the Duchess of Leinster and Lady Helen Duncombe, the Duchess of Manchester, the Dowager Countess of Airlie and Lady Griselda Ogilvy, [[Social Victorians/People/Mandeville|Viscountess Mandeville and Lord Kimbolton]], Viscountess Hood, Lord and Lady Brooke and Lady Sybil St. Clair-Erskine, Lord and Lady William Nevill, Lord Brassey, Lord and Lady George Nevill, Hon. Thomas and Lady Idina Brassey, Lord and Lady Henry Nevill, the Bishop of Southwark, Lady Frances Pratt and Lady Clementine Pratt, Lady Lister-Kaye, Lady Dorothy Nevill, Lady Cicely Gathorne-Hardy, Lady Sandhurst, Lady Alice Morland, Lord Richard Nevill, Sir Frederick and Lady Milner, Hon. C. N. Spencer, M.P., and Mrs. Spencer, Mr. and Lady Margaret Douglas, Hon. Humphrey Sturt, Sir Oscar Clayton, Lady Constance Leslie and Miss Leslie, Sir William Gordon-Cumming, Hon. Mrs. Agar-Ellis and Miss Ellis, Mons. and Madame Escandon and Mdlle. Escandon, M. Calderon, M. Errazu, M. Galintz, Mr. Frank Lee, Major Swaine, Mr. and Mrs. Granville Ward, M. de Soveral, Mr. W. H. Mitchell, the Rev. Mr. Palmer, Mr. C. de Murrieta, Mr. A. de Murrieta, Mr. Mariano de Murrieta, Mr. C. J. de Murrieta, Mr. and Mrs. Barron, Mr. Hatch, Mr. Reginald Ronalds, Mrs.  Temple Soanes, Dr. and Mrs. Robson Roose, Mr. and Mrs M. Van Raalte, Mr. Grenfell, Mrs. Bischoffsheim, Mr. Hulse, M.P., and Mrs. Hulse, Mr. Wood, Dr. White, Mrs. Ronalds and Mrs. Ritchie, Mr. Leo Schuster, Mrs. Ince Anderton, Mr. Eldrid, Mr. and Mrs. Hammond, Mr. and Mrs. E. H. Eldrid, the Rev. J. S. Welby, Mr. F. O. Smithers, Mr. and Mrs. Moreton Frewen, Mr. and Mrs. Granville Ward, Mrs. and Miss Silvertop, Mr. Gerald Paget, Mr. and Mrs. Hwfa Williams, Mr. Charles Van Raalte, Mr. Albert Stopford, Hon. Mrs. Vaughan, Miss E. Vaughan, Miss Townshend, Mrs. Coupland, Mrs. and Miss Leigh, Mr. and Mrs. F. V. Williams, and the Spanish Consul-General. THE WEDDING BREAKFAST Was served at the residence of the parents of the bride, 18, Carlton House-terrace. The Prince of Wales arrived there soon after the bride and bridegroom, when the Hungarian band, stationed in the corridor at the top of the grand staircase, played the "National anthem." Here, again, the floral decorations were superb. The table at which the Prince of Wales sat, with the bride and groom and their immediate relatives, was a mass of white and gold. The bridal colouring was supplied in the first instance by the colossal frosted structure of the cake, flanked by crescents of white orchids, orange flower, and branches of orange trees, bearing double burdens of fruit and bloom. The other six tables in the dining-room were decorated with white and the palest of blush pink, a favourite colour with the bride. The principal drawing-room was made to appear almost tropical with gorgeously-hued orchids and foliage, combining tints of vivid scarlet and bright yellow, with hundreds of shades of tender green. A stand of white lilies and pink roses placed in the entrance hall was much and deservedly admired. Nor were the charms of a second drawing-room, adorned with dozens upon dozens of double and single daffodils, passed over in silence. In the ball-room where the wedding presents were "on view," was an atmosphere laden with the subtle sweetness of fair white lilies. everywhere [sic] there were flowers, and the effect, combined with that of the brilliant sunshine which crowned the day, was to banish the recollection of January and suggest a vision of June. About three o’clock the Duque de Santona and his bride left by special train for Wadhurst Park, where they will pass the early days of the honeymoon. The bride went away in a costume of grey velvet, of a delicate shade, draped with ''Sicilienne'', and trimmed with rich steel passementerie; a broad band  of grey velvet edged the skirt, and she wore a jacket and hat to match, and sable boa and muff. THE WEDDING PRESENTS Were displayed in the ball-room, at the house of the Marquess De Santurce in Carlton House Terrace. The jewellery was simply magnificent, and the others were also costly and elegant. The presents to bride and bridegroom numbered about 500, including the following:—<ref name=":2">"Marriage of Miss de Murrieta to the Duke of Santona." ''Sussex Express'' 1 February 1890, Saturday: 7 [of 12], Cols. 1a–3a. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0000654%2F18900201&page=7&article=136&stringtohighlight=mandeville+viscount. Print title: ''The Sussex Express, Surrey Standard, Weald of Kent Mail, Hants and County Advertiser'', p. 7.</ref> [set as unordered list, originally set as separate paragraphs] TO THE BRIDE * The P<small>RINCE</small> and P<small>RINCESS</small> of W<small>ALES</small>, moonstone heart brooch, set with rubies and diamonds. * Princess L<small>OUISE</small>, Duchess of Fife, and the Duke of F<small>IFE</small>, a set of silver salt-cellars. * The Empress E<small>UGENIE</small>, a large silver mirror. * The B<small>RIDEGROOM</small>, a magnificent sapphire and diamond necklace, a sapphire and diamond bracelet, ruby and diamond ring, pearl double-heart brooch, diamond pin, diamond and pearl brooch, gold and pearl studs, and gold-handled hunting crop. * The Marquess and Marquesa <small>DE</small> S<small>ANTRUCE</small> [sic], a magnificent diamond tiara. * Marquesa <small>DE</small> S<small>ANTURCE</small>, diamond half-hoop ring. * M. M<small>ITJANS</small>, father of the bridgegroom, three rows of large pearls, with diamond and emerald clasp. * Marquesa De M<small>ANZANEDO</small>, mother of bridgeroom [sic], ruby and diamond cluster necklace. * Lord and Lady W<small>ILLIAM</small> N<small>EVILL</small>, handsome dressing bag with tortoiseshell and gold fittings, and enamel and diamond watch bracelet. * Mr. C<small>HRISTOBAL</small> and Mr. A<small>DRIANO DE</small> M<small>URRIETA</small>, diamond aigrette, and two pairs of carriage horses. * Mr. M<small>URIANO DE</small> M<small>URRIETA</small>, silver-gilt tea service and tray, three silver-gilt candelabras, and set of silver-gilt dessert plates. * The Duc and Duchesse <small>DE</small> V<small>ISTAHAMOSA</small>, complete set of silver-gilt dessert forks, knives, and spoons, and four pairs of old English silver candlesticks. * Mr. F<small>RANCIS</small> and Mr. C. J. <small>DE</small> M<small>URRIETA</small>, pair of large silver-gilt repoussé dishes. * Marques <small>DE LA</small> T<small>ORREVILLE</small>, diamond double-heart  brooch. * M. C<small>ALDERON</small>, set of diamond hair pins. * Marchioness of A<small>BERGAVENNY</small>, black point lace and tortoiseshell fan, with monogram in rubies and diamonds. * Duke and Duchess of N<small>EWCASTLE</small>, diamond and emerald watch-bracelet. * Mr. A<small>LFRED DE</small> R<small>OTHSCHILD</small>, diamond and pearl bracelet. * Lord and Lady S<small>ANDHURST</small>, gold "1890" sleevelinks. * Mdlle. M<small>ARIA</small> M<small>ITJANS</small>, large carbuncle and diamond pendant. * The S<small>PANISH</small> A<small>MBASSADOR</small>, six silver coffee cups. * Duchess of M<small>ANCHESTER</small>, pair of silver-gilt-topped scent bottles. * Duchess of L<small>EINSTER</small>, old china box. * Hon. R<small>OBERT</small> and Mrs. S<small>PENCER</small>, diamond pin. * Marquis of A<small>BERGAVENNY</small>, writing set and candlestick. * Countess of D<small>ENBIGH</small>, embroidered silk blotting book. * Lady A<small>LICE</small> M<small>ORLAND</small>, silver vase. * Lord R<small>ICHARD</small> N<small>EVILL</small>, pigskin luncheon bag with complete silver fittings. * Hon. T<small>HOMAS</small> and Lady I<small>DINA</small> B<small>RASSEY</small>, leather carriage card case, with gold mountings and monogram. * Lord and Lady B<small>ROOKE</small>, Dutch silver ornament. * Viscount and Lady V<small>IOLET</small> D<small>ANGAN</small>, old painted snuff-box. * Sir O<small>SCAR</small> C<small>LAYTON</small>, pair of silver ash trays. * Sir W<small>ILLIAM</small> G<small>ORDON</small> C<small>UMMING</small>, silver-headed scent bottle. * Viscountess M<small>ANDEVILLE</small>, small green leather travelling bag. * Mrs. C<small>OUPLAND</small>, silver crucifix. * Canon S<small>EARLE</small>, benetier. * Lady B<small>ROUGHAM</small> and V<small>AUX</small>, old gold-mounted scent  bottle. * Lady C<small>LIFFORD</small> and Miss T<small>OWNELEY</small>, silver looking-glass. * Lord A<small>SHBURTON</small>, silver box. * Lady A<small>LGERNON</small> G<small>ORDON</small>-L<small>ENNOX</small>, inlaid tortoiseshell box. * Dowager Duchess of N<small>EWCASTLE</small>, silver tray. * Lord and Lady C<small>HARLES</small> B<small>ERESFORD</small>, small Louis XVI table. * Sir F<small>REDERICK</small> and Lady M<small>ILNER</small>, silver tray. * Sir Bach Cunard, scent bottle with gold top set with diamonds. * Mrs. G. C<small>AVENDISH</small>-B<small>ENTINCK</small>, pair of small old silver vases. * Mr. and Mrs. E<small>DWARD</small> S<small>ASSOON</small>, Sevres china ink-stand. * Mr. J. B. and Lady R<small>OSE</small> L<small>EIGH</small>, Chippendale table. * Lord and Lady H<small>ENRY</small> N<small>EVILL</small>, complete silver tea set. * Mr. H<small>ORACE</small> F<small>ARQUHAR</small>, two girandoles. * Colonel R<small>ALPH</small> V<small>IVIAN</small>, umbrella with gold handle. * T<small>HE</small> S<small>ERVANTS AT</small> W<small>ADHURST</small> PA<small>RK AND</small> 18, C<small>ARLTON</small> H<small>OUSE-TERRACE</small>, large silver salver. * T<small>HE</small> W<small>ADHURST</small> T<small>ENANTS AND</small> T<small>RADESMEN</small>, large silver cup. * W<small>ADHURST</small> P<small>ARK</small> S<small>TABLEMEN</small>, driving whip and hunting crop. * Marquis C<small>AMDEN</small> and Lady C<small>LEMENTINE</small> P<small>RATT</small>, silver box. * Mr. R<small>ICARDO DE LA</small> Q<small>UININA</small>, Minton china tea and coffee set and dinner service. * Mr. H<small>EREDIM</small>, diamond and enamel watch bracelet. * Duque and Duquesa <small>DE</small> L<small>ACERA</small>, diamond and sapphire brooch. * Mr. and Mrs. D. Y<small>BARROMDO</small>, large silver bowl. [Col. 2c–3a] * Mr. F. V. and Miss W<small>ILLIAMS</small>, four silver-gilt salt cellars. * Miss L<small>EIGH</small>, leather letter holders. * Duqe and Duquesa <small>DE</small> F<small>ERNAN</small>-N<small>UNEZ</small>, old Spanish fan. * Duque and Duquesa <small>DE</small> A<small>LBA</small>, old Spanish fan. * Mrs. and the Misses C<small>ARROLL</small>, silver hand-glass. * Lord George N<small>EVILL</small>, hunting crop. * Lady George N<small>EVILL</small>, silver photo frame. TO THE BRIDEGROOM. * The Bride, turquoise and diamond pin, and ruby and diamond ring, and Cabochen sapphire and diamond sleeve links. * The Marquesa <small>DE</small> M<small>ANZANEDO</small>, emerald and diamond  pin. * The Marquesa <small>DE</small> S<small>ANTURCE</small>, a brougham, sapphire and diamond pin, and ruby and diamond horseshoe pin. * Mr. C. and Mr. A. <small>DE</small> M<small>URRIETA</small>, pair of guns. * Lord and Lady W<small>ILLIAM</small> N<small>EVILL</small>, set of crystal and silver liqueur cups and bottles on crystal and silver tray. * Mr. F<small>RANCIS DE</small> M<small>URRIETA</small>, silver looking-glass. * Mr. C. J. <small>DE</small> M<small>URRIETA</small>, pearl pin. * Count T<small>ORRE</small>-A<small>RIAS</small>, silver-mounted paper knife. * Comte <small>DE LA</small> P<small>ATELLA</small>, pearl pin.   * Count <small>DE</small> B<small>ENATUA</small>, Rahi [?] cart. * The Duque and Duquesa <small>DE</small> L<small>ECERA</small>, gold links and studs. * Duc <small>DE</small> A<small>LBA</small>, phaeton. * Mr. J. G<small>RENFELL</small>, silver cigarette case. * Mr. T<small>HOMAS</small> W<small>OOD</small>, umbrella and cigar case. * Lord R<small>ICHARD</small> N<small>EVILL</small>, leather box, containing cards, counters, &c. * Mr. P. <small>DE</small> G<small>ALINDEZ</small>, silver cigar case. * Madame <small>DE LOS</small> H<small>EROS</small>, tea basket. * Duchesse <small>DE</small> A<small>LIAGA</small>, set of books. * M. and Madame E<small>SCAUDON</small>, sapphire and diamond pin. * Count E<small>STRADOS</small>, gold match-box. * M. R<small>AMON DE</small> E<small>RRAZU</small>, silver-fitted dressing bag. * M. L<small>UTS DE</small> E<small>RRAZU</small>, diamond pin. * Sir W<small>ILLIAM</small> G<small>ORDON</small>-C<small>UMMING</small>, old silver box. * The S<small>ERVANTS</small> at Wadhurst and 18, Carlton House-terrace, pair of silver-mounted riding whips.<ref name=":2" /> </blockquote>This report from the ''Tunbridge Wells Journal'' is a good example of a regional paper covering an event from a local perspective.<blockquote>On Wednesday morning, the Brompton Oratory was crowded to witness the nuptials of Miss Clarita de Murietta, daughter of the Marques and Marquesa de Santurce, of Wadhurst Park, Sussex, and Carlton House terrace, and the Duc de Santona. The event was invested with considerable interest to Kent and Sussex, the bride being connected by the marriage of her sister to Lord W. Nevill, with the families of Nevill, Gathorne-Hardy, Brassey, and Egerton. The Oratory was beautifully decorated with palms and ferns and white flowers. The service was fully choral and during the celebration of the nuptial mass selected music was rendered. The Prince of Wales, attended by Colonel Teesdale, was present. The Bishop or Southwark, assisted by Father Gordon and the Fathers of the Oratory, officiated. The bridge [sic] was conducted to the high altar by her father, the Marques de Santurce, who gave her away. A cousin of the bride, Mr Francis de Murietta, accompanied the Duc de Santona as best man. The bridesmaids wore dresses of soft cream crêpon, with sleeves and vests in vert pomme velvet edged with gold braid, straight skirts edged with the same, and slashes of pale mauve moiré. Two of the bridesmaids wore bonnets and the other four hats of green velvet  ornamented with gold braid and green ostrich feathers. The bridegroom's presents were a diamond arrow piercing a diamond and sapphire horseshoe, surmounted by ducal coronet in rubies and diamonds, and a "good-year" bouquet of lilies of the valley and green orchids tied with mauve streamers. The bridesmaids were Mdlle. Mara [?] Mitzans [s/b Mitjans], slater of the bridegroom, Miss Constance Barrow, daughter of Captain and Mrs Barrow, Miss Ivan Marion Nevill, daughter of Lord and Lady H. G. R. Nevill, Miss Violet Gathorne-Hardy, daughter of the Hon. C. G. and Lady Cicely Louisa Gathorne-Hardy, the Hon. Muriel Agnes Brassey, and the Hon. Marie Adelaide Brassey, daughters of Lord Brassey. The bride's dress was of rich white Venetian brocade, with long train, the front being bordered with fringes and bouquets of orange blossoms. The bodice had a high collar of lace, and a fichu of lace and fine muslin, softly draped. She wore a small crown of real orange blossoms, surmounted by a fine tulle veil. After the ceremony, the wedding party proceeded to 18, Carlton House terrace, the town residence of the Marques and Marquisa de Santurce, where a déjeuner and reception were held, the Hungarian band playing selected airs on the grand staircase. The honeymoon is to be spent at Wadhurst Park. The bride's going away dress was of a delicate shade of grey velvet, draped with Siciliéune, and trimmed with rich steel passementerie, with hat to match. The following is a list of the more important presents:— [Col. 6b–c] To the Bride. —<ref name=":1">"Marriage of Miss de Murietta." ''Tunbridge Wells Journal'' 6 February 1890, Thursday: 2 [of 8], Col. 6b–c [of 6]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0004632%2F18900206&page=2&article=036&stringtohighlight=mandeville+viscount. Same print title and p.</ref> [gifts list below set as unordered list to make it easier to read] * From the Prince and Princess of Wales, moonstone heart brooch, set with rubies and diamonds; * Princess Louise, Duchess of Fife, and the Duke of Fife, a set of silver-gilt salt cellars; * the Empress Eugénie, a large silver mirror; * the bridegroom, a magnificent sapphire and diamond necklace, a sapphire and diamond bracelet, ruby and diamond ring, pearl double-heart brooch, diamond pin, diamond and pearl brooch, gold and pearl studs, and gold-handled hunting crop; * the Marques and Marquesa de Santurce, a magnificent diamond tiara; * Marquesa de Santurce, diamond half-loop ring; * M. Mitzans, father of the bridegroom, three rows of large pearls, with diamond and emerald clasp; * Marquesa de Manzanedo, mother of bridegroom, ruby and diamond cluster necklace; * Lord and Lady William Nevill, handsome dressing bag with tortoiseshell and gold fittings, and enamel and diamond watch bracelet; * Mr Christobal and Mr Adriano de Murietta, diamond aigrette, and two pairs of carriage horses; * Mr Muriano de Murietta, silver-gilt tea service and tray, three sliver-gilt candelabras, and set of silver-gilt dessert plates; * the Duc and Duchesse de Vistahamosa, complete set of silver-gilt dessert forks, knives and spoons, and four pairs of old English silver candlesticks; * Mr Francis and Mr C. J. de Murietta, pair of large silver-gilt repoussé dishes; * Marquess de Ia Torreville, diamond double-heart brooch; * M. Calderon, set of diamond hairpins; * Marchioness of Abergavenny, black point lace and tortoiseshell fan, with monogram in rubies and diamonds; * Duke and Duchess of Newcastle, diamond and emerald watch-bracelet; * Mr Alfred de Rothschild, diamond and pearl bracelet; * Lord and Lady Sandhurst, gold "1890" sleeve links; * Mdlle. Maria Mitzans, large carbuncle and diamond pendant; * the Spanish Ambassador, six sliver coffee cups; * Duchess of Manchester, pair of silver-gilt-topped scent bottles; * Duchess of Leinster, old china box; * Hon. Hobert and Mrs Spencer, diamond pin; * Marquess of Abergavenny, writing set and candlestick; * Countess of Denbigh, embroidered silk blotting book; * Lady Alice Morland, silver vase; * Lord Richard Nevill, pigskin luncheon bag, with complete silver fittings; * Hon. Tomas and Lady Idina Brassey, leather carriage card-case with gold mountings and monogram; * Lord and Lady Brooke, Dutch silver ornament; * Viscount and Lady Violet Dangen, old painted snuff box; * Sir Oscar Clayton, pair of silver ash trays; * Sir William Gordon Cumming, silver-headed owl scent bottle; * [[Social Victorians/People/Mandeville|Viscountess Mandeville]], small green leather travelling bag; * Mrs Coupland, silver crucifix; * Canon Searle, benetier [font for holy water]; * Lady Brougham and Vaux, old gold-mounted scent bottle; * Lady Clifford and Miss Towneley, silver looking-glass; * Lord Asburton, silver box; * Lady Algernon Gordon Lennox, inlaid tortoiseshell box; * Dowager Duchess of Newcastle, silver tray; * Lord and Lady Charles Beresford, small Louis XVI. table; * Sir Frederick and Lady Milner, silver tray; * Sir Bache Cunard, scent bottle with gold top set with diamonds; * Mrs G. Cavendish-Bentick [sic], pair of small old silver vases; * Mr and Mrs  Edward Sassoon, Sèvres china inkstand; * Mr J. B. and Lady Rose Leigh, Chippendale table; * Lord and Lady Henry Nevill, complete silver tea set; * Mr Horace Farquhar, two girandoles; * Colonel Ralph Vivian, umbrella with gold handle; * the servants at Wadhurst Park and 18, Carlton House terrace, large silver salver; * the Wadhurst tenants and tradesmen, large silver cup; * Wadhurst Park stablemen, driving whip and hunting crop. To the Bridegroom. — * From the bride, turquoise and diamond pin, ruby and diamond ring; * Marquesa de Santurce, a brougham, sapphire and diamond pin, ruby and diamond horseshoe pin; * Mr C. and Mr A. de Murietta, pair of guns; * Lord and Lady William Nevill, set of crystal and sliver liqueur cups and bottles on crystal and silver tray; * Count Terro-Arias, silver-mounted paper knife; * Duc de Alba, phaeton; * Mr J. Grenfell, silver cigarette case; * Lord Richard Nevill, leather box, containing cards, counters, &c.; * Sir W. Gordon Cumming, old silver box; * Duchess de Alto, set of books; * M. and Mdme. Escandon, sapphire and diamond pin; * Count Estrados, gold match box.<ref name=":1" /> </blockquote> == Notes and Questions == # ==References== {{reflist}} kucklv7cip1avhqed5re4n4dh3mxi22 2835233 2835230 2026-09-30T22:27:34Z Scogdill 1331941 /* The House Party */ 2835233 wikitext text/x-wiki = Wedding of Miss Clarita de Murietta and the Duc de Santona = ==Overview== This wedding is between Spanish Catholics, but it took place in England. ==Logistics== * ===Staff and Vendors=== * ==Related Events== * Reception * Honeymoon ==Who Was Present== ===Bride and Bridesmaids=== ====Bride==== ====Bridesmaids==== ====Pages==== ===Groom and Best Man=== ===People Who Attended=== # The Prince of Wales ==What People Wore== # ==Gifts== ===Unusual or Interesting Gifts=== ==Anthology== The Marques and Marquesa of Santurce hosted a house party and then the reception for the wedding of their daughter, Miss Clarita de Murietta, and the Duc de Santona. ==== The House Party ==== This ''Bedfordshire Mercury'' report includes both the house party and some information about the wedding as well. Given the focus on [[Social Victorians/People/Louisa Montagu Cavendish|Louisa, Duchess of Manchester]] and her daughter-in-law [[Social Victorians/People/Mandeville|Consuelo, Lady Mandeville]], the ''Bedfordshire Mercury'' looks like a paper local to them.<blockquote>The Duchess of Manchester, Vicountess Mandeville and Lord Kimbolton were among the guests entertained by the Marques and Marquesa de Santurce at their residence, Carlton House-terrace, London, on the occasion of the marriage of their younger daughter, Mdlle. Clarita de Murrieta, with the Due de Santona, last Wednesday. The ceremony took place at Brompton Oratory, where the floral  decorations were most elaborate, whole trees of white lilac and camelias, besides a profusion of arums and lilies of the valley, being artistically arranged about the sanctuary and in adjacent chapels. An orchestra of nearly 40 string instruments, with the organ, performed for three-quarters of hour before the time fixed, 11.30. The bridesmaids were Mdlle. de Mitjans (sister of the bridegroom), the Hon. Muriel and Hon. Marie Brassey, Miss Joan Nevill, Miss Violet Gathorne-Hardy, and Miss Constance Barron. Mr Francis de Murrieta, cousin of the bride, was best man. The Bishop of Southwark performed the nuptial rite, and afterwards said Mass, assisted by the Rev. W. F. Gordon, and other Fathers; Gounod’s "Messe Solennelle" was sung by nearly 40 voices, and his "Ave Maria," adapted from Bach, by a Master Hawkins. The Prince of Wales, the Duchess of Leinster and Lady Helen Duncombe, Viscountess Hood, Lady Frances and Lady Clementine Pratt, the Hon. C. R. and Mrs Spencer, Mr Grenfell, Mr and Mrs Hulse, &c., were also of the bridal company. The Duchess of Manchester wore at the church a long velvet mantle trimmed with sable, which almost concealed her grey dress. The donors of wedding presents included the Empress Eugénie, the Prince and Princess of Wales, the Duke and (Princess Louise) Duchess of Fife, Mr Alfred Rothschild, &c. The Duchess of Manchester gave the bride a pair of silver-gilt-topped scent bottles, and Lady Mandeville a small green leather travelling bag. The Duc de Santona and his bride left town for Wadhurst Park.<ref>"Kimbolton." ''Bedfordshire Mercury'' 1 February 1890, Saturday: 8 [of 8], Col. 3b [of 6]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0001290%2F18900201&page=8&article=101&stringtohighlight=mandeville+viscount. Same print title and p.</ref></blockquote> ==== The Wedding ==== This report from the ''The Sussex Express, Surrey Standard, Weald of Kent Mail, Hants and County Advertiser'' took up about 2 1/3 full columns:<blockquote>The marriage was solemnised, on Wednesday, at Brompton Oratory, with imposing ceremonial, and under most auspicious circumstances, of Juan Manuel Mitjans, Duque de Santona, a grandee of Spain, to Clarita de Murrieta, younger daughter of the Marques and Marquesa de Santurce, of Wadhurst Park, Sussex, and 18, Carlton House-terrace. The [happy event?] we now record not only attracted a numerous and brilliant congregation of the fashionable world to the service at the Oratory and the subsequent festivities, but was [invested?] with considerable interest to the wide borders of Kent and Sussex, from the sea to beyond the Weald, the bride being connected by the marriage of her sister to Lord William Nevill, last year, with the noble local families of Nevill, Gathorne-Hardy, Brassey, and Egerton. Her father, too, the Marques de Santurce, is now quite a Sussex man, having for years past been seated at Wadhurst Park. The weather was all that could desired of a winter's day, presenting a bright and cheerful contrast to the storms which have lately proved so destructive and depressing. That is to say, the wind had moderated, the sun shone brightly, and the air was tinged with exhiliarating [sic] crispness. As early ten o'clock — an hour and half before the ceremony — the holders of tickets for admission to the sacred building began to arrive, and crowd to assemble round the gateways. At eleven every seat, except those reserved for the wedding party, was oocupied, and from that time till nearly one o’clock a long line of carriages occupied both sides of the broad roadway from the Oratory to beyond South Kensington Museum. The interior of the church, long before the arrival of the bride, presented a brilliant appearance. Rays of sunshine from the clerestory windows brought into relief the beautiful floral decorations within the sanctuary. Groups tall palms and camellia trees in blooms, interspersed with white lilac and arum lilies, were placed in front of the chancel, while on the fine marble balustrade were large brass bowls filled with white azaleas, lilies of the valley, and roses. Between the massive columns separating the transepts from the aisles, were also palms and ferns interspersed with rose-tinted camellias and other flowers. The altars were also richly decorated. On the high altar were eight large bouquets of choice white exotics. The altar of Our Lady in the East transept was decked in bouquets of white, orange, and a pale shade of yellow, while that of St. Philip the west transept, was arranged with palms and scarlet and white blooms. THE CEREMONY. The choral part of the service commenced at eleven o’clock, when the choir, numbering about one hundred performers, including trumpeters and stringed instrumentalists, commenced a programme of grand sacred music. The Duke de Santona, who was attended by the bride’s cousin, Mr. Francis Murrieta, as best man, arrived several minutes before the half-hour, and awaited, at a ''prie-Dieu'' placed in front of the chancel balustrades, the coming of his ''fiance'' [sic]. The bridesmaids reached the Oratory just afterwards in readiness to take their part in the bridal procession. They were Miss Marie Mitjans (sister of the bridegroom), Miss Joan Marion Nevill (daughter of Lord Henry Nevill), Miss Violet Gathorne-Hardy (daughter of the Hon. C. C. and Lady Cicely Louisa Gathorne-Hardy), Miss Barron (daughter of Capt. and Mrs. Barron), the Hon. Muriel Agnes Brassey,  and the Hon. Marie Adelaide Brassey (daughters of Lord Brassey, of Normanhurst). Then came the Prince of Wales, who had journeyed from Sandringham specially for the occasion. His Royal Highness, attended by  Colonel Teesdale, was conducted to a seat in front of the sanctuary. The Bishop of Southwark, the Rev. Canon Searle (of Tunbridge Wells), the Rev. Father Gordon, of the Oratory, who performed the ceremony, entered the church in procession, with their attendants, from the north door of the west transept, and took their position in front of the high altar. The bride was accompanied to church by her mother, and the Marques de Santurce received his daughter at the main entrance to the nave. The bridal procession was at once formed. The fair and stately bride — fairer than most of the daughters of the sunny south — was escorted by her father through the nave and transepts to the ''prie-Dieu'' in front of the entrance to the sanctuary, the bridesmaids following, and the instrumental part of the choir performing the spirited bridal match [sic] from Lohengrin. During the first few minutes of the holy ceremony, the bride and bridegroom  remained in prayer in front of the chancel. They were then conducted to the altar, before which, the marriage service was celebrated. It occupied but a few minutes[.] The clergy, the bride and bridegroom, the Prince of Wales, the parents of the happy pair, and several of their nearest relatives repaired to the vestry to sign the register. The Prince gave his arm to the Marquesa de Santurce, and signed the register as one of the witnesses. On returning to the church Nuptial Mass was celebrated, and the whole service which occupied less than an hour, was brought to a conclusion by the Bishop bestowing the blessing of the Church upon the young couple. The music was as follows:— Before service, slow movement of minuet and trio for Italian Symphony (Mendelssohn) and Allegretto from 8th Symphony (Beethoven). As the bride entered the church, "Bridal march" from Lohengrin. While the register was signed, offertoire from "Messe Solennelle." During Mass, Gounod's "Mess Solennelle," offertory, Gounod's "Ave Maria," solo by Master Hawkins. Finale, Mendelssohn’s "Wedding March." THE DRESSES OF THE LADIES. The Bride. — The bride’s dress was of rich white Venetian brocade, with a very long court train; the front was bordered round the hem with fringes and bouquets of orange blossom, a garland of the same being arranged on the left side. The bodice had a high collar of delicate lace and a softly-draped fichu of lace and fine muslin. She wore small crown of orange-flowers and a tulle veil fastened to the hair with diamond ornaments and carried a lovely bouquet of exotics. The Bridesmaids. — The bridesmaids’ pretty costumes were of soft cream crepon, with sleeves and vests of apple green velvet; the straight skirts were edged with a single row of gold braid; and they wore sashes of pale mauve moiré, the ends of which fell from the waist in front to the feet. The two elder bridesmaids wore small bonnets of green velvet and gold braid, and the other four picturesque hats match, trimmed with the braid and several green ostrich feathers. The bridegroom's gift to each bridesmaid was also worn. It was a very handsome brooch formed of a horseshoe in diamonds and sapphires pierced by a diamond arrow; in the centre of the horseshoe were the initials "J. C." in diamonds, with a ducal coronet above in rubies and diamonds. The bridesmaids carried bouquets of lilies of the valley and green orchids, tied with mauve and green ribbons. The Bride’s Mother. — The Marquesa de Santurce's costume was entirely of dark reseda velvet, with the exception of the sleeves, which were of embossed silk with a design of foliage delicately outlined in gold. The straight collar was also of embossed brocade. The Marquesa’s bonnet was composed of two wing-like arrangements of reseda-green lisse, wrought with lines of gold, placed eave-like over the wearer's dark hair. The crown, a very tiny one, almost hidden by the wings, was of velvet embroidered in gold. The bouquet carried was an exquisite combination of white orchids, Maréchal Niel roses, and mimosa. It was tied with ribbon of the same colour as the costume. The Bridegroom's Mother. — The Marquesa de Manzanedo, the bridegroom’s mother, wore train of almost courtly proportions. It, as well as the bodice, was of dark heliotrope velvet. The bodice was made with puffed sleeves, very high on the shoulders, and a Medici collar This was faced, and the bodice bordered, with Russian sable. The skirt was of pearl-coloured brocade, backed with plaler heliotrope. It was deeply flounced with dark rich sable tail, and over it at one side a scarf of priceless Spanish lace was draped. A bonnet of lisse and velvet in corresponding tones of heliotrope colour was worn. The Marquesa carried a magnificent bouquet of orchids of the same shade her costume, arranged with varied foliage and tied with dark heliotrope ribbon. The Bridegroom's Sister.—The Duquesa de Lecera, the bridegroom's sister, was attired in a striking costume of pale pink satin striped with black. It was princess in form the stripes symetrically converging towards the waist. The skirt was bordered with soft ruche of pale pink chiffon. A pretty little bonnet composed of lisse and velvet matched the dress, and the Duquesa carried a bouquet of pale pink carnations and orchids. The Bride’s Sister.—Lady William Nevill’s dress was of Sicilienne and velvet. The form was of the polonaise order and the colour serpent-green. The skirt was quite plainly arranged, and entirely of Sicilienne. Lady William’s bonnet was of velvet, a ruche of pale pink China crêpe showing above the hair. Pink and green ospreys were placed at one side. Her bouquet was mass of pink blossoms arranged with fern fronds, and tied with serpent-green ribbon. Lady Cicely Gathorne-Hardy's dress was a pretty combination of electric-blue velvet and cashmere. There was soft vest of white China crêpe. The bonnet was of velvet, similar that of the dress; a grey and white bird was coquettishly placed at one side. Lady Cicely’s bouquet was of white roses and pink carnations. Lady Henry Nevill’s dress was made of light cloth of a pale tone of fawn-colour striped with narrow lines of brown. The sleeves and top portion of the bodice were of violet velvet. pointed panel of similar velvet showed at either side of the skirt. The cloth was drawn in folds  over the shoulders, and was caught under folds of velvet at the waist, showing deep V-shaped points of the bright-hued velvet in front and at the back. A bonnet of fawn-coloured silken gauze was covered with violet velvet pansies laid flatly on the crown. Lady Henry's bouquet was of shaded violets. Lady George Nevill wore a long mantle of dark-brown cloth broché with red. The sleeves, made high at shoulders were of dark autumnal-brown velvet, and the bonnet was of velvet, of the same colour, amid loops of which dark-red plumaged birds were nestled. Lady Idina Brassey's costume of ruby velvet was very effective, being flounced and bordered with dark fur. The hat was of felt, matching the dress in colour, and its flat crown was surrounded with dark red ostrich feathers. Lady Rose Leigh was quietly dressed in a neat tailor-made tweed gown, dark blue in colour, intercepted by narrow lines of white. A hat of dark blue felt, bordered with cock’s feathers twisted into a curl over the flat crown, looked appropriate to the studied simplicity of the dress. Lady Dorothy Nevill was attired in a long mantle of wall-flower red plush trimmed with bronze passementerie. Her headgear was a neat, closely-fitting bonnet, matching her mantle in color. The Duchess of Manchester wore a dress of silver-grey silk brocaded with satin; a section of plain satin, arranged in straight pleats, formed the back. Her Grace's mantle was of velvet — of so dark a shade of [Col. 1c–2a] myrtle green as to appear black in the shadow — and it was trimmed with lines of jet embroidery. The bonnet worn by the Duchess was of sinrlar velvet, with a spray of jet across the front. The Duchess of Leinster, who was accompanied by her sister, Lady Helen Duncombe, was attired in golden brown cloth trimmed with a design of foliage in velvet, applied to the surface of the cloth, with silk embroidery. Her Grace’s coat was of embossed silk of a delicate shade of stone colour slightly wrought with gold. The pretty but very small hat worn by the duchess was of brown felt, and her Grace's boa of ostrich feathers shaded from brown to pale stone colour. Lady Helen’s dress was of dark reddish brown woollen material, simple in form but of perfect style. Her hat was also of felt, matching her costume in colour. Lady Algernon Gordon Lennox. — A strikingly-handsome costume was that worn by Lady Algernon Gordon-Lennox. It was of bright soft-red velvet trimmed with bands of red-gold embroidery. Her bonnet was a very small one of red velvet, with a spray of ferns  simulated in jet across the front. Lady Algernon wore a long boa of sable-tail. The Dowager Countess Airlie. — Was costumed in her invariable sable robes of almost cloister-like severity, which so admirably suit her distinguished figure and beautiful face. Lady Grisel [Griselda?] Ogilvy. — Wore a black skirt, with a broad sash of pale blue moire. Her cape was of fine steel beadwork, and she wore a Henry VIII. hat of black velvet, with a group of pale blue feathers at one side. Mrs. Ronalds. — Wore a dress and mantle of black velvet bordered with sable tail, and a bonnet ''en suite''. Her daughter, Mrs. Ritchie. — Was gowned in willow-green Royal silk, and wore a bonnet of green lisse and mantle made entirely of jet beadwork. THE WEDDING GUESTS. The company present the wedding ceremony, and afterwards at the breakfast at Carlton House-terrace, included, in addition to the Prince of Wales, the Marquesa de Manzanedo and Mdlle. Maria Mitjans, the Duque and Duquesa de Lecera, the Duchess of Leinster and Lady Helen Duncombe, the Duchess of Manchester, the Dowager Countess of Airlie and Lady Griselda Ogilvy, [[Social Victorians/People/Mandeville|Viscountess Mandeville and Lord Kimbolton]], Viscountess Hood, Lord and Lady Brooke and Lady Sybil St. Clair-Erskine, Lord and Lady William Nevill, Lord Brassey, Lord and Lady George Nevill, Hon. Thomas and Lady Idina Brassey, Lord and Lady Henry Nevill, the Bishop of Southwark, Lady Frances Pratt and Lady Clementine Pratt, Lady Lister-Kaye, Lady Dorothy Nevill, Lady Cicely Gathorne-Hardy, Lady Sandhurst, Lady Alice Morland, Lord Richard Nevill, Sir Frederick and Lady Milner, Hon. C. N. Spencer, M.P., and Mrs. Spencer, Mr. and Lady Margaret Douglas, Hon. Humphrey Sturt, Sir Oscar Clayton, Lady Constance Leslie and Miss Leslie, Sir William Gordon-Cumming, Hon. Mrs. Agar-Ellis and Miss Ellis, Mons. and Madame Escandon and Mdlle. Escandon, M. Calderon, M. Errazu, M. Galintz, Mr. Frank Lee, Major Swaine, Mr. and Mrs. Granville Ward, M. de Soveral, Mr. W. H. Mitchell, the Rev. Mr. Palmer, Mr. C. de Murrieta, Mr. A. de Murrieta, Mr. Mariano de Murrieta, Mr. C. J. de Murrieta, Mr. and Mrs. Barron, Mr. Hatch, Mr. Reginald Ronalds, Mrs.  Temple Soanes, Dr. and Mrs. Robson Roose, Mr. and Mrs M. Van Raalte, Mr. Grenfell, Mrs. Bischoffsheim, Mr. Hulse, M.P., and Mrs. Hulse, Mr. Wood, Dr. White, Mrs. Ronalds and Mrs. Ritchie, Mr. Leo Schuster, Mrs. Ince Anderton, Mr. Eldrid, Mr. and Mrs. Hammond, Mr. and Mrs. E. H. Eldrid, the Rev. J. S. Welby, Mr. F. O. Smithers, Mr. and Mrs. Moreton Frewen, Mr. and Mrs. Granville Ward, Mrs. and Miss Silvertop, Mr. Gerald Paget, Mr. and Mrs. Hwfa Williams, Mr. Charles Van Raalte, Mr. Albert Stopford, Hon. Mrs. Vaughan, Miss E. Vaughan, Miss Townshend, Mrs. Coupland, Mrs. and Miss Leigh, Mr. and Mrs. F. V. Williams, and the Spanish Consul-General. THE WEDDING BREAKFAST Was served at the residence of the parents of the bride, 18, Carlton House-terrace. The Prince of Wales arrived there soon after the bride and bridegroom, when the Hungarian band, stationed in the corridor at the top of the grand staircase, played the "National anthem." Here, again, the floral decorations were superb. The table at which the Prince of Wales sat, with the bride and groom and their immediate relatives, was a mass of white and gold. The bridal colouring was supplied in the first instance by the colossal frosted structure of the cake, flanked by crescents of white orchids, orange flower, and branches of orange trees, bearing double burdens of fruit and bloom. The other six tables in the dining-room were decorated with white and the palest of blush pink, a favourite colour with the bride. The principal drawing-room was made to appear almost tropical with gorgeously-hued orchids and foliage, combining tints of vivid scarlet and bright yellow, with hundreds of shades of tender green. A stand of white lilies and pink roses placed in the entrance hall was much and deservedly admired. Nor were the charms of a second drawing-room, adorned with dozens upon dozens of double and single daffodils, passed over in silence. In the ball-room where the wedding presents were "on view," was an atmosphere laden with the subtle sweetness of fair white lilies. everywhere [sic] there were flowers, and the effect, combined with that of the brilliant sunshine which crowned the day, was to banish the recollection of January and suggest a vision of June. About three o’clock the Duque de Santona and his bride left by special train for Wadhurst Park, where they will pass the early days of the honeymoon. The bride went away in a costume of grey velvet, of a delicate shade, draped with ''Sicilienne'', and trimmed with rich steel passementerie; a broad band  of grey velvet edged the skirt, and she wore a jacket and hat to match, and sable boa and muff. THE WEDDING PRESENTS Were displayed in the ball-room, at the house of the Marquess De Santurce in Carlton House Terrace. The jewellery was simply magnificent, and the others were also costly and elegant. The presents to bride and bridegroom numbered about 500, including the following:—<ref name=":2">"Marriage of Miss de Murrieta to the Duke of Santona." ''Sussex Express'' 1 February 1890, Saturday: 7 [of 12], Cols. 1a–3a. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0000654%2F18900201&page=7&article=136&stringtohighlight=mandeville+viscount. Print title: ''The Sussex Express, Surrey Standard, Weald of Kent Mail, Hants and County Advertiser'', p. 7.</ref> [set as unordered list, originally set as separate paragraphs] TO THE BRIDE * The P<small>RINCE</small> and P<small>RINCESS</small> of W<small>ALES</small>, moonstone heart brooch, set with rubies and diamonds. * Princess L<small>OUISE</small>, Duchess of Fife, and the Duke of F<small>IFE</small>, a set of silver salt-cellars. * The Empress E<small>UGENIE</small>, a large silver mirror. * The B<small>RIDEGROOM</small>, a magnificent sapphire and diamond necklace, a sapphire and diamond bracelet, ruby and diamond ring, pearl double-heart brooch, diamond pin, diamond and pearl brooch, gold and pearl studs, and gold-handled hunting crop. * The Marquess and Marquesa <small>DE</small> S<small>ANTRUCE</small> [sic], a magnificent diamond tiara. * Marquesa <small>DE</small> S<small>ANTURCE</small>, diamond half-hoop ring. * M. M<small>ITJANS</small>, father of the bridgegroom, three rows of large pearls, with diamond and emerald clasp. * Marquesa De M<small>ANZANEDO</small>, mother of bridgeroom [sic], ruby and diamond cluster necklace. * Lord and Lady W<small>ILLIAM</small> N<small>EVILL</small>, handsome dressing bag with tortoiseshell and gold fittings, and enamel and diamond watch bracelet. * Mr. C<small>HRISTOBAL</small> and Mr. A<small>DRIANO DE</small> M<small>URRIETA</small>, diamond aigrette, and two pairs of carriage horses. * Mr. M<small>URIANO DE</small> M<small>URRIETA</small>, silver-gilt tea service and tray, three silver-gilt candelabras, and set of silver-gilt dessert plates. * The Duc and Duchesse <small>DE</small> V<small>ISTAHAMOSA</small>, complete set of silver-gilt dessert forks, knives, and spoons, and four pairs of old English silver candlesticks. * Mr. F<small>RANCIS</small> and Mr. C. J. <small>DE</small> M<small>URRIETA</small>, pair of large silver-gilt repoussé dishes. * Marques <small>DE LA</small> T<small>ORREVILLE</small>, diamond double-heart  brooch. * M. C<small>ALDERON</small>, set of diamond hair pins. * Marchioness of A<small>BERGAVENNY</small>, black point lace and tortoiseshell fan, with monogram in rubies and diamonds. * Duke and Duchess of N<small>EWCASTLE</small>, diamond and emerald watch-bracelet. * Mr. A<small>LFRED DE</small> R<small>OTHSCHILD</small>, diamond and pearl bracelet. * Lord and Lady S<small>ANDHURST</small>, gold "1890" sleevelinks. * Mdlle. M<small>ARIA</small> M<small>ITJANS</small>, large carbuncle and diamond pendant. * The S<small>PANISH</small> A<small>MBASSADOR</small>, six silver coffee cups. * Duchess of M<small>ANCHESTER</small>, pair of silver-gilt-topped scent bottles. * Duchess of L<small>EINSTER</small>, old china box. * Hon. R<small>OBERT</small> and Mrs. S<small>PENCER</small>, diamond pin. * Marquis of A<small>BERGAVENNY</small>, writing set and candlestick. * Countess of D<small>ENBIGH</small>, embroidered silk blotting book. * Lady A<small>LICE</small> M<small>ORLAND</small>, silver vase. * Lord R<small>ICHARD</small> N<small>EVILL</small>, pigskin luncheon bag with complete silver fittings. * Hon. T<small>HOMAS</small> and Lady I<small>DINA</small> B<small>RASSEY</small>, leather carriage card case, with gold mountings and monogram. * Lord and Lady B<small>ROOKE</small>, Dutch silver ornament. * Viscount and Lady V<small>IOLET</small> D<small>ANGAN</small>, old painted snuff-box. * Sir O<small>SCAR</small> C<small>LAYTON</small>, pair of silver ash trays. * Sir W<small>ILLIAM</small> G<small>ORDON</small> C<small>UMMING</small>, silver-headed scent bottle. * Viscountess M<small>ANDEVILLE</small>, small green leather travelling bag. * Mrs. C<small>OUPLAND</small>, silver crucifix. * Canon S<small>EARLE</small>, benetier. * Lady B<small>ROUGHAM</small> and V<small>AUX</small>, old gold-mounted scent  bottle. * Lady C<small>LIFFORD</small> and Miss T<small>OWNELEY</small>, silver looking-glass. * Lord A<small>SHBURTON</small>, silver box. * Lady A<small>LGERNON</small> G<small>ORDON</small>-L<small>ENNOX</small>, inlaid tortoiseshell box. * Dowager Duchess of N<small>EWCASTLE</small>, silver tray. * Lord and Lady C<small>HARLES</small> B<small>ERESFORD</small>, small Louis XVI table. * Sir F<small>REDERICK</small> and Lady M<small>ILNER</small>, silver tray. * Sir Bach Cunard, scent bottle with gold top set with diamonds. * Mrs. G. C<small>AVENDISH</small>-B<small>ENTINCK</small>, pair of small old silver vases. * Mr. and Mrs. E<small>DWARD</small> S<small>ASSOON</small>, Sevres china ink-stand. * Mr. J. B. and Lady R<small>OSE</small> L<small>EIGH</small>, Chippendale table. * Lord and Lady H<small>ENRY</small> N<small>EVILL</small>, complete silver tea set. * Mr. H<small>ORACE</small> F<small>ARQUHAR</small>, two girandoles. * Colonel R<small>ALPH</small> V<small>IVIAN</small>, umbrella with gold handle. * T<small>HE</small> S<small>ERVANTS AT</small> W<small>ADHURST</small> PA<small>RK AND</small> 18, C<small>ARLTON</small> H<small>OUSE-TERRACE</small>, large silver salver. * T<small>HE</small> W<small>ADHURST</small> T<small>ENANTS AND</small> T<small>RADESMEN</small>, large silver cup. * W<small>ADHURST</small> P<small>ARK</small> S<small>TABLEMEN</small>, driving whip and hunting crop. * Marquis C<small>AMDEN</small> and Lady C<small>LEMENTINE</small> P<small>RATT</small>, silver box. * Mr. R<small>ICARDO DE LA</small> Q<small>UININA</small>, Minton china tea and coffee set and dinner service. * Mr. H<small>EREDIM</small>, diamond and enamel watch bracelet. * Duque and Duquesa <small>DE</small> L<small>ACERA</small>, diamond and sapphire brooch. * Mr. and Mrs. D. Y<small>BARROMDO</small>, large silver bowl. [Col. 2c–3a] * Mr. F. V. and Miss W<small>ILLIAMS</small>, four silver-gilt salt cellars. * Miss L<small>EIGH</small>, leather letter holders. * Duqe and Duquesa <small>DE</small> F<small>ERNAN</small>-N<small>UNEZ</small>, old Spanish fan. * Duque and Duquesa <small>DE</small> A<small>LBA</small>, old Spanish fan. * Mrs. and the Misses C<small>ARROLL</small>, silver hand-glass. * Lord George N<small>EVILL</small>, hunting crop. * Lady George N<small>EVILL</small>, silver photo frame. TO THE BRIDEGROOM. * The Bride, turquoise and diamond pin, and ruby and diamond ring, and Cabochen sapphire and diamond sleeve links. * The Marquesa <small>DE</small> M<small>ANZANEDO</small>, emerald and diamond  pin. * The Marquesa <small>DE</small> S<small>ANTURCE</small>, a brougham, sapphire and diamond pin, and ruby and diamond horseshoe pin. * Mr. C. and Mr. A. <small>DE</small> M<small>URRIETA</small>, pair of guns. * Lord and Lady W<small>ILLIAM</small> N<small>EVILL</small>, set of crystal and silver liqueur cups and bottles on crystal and silver tray. * Mr. F<small>RANCIS DE</small> M<small>URRIETA</small>, silver looking-glass. * Mr. C. J. <small>DE</small> M<small>URRIETA</small>, pearl pin. * Count T<small>ORRE</small>-A<small>RIAS</small>, silver-mounted paper knife. * Comte <small>DE LA</small> P<small>ATELLA</small>, pearl pin.   * Count <small>DE</small> B<small>ENATUA</small>, Rahi [?] cart. * The Duque and Duquesa <small>DE</small> L<small>ECERA</small>, gold links and studs. * Duc <small>DE</small> A<small>LBA</small>, phaeton. * Mr. J. G<small>RENFELL</small>, silver cigarette case. * Mr. T<small>HOMAS</small> W<small>OOD</small>, umbrella and cigar case. * Lord R<small>ICHARD</small> N<small>EVILL</small>, leather box, containing cards, counters, &c. * Mr. P. <small>DE</small> G<small>ALINDEZ</small>, silver cigar case. * Madame <small>DE LOS</small> H<small>EROS</small>, tea basket. * Duchesse <small>DE</small> A<small>LIAGA</small>, set of books. * M. and Madame E<small>SCAUDON</small>, sapphire and diamond pin. * Count E<small>STRADOS</small>, gold match-box. * M. R<small>AMON DE</small> E<small>RRAZU</small>, silver-fitted dressing bag. * M. L<small>UTS DE</small> E<small>RRAZU</small>, diamond pin. * Sir W<small>ILLIAM</small> G<small>ORDON</small>-C<small>UMMING</small>, old silver box. * The S<small>ERVANTS</small> at Wadhurst and 18, Carlton House-terrace, pair of silver-mounted riding whips.<ref name=":2" /> </blockquote>This report from the ''Tunbridge Wells Journal'' is a good example of a regional paper covering an event from a local perspective.<blockquote>On Wednesday morning, the Brompton Oratory was crowded to witness the nuptials of Miss Clarita de Murietta, daughter of the Marques and Marquesa de Santurce, of Wadhurst Park, Sussex, and Carlton House terrace, and the Duc de Santona. The event was invested with considerable interest to Kent and Sussex, the bride being connected by the marriage of her sister to Lord W. Nevill, with the families of Nevill, Gathorne-Hardy, Brassey, and Egerton. The Oratory was beautifully decorated with palms and ferns and white flowers. The service was fully choral and during the celebration of the nuptial mass selected music was rendered. The Prince of Wales, attended by Colonel Teesdale, was present. The Bishop or Southwark, assisted by Father Gordon and the Fathers of the Oratory, officiated. The bridge [sic] was conducted to the high altar by her father, the Marques de Santurce, who gave her away. A cousin of the bride, Mr Francis de Murietta, accompanied the Duc de Santona as best man. The bridesmaids wore dresses of soft cream crêpon, with sleeves and vests in vert pomme velvet edged with gold braid, straight skirts edged with the same, and slashes of pale mauve moiré. Two of the bridesmaids wore bonnets and the other four hats of green velvet  ornamented with gold braid and green ostrich feathers. The bridegroom's presents were a diamond arrow piercing a diamond and sapphire horseshoe, surmounted by ducal coronet in rubies and diamonds, and a "good-year" bouquet of lilies of the valley and green orchids tied with mauve streamers. The bridesmaids were Mdlle. Mara [?] Mitzans [s/b Mitjans], slater of the bridegroom, Miss Constance Barrow, daughter of Captain and Mrs Barrow, Miss Ivan Marion Nevill, daughter of Lord and Lady H. G. R. Nevill, Miss Violet Gathorne-Hardy, daughter of the Hon. C. G. and Lady Cicely Louisa Gathorne-Hardy, the Hon. Muriel Agnes Brassey, and the Hon. Marie Adelaide Brassey, daughters of Lord Brassey. The bride's dress was of rich white Venetian brocade, with long train, the front being bordered with fringes and bouquets of orange blossoms. The bodice had a high collar of lace, and a fichu of lace and fine muslin, softly draped. She wore a small crown of real orange blossoms, surmounted by a fine tulle veil. After the ceremony, the wedding party proceeded to 18, Carlton House terrace, the town residence of the Marques and Marquisa de Santurce, where a déjeuner and reception were held, the Hungarian band playing selected airs on the grand staircase. The honeymoon is to be spent at Wadhurst Park. The bride's going away dress was of a delicate shade of grey velvet, draped with Siciliéune, and trimmed with rich steel passementerie, with hat to match. The following is a list of the more important presents:— [Col. 6b–c] To the Bride. —<ref name=":1">"Marriage of Miss de Murietta." ''Tunbridge Wells Journal'' 6 February 1890, Thursday: 2 [of 8], Col. 6b–c [of 6]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0004632%2F18900206&page=2&article=036&stringtohighlight=mandeville+viscount. Same print title and p.</ref> [gifts list below set as unordered list to make it easier to read] * From the Prince and Princess of Wales, moonstone heart brooch, set with rubies and diamonds; * Princess Louise, Duchess of Fife, and the Duke of Fife, a set of silver-gilt salt cellars; * the Empress Eugénie, a large silver mirror; * the bridegroom, a magnificent sapphire and diamond necklace, a sapphire and diamond bracelet, ruby and diamond ring, pearl double-heart brooch, diamond pin, diamond and pearl brooch, gold and pearl studs, and gold-handled hunting crop; * the Marques and Marquesa de Santurce, a magnificent diamond tiara; * Marquesa de Santurce, diamond half-loop ring; * M. Mitzans, father of the bridegroom, three rows of large pearls, with diamond and emerald clasp; * Marquesa de Manzanedo, mother of bridegroom, ruby and diamond cluster necklace; * Lord and Lady William Nevill, handsome dressing bag with tortoiseshell and gold fittings, and enamel and diamond watch bracelet; * Mr Christobal and Mr Adriano de Murietta, diamond aigrette, and two pairs of carriage horses; * Mr Muriano de Murietta, silver-gilt tea service and tray, three sliver-gilt candelabras, and set of silver-gilt dessert plates; * the Duc and Duchesse de Vistahamosa, complete set of silver-gilt dessert forks, knives and spoons, and four pairs of old English silver candlesticks; * Mr Francis and Mr C. J. de Murietta, pair of large silver-gilt repoussé dishes; * Marquess de Ia Torreville, diamond double-heart brooch; * M. Calderon, set of diamond hairpins; * Marchioness of Abergavenny, black point lace and tortoiseshell fan, with monogram in rubies and diamonds; * Duke and Duchess of Newcastle, diamond and emerald watch-bracelet; * Mr Alfred de Rothschild, diamond and pearl bracelet; * Lord and Lady Sandhurst, gold "1890" sleeve links; * Mdlle. Maria Mitzans, large carbuncle and diamond pendant; * the Spanish Ambassador, six sliver coffee cups; * Duchess of Manchester, pair of silver-gilt-topped scent bottles; * Duchess of Leinster, old china box; * Hon. Hobert and Mrs Spencer, diamond pin; * Marquess of Abergavenny, writing set and candlestick; * Countess of Denbigh, embroidered silk blotting book; * Lady Alice Morland, silver vase; * Lord Richard Nevill, pigskin luncheon bag, with complete silver fittings; * Hon. Tomas and Lady Idina Brassey, leather carriage card-case with gold mountings and monogram; * Lord and Lady Brooke, Dutch silver ornament; * Viscount and Lady Violet Dangen, old painted snuff box; * Sir Oscar Clayton, pair of silver ash trays; * Sir William Gordon Cumming, silver-headed owl scent bottle; * [[Social Victorians/People/Mandeville|Viscountess Mandeville]], small green leather travelling bag; * Mrs Coupland, silver crucifix; * Canon Searle, benetier [font for holy water]; * Lady Brougham and Vaux, old gold-mounted scent bottle; * Lady Clifford and Miss Towneley, silver looking-glass; * Lord Asburton, silver box; * Lady Algernon Gordon Lennox, inlaid tortoiseshell box; * Dowager Duchess of Newcastle, silver tray; * Lord and Lady Charles Beresford, small Louis XVI. table; * Sir Frederick and Lady Milner, silver tray; * Sir Bache Cunard, scent bottle with gold top set with diamonds; * Mrs G. Cavendish-Bentick [sic], pair of small old silver vases; * Mr and Mrs  Edward Sassoon, Sèvres china inkstand; * Mr J. B. and Lady Rose Leigh, Chippendale table; * Lord and Lady Henry Nevill, complete silver tea set; * Mr Horace Farquhar, two girandoles; * Colonel Ralph Vivian, umbrella with gold handle; * the servants at Wadhurst Park and 18, Carlton House terrace, large silver salver; * the Wadhurst tenants and tradesmen, large silver cup; * Wadhurst Park stablemen, driving whip and hunting crop. To the Bridegroom. — * From the bride, turquoise and diamond pin, ruby and diamond ring; * Marquesa de Santurce, a brougham, sapphire and diamond pin, ruby and diamond horseshoe pin; * Mr C. and Mr A. de Murietta, pair of guns; * Lord and Lady William Nevill, set of crystal and sliver liqueur cups and bottles on crystal and silver tray; * Count Terro-Arias, silver-mounted paper knife; * Duc de Alba, phaeton; * Mr J. Grenfell, silver cigarette case; * Lord Richard Nevill, leather box, containing cards, counters, &c.; * Sir W. Gordon Cumming, old silver box; * Duchess de Alto, set of books; * M. and Mdme. Escandon, sapphire and diamond pin; * Count Estrados, gold match box.<ref name=":1" /> </blockquote> == Notes and Questions == # ==References== {{reflist}} 50bjnwg2vxkaq6ff8a9zuq78bzvdl0e 0 332289 2835229 2026-09-30T22:13:18Z IanVG 2918363 started page on thermodynamic properties 2835229 wikitext text/x-wiki ''T''hermodynamic properties are macroscopic characteristics of a system that can be assigned a numerical value when the system is in a specified state. Examples of properties include pressure, temperature, volume, internal energy, enthalpy and entropy. Thermodynamic properties can help describe the current [[Introduction to thermodynamics/State, process, and cycle|state]] of a system, and changes in state. As you may recollect, a thermodynamic system at specified state, can be described by many different properties. Some systems have the peculiar property that a defined number of properties can completely define the state (such as two for an ideal gas). == Properties and state == An important characteristic of a thermodynamic property is that its value depends only on the current state of the system, not on the process by which the system reached that state. Consider a a system that moves from state 1 to state 2. The change in a property such as specific internal energy is <math>\Delta u = u_2 - u_1</math> regardless of the process taken from state 1 to state 2. This differentiates properties from other thermodynamic quantities such as ''heat'' and ''work'', which describe transfers of energy that occur during a process. Thus a system cannot contain heat or work, but rather accept or reject energy in forms such as ''heat'' or ''work''. Their values will depend on the path followed during a process, hence they are path-dependent variables. And thus, heat and work are not thermodynamic properties. == Common thermodynamic properties == pzmjpq5eqjw87kgkxk52x2xtedsdrmp 2 332290 2835290 2026-10-01T08:47:18Z Jeanne Noiraud 1366702 Created page with "WikiZotRef is a prototype of tool to convert wikitext with references into a Word file including references linked to the user's personal Zotero library." 2835290 wikitext text/x-wiki WikiZotRef is a prototype of tool to convert wikitext with references into a Word file including references linked to the user's personal Zotero library. iqrqoftvjhkxjo5t9slt1uh6438a3z6 6 332291 2835322 2026-10-01T10:18:53Z Young1lim 21186 {{Information |Description=Block CLA 2B Single Level (20260930 - 20260929) |Source={{own|Young1lim}} |Date=2026-10-01 |Author=Young W. Lim |Permission={{self|GFDL|cc-by-sa-4.0,3.0,2.5,2.0,1.0}} }} 2835322 wikitext text/x-wiki == Summary == {{Information |Description=Block CLA 2B Single Level (20260930 - 20260929) |Source={{own|Young1lim}} |Date=2026-10-01 |Author=Young W. Lim |Permission={{self|GFDL|cc-by-sa-4.0,3.0,2.5,2.0,1.0}} }} == Licensing == {{self|GFDL|cc-by-sa-4.0,3.0,2.5,2.0,1.0}} lbzqxvj1vooca5zkyrugu7a44q0zj2d 6 332292 2835324 2026-10-01T10:19:51Z Young1lim 21186 {{Information |Description=Block CLA 2B Single Level (20261001 - 20260930) |Source={{own|Young1lim}} |Date=2026-10-01 |Author=Young W. Lim |Permission={{self|GFDL|cc-by-sa-4.0,3.0,2.5,2.0,1.0}} }} 2835324 wikitext text/x-wiki == Summary == {{Information |Description=Block CLA 2B Single Level (20261001 - 20260930) |Source={{own|Young1lim}} |Date=2026-10-01 |Author=Young W. 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Lim |Permission={{self|GFDL|cc-by-sa-4.0,3.0,2.5,2.0,1.0}} }} 2835327 wikitext text/x-wiki == Summary == {{Information |Description=Block CLA 2C Multi Level (20261001 - 20260930) |Source={{own|Young1lim}} |Date=2026-10-01 |Author=Young W. Lim |Permission={{self|GFDL|cc-by-sa-4.0,3.0,2.5,2.0,1.0}} }} == Licensing == {{self|GFDL|cc-by-sa-4.0,3.0,2.5,2.0,1.0}} slbn1fr2ba1ep48icma4laip10ilp2u 6 332295 2835329 2026-10-01T10:37:43Z Young1lim 21186 {{Information |Description=C04.SA0: Address and Dereference Operators (20261001 - 20260930) |Source={{own|Young1lim}} |Date=2026-10-01 |Author=Young W. Lim |Permission={{self|GFDL|cc-by-sa-4.0,3.0,2.5,2.0,1.0}} }} 2835329 wikitext text/x-wiki == Summary == {{Information |Description=C04.SA0: Address and Dereference Operators (20261001 - 20260930) |Source={{own|Young1lim}} |Date=2026-10-01 |Author=Young W. 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